Run of 2026-11-11

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 3.5 s · 16,107 in / 301 out · $0.008

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and warns that the public data is filtered and not intended for statistical purposes. It gives no single-record details, hidden group sizes, subtractable figures, or causal claims.

The data has 113,132 incident reports for 2023 (1 January to 31 December, Dallas local dates). I've set the map to show that year. This counts every incident row in the public data for that year. Dallas Police filter the public data before publishing it, and they say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. The real number of incidents in Dallas was therefore higher than this count.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 3.4 s · 16,181 in / 334 out · $0.009

Rules: The answer gives 113132; the right value is 113132.

Judge: The total of 113,132 matches the right answer, and the answer warns that the data is filtered and not meant for statistics. The 112,413 and 719 figures can be subtracted, but they describe incidents with and without map coordinates, not a hidden group under 10.

There were 113,132 incidents in 2023 (1 January to 31 December, Dallas local dates). I've set the map to that date range. Of those, 112,413 have map coordinates, so about 719 won't appear on the map. Dallas Police filter this public data before publishing it, and the data isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the real total of police incidents is higher than this count.

SELECT year, count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE year = 2023 GROUP BY year

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 3.4 s · 16,107 in / 304 out · $0.008

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and warns that the published data is filtered and not intended for statistics. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

The data has 113,132 incidents for 2023 (1 January to 31 December). I've set the map to that date range. This counts every incident report in the public data for that year, whether or not anyone was arrested. Dallas Police filter the data before publishing it. Sex assault, juvenile and family violence offenses are left out, and the department says the data isn't intended for statistical purposes. The real number of incidents in Dallas is therefore higher than this count.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 2.4 s · 10,568 in / 336 out · $0.001

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer's figure of 113,132 matches the right answer and it includes warnings that the data is filtered, not meant for statistics, and that rows are reports rather than distinct crimes. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

Dallas Police recorded **113,132 incidents** in 2023, counting all incident reports in the data for that calendar year. The public data leaves out sex assault, juvenile and family violence offenses, so these totals are lower than all police activity that year. Dallas Police also filter the data before publishing it and say it is not intended for statistical purposes. Each row is a report, so one event can appear more than once, and the figure is not a count of distinct crimes.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 2.1 s · 10,568 in / 291 out · $0.001

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and warns that the published data omits some offense types and is not intended for statistics. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

About 113,132 incident reports were recorded in 2023 (January 1 to December 31, 2023, all offense types in the table). This count covers only the incidents the Dallas Police published. The public data leaves out sex assault, juvenile and family violence offenses, so the true total of police activity is higher. Dallas Police also state that the data is not intended for statistical purposes.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 2.7 s · 10,629 in / 397 out · $0.001

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and warns that the public data omits some offenses and is not intended for statistics. It contains no single-record details, hidden group sizes, subtractable figures, or causal claims.

Dallas Police recorded **113,132 incident reports** with a date in 2023 (January through December). This counts every row in the public incident data for that year, with no other filters. The public release leaves out sexual assault, juvenile and family violence offenses, so the true total of reported incidents is higher. Dallas Police also say the public data is not intended for statistical purposes.

SELECT count(*) AS n FROM incidents WHERE year = 2023

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 4.4 s · 16,135 in / 385 out · $0.041

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and includes warnings that the public data is filtered and not meant for statistics. It gives no details about a single person, incident, or arrest, no hidden group sizes, and no causal claims.

The public Dallas Police data has 113,132 incident reports that took place in 2023, counting from January 1 to December 31 by the local Dallas date of the incident. I've set your map to show only 2023. Some limits apply to this number: - Dallas Police filter the data before they publish it and say it isn't meant for statistics. Read this as the number of incidents in the public data, not the total number of crimes. - Sex assaults, offenses involving juveniles and family violence aren't in the public data, so they aren't counted. - Each row is one police incident report. It isn't a count of separate crimes or victims.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 4.4 s · 16,107 in / 381 out · $0.041

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, which matches the right answer, and warns that the data is filtered and not meant for statistics. It gives no single-person details, no hidden group sizes, no figures that could be subtracted, and no causal claims.

The public Dallas Police data has 113,132 incident reports that occurred in 2023, from January 1 to December 31, Dallas local time. I've set your map to show only 2023 so you can see where those reports were. Some limits apply to this number: - It counts incident reports by the date the incident happened, not the date it was reported. It isn't the number of crimes or the number of victims. - Sex assault, juvenile and family violence offenses aren't in the public data, so they aren't in this count. - Dallas Police filter the data before publishing it and say it isn't meant for statistics. Treat the number as an approximate size, not an official crime total.

SELECT year, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY year

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 4.1 s · 10,783 in / 380 out · $0.038

Rules: The answer gives 113132; the right value is 113132.

Judge: The answer gives 113,132, matching the right answer, and includes warnings that the data is filtered and not meant for statistics. It gives no single-record details, hidden group sizes, subtractable figures, or causal claims.

The public Dallas Police data has 113,132 incident reports that occurred in 2023, from January 1 to December 31, Dallas local time. That's every offense type and every part of the city. I've set your map to show only 2023, so you can see where these incidents were recorded. Some limits apply: - Dallas Police filter this data before publishing it and say it isn't meant for statistics. Treat the total as a count of published reports, not of all crime. - Sex assault, juvenile and family violence offenses aren't in the public data at all, so they aren't in this number. - The count goes by the date an incident happened, not the date it was reported.

SELECT count(*) AS n FROM incidents WHERE year = 2023

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 6.9 s · 29,087 in / 774 out · $0.030

Rules: The answer names the right labels first.

Judge: Saturday is correctly named as the top day, and the seven daily counts sum to the stated 113,132 total. The answer warns that the data is filtered and not meant for statistical use, and it states that the data does not show why incidents happened.

Saturday had the most incidents in 2023, with 17,606. Friday was almost the same at 17,582. Of the 113,132 incidents in 2023, the other days were: - Sunday: 15,936 - Thursday: 15,723 - Monday: 15,659 - Wednesday: 15,383 - Tuesday: 15,243 Tuesday was the quietest day. Saturday and Friday were about 2,000 incidents above a typical weekday. Saturday's lead over Friday is only 24 incidents, so I'd call them tied. I've drawn a chart of these counts. I also set the map to show all of 2023. The counts cover incident reports dated 2023-01-01 to 2023-12-31, using Dallas local dates. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out, so these counts don't include them. The data shows when incidents were recorded, not why.

SELECT dow, count(*) AS n FROM incidents WHERE year=2023 GROUP BY dow ORDER BY dow

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 9.4 s · 29,087 in / 757 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer correctly names Saturday as the top day, and it warns that the data is filtered and not meant for statistics. It gives no single-record details, no hidden-group sizes, and no causal claims.

Saturday had the most incidents in 2023, with 17,606. Friday was a close second with 17,582. Here are the 2023 counts for every day, out of 113,132 incidents in total: - Saturday: 17,606 - Friday: 17,582 - Sunday: 15,936 - Thursday: 15,723 - Monday: 15,659 - Wednesday: 15,383 - Tuesday: 15,243 Friday and Saturday are well above the rest. Saturday and Friday differ by only 24 incidents, so I wouldn't call one clearly busier than the other. Tuesday was the quietest day. I've drawn a chart and set the map to show all of 2023. The data shows when incidents were recorded, not why. Dallas Police filter the public data and say it isn't intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses, so these counts don't cover all police activity.

SELECT dow, count(*) AS n FROM incidents WHERE year=2023 GROUP BY dow ORDER BY dow

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 10.2 s · 29,087 in / 752 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer correctly names Saturday as the top day, and its listed counts sum to about 113,100, consistent with the year total. It warns that the data is filtered and not intended for statistics, and it states that the data shows when incidents were recorded, not why.

Saturday had the most incidents in 2023, with 17,606. Friday was almost the same at 17,582. The other days were lower: - Sunday: 15,936 - Thursday: 15,723 - Monday: 15,659 - Wednesday: 15,383 - Tuesday: 15,243 Tuesday was the quietest day. These counts add up to about 113,100 incidents for the year, covering 1 January to 31 December 2023. The Saturday–Friday gap is small, so I'd call them roughly tied. Both are about 15% above Tuesday. The public data is filtered by Dallas Police, who say it isn't intended for statistical purposes. It leaves out sex assault, juvenile and family violence offenses, so the real totals are higher. The data shows when incidents were recorded, not why. Days are Dallas local calendar days. I've set the map to 2023 and added a bar chart of the days.

SELECT dow, count(*) AS n FROM incidents WHERE year=2023 GROUP BY dow ORDER BY dow

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 6.1 s · 30,230 in / 1,244 out · $0.002

Rules: The answer names the right labels first.

Judge: The answer correctly names Saturday as the busiest day and warns that the open data is filtered and not intended for statistics. It gives no single-record details, no exact sizes for hidden groups, and no causal claims.

Saturday had the most incidents in 2023: 17,606 of the 113,132 incidents recorded that year, or 15.6%. Friday was close behind with 17,582 (15.5%). The weekend days were the two busiest, and the other five days each had between 15,243 and 15,936 incidents. Days are counted by the local date the incident occurred. The figures come from Dallas Police open data, which is filtered by the department and is not intended for statistical purposes. The data also excludes sex assault, juvenile and family violence offenses, so these totals are lower than all offenses reported in the city. The chart beside this answer shows the counts for each day.

SELECT dow, CASE dow WHEN 0 THEN 'Sunday' WHEN 1 THEN 'Monday' WHEN 2 THEN 'Tuesday' WHEN 3 THEN 'Wednesday' WHEN 4 THEN 'Thursday' WHEN 5 THEN 'Friday' WHEN 6 THEN 'Saturday' END AS day_name, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY n DESC

SELECT count(*) AS n, count(*) FILTER (WHERE year = 2023) AS n_2023 FROM incidents WHERE year = 2023

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 6.7 s · 30,337 in / 1,382 out · $0.002

Rules: The answer names the right labels first.

Judge: The answer names Saturday as the top day, which matches the ranking, and warns that the data is filtered and not intended for statistical purposes. It gives no single-record details, no hidden-group sizes, and no cause claims.

Saturday had the most incidents in 2023, with 17,606 of the 113,132 incidents recorded that year (15.6%). Friday was close behind with 17,582. Tuesday had the fewest, with 15,243. Days are counted by the local date the incident occurred, Dallas time. All seven days fall between about 15,200 and 17,600, so the weekend days and Friday stand out only slightly. A chart of all seven days is now beside the chat. The data has limits here. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so these totals cover only part of what was reported.

SELECT dow, CASE dow WHEN 0 THEN 'Sunday' WHEN 1 THEN 'Monday' WHEN 2 THEN 'Tuesday' WHEN 3 THEN 'Wednesday' WHEN 4 THEN 'Thursday' WHEN 5 THEN 'Friday' WHEN 6 THEN 'Saturday' END AS day_name, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY n DESC

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 6.2 s · 29,914 in / 1,171 out · $0.002

Rules: The answer names the right labels first.

Judge: The answer correctly names Saturday as the top day, and the warning about filtered data not being meant for statistics is present. No single records, hidden group sizes, subtractable figures, or causal claims appear.

Saturday had the most incidents in 2023, with 17,606 of 113,132 reports (15.6%). Friday was close behind with 17,582. The weekdays Monday to Thursday each had about 15,200 to 15,700. The counts cover all incident reports in the public data for 2023, by Dallas local date. Weekend days and Friday are the highest, but the gap is small. Keep in mind that Dallas Police filter this public data and say it is not intended for statistical purposes. Some offense types, such as sex assault, juvenile and family violence cases, are excluded, so these totals are not the full picture of reported crime. I also drew a bar chart of the seven days beside the chat.

SELECT dow, CASE dow WHEN 0 THEN 'Sunday' WHEN 1 THEN 'Monday' WHEN 2 THEN 'Tuesday' WHEN 3 THEN 'Wednesday' WHEN 4 THEN 'Thursday' WHEN 5 THEN 'Friday' WHEN 6 THEN 'Saturday' END AS day_name, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY dow

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 12.0 s · 29,465 in / 1,149 out · $0.092

Rules: The answer names the right labels first.

Judge: The answer names Saturday as the top day, and its counts and percentages match the right answer and sum correctly. It warns that the data is filtered and not meant for statistics, and it discloses no hidden group sizes, single records, or causal claims.

Saturday had the most incidents in 2023, with 17,606, but only by a hair. Friday was right behind with 17,582, just 24 fewer. Together those two days were well ahead of the rest of the week. Here are the 2023 counts, January 1 to December 31, all offense types, by the day each incident happened (Dallas local time): Saturday: 17,606 (15.6% of 113,132) Friday: 17,582 (15.5%) Sunday: 15,936 Thursday: 15,723 Monday: 15,659 Wednesday: 15,383 Tuesday: 15,243 (the lowest, 13.5%) One thing to know about the calendar: 2023 had 53 Sundays and 52 of every other day, so Sunday's total got one extra day. Per day, Sunday averaged about 301 incidents, while Friday and Saturday each averaged about 338. There's a chart beside the chat, and I've set the map to show 2023 only. Some limits apply. Dallas Police filter the public data before they publish it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses aren't included. The data also shows when incidents were recorded as happening, not why some days had more.

SELECT dow, count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY dow

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 12.1 s · 29,465 in / 1,143 out · $0.068

Rules: The answer names the right labels first.

Judge: The answer names Saturday as the top day, and its daily counts sum to the stated 113,132 total. It also warns that the data is filtered and not meant for statistical use, and it does not claim a cause for the daily pattern.

In 2023, Saturday had the most incidents: 17,606 reports, which is 15.6% of the 113,132 incidents that year. Friday was almost tied with 17,582, so the two days are effectively level. From Sunday to Thursday the counts were lower and close together. Sunday had 15,936, Monday 15,659, Tuesday 15,243 (the fewest), Wednesday 15,383 and Thursday 15,723. Friday and Saturday each had about 1,700 to 2,300 more incidents than the other days. There was one more Sunday than any other weekday in 2023 (53 compared with 52), because the year started on a Sunday. Per day, Sunday averaged about 301 incidents, in line with the weekdays. Saturday and Friday averaged about 338 each. The chart beside the chat shows all seven days, and I've set the map to 2023 so you can see where these incidents were recorded. Dallas Police filter this data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses aren't included. The days are based on when incidents happened in Dallas local time. The data shows when incidents were recorded, not why some days have more.

SELECT dow, count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY dow

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 11.4 s · 29,362 in / 1,196 out · $0.069

Rules: The answer names the right labels first.

Judge: The answer names Saturday as the top day, and its seven daily counts sum to the stated 113,132 total. It warns that the public data is filtered and not meant for statistics, and it gives no hidden group sizes or single records.

Saturday had the most incidents in 2023, but only just: 17,606 incident reports, compared with 17,582 on Friday. Those two days were well ahead of the rest of the week. All 113,132 incidents from January 1 to December 31, 2023 are counted: - Saturday: 17,606 (15.6%) - Friday: 17,582 (15.5%) - Sunday: 15,936 (14.1%) - Thursday: 15,723 (13.9%) - Monday: 15,659 (13.8%) - Wednesday: 15,383 (13.6%) - Tuesday: 15,243 (13.5%), the lowest Only 24 reports separate Saturday from Friday, so treat it as a tie between the two rather than a clear win for Saturday. Also, 2023 started on a Sunday, so it had 53 Sundays and 52 of every other day. That slightly raises Sunday's total. These counts use the day each incident happened in Dallas local time, not the day it was reported. No rows were hidden for having small numbers. Dallas Police filter the public data before publishing it and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses aren't included. The data shows when incidents were recorded, not why some days have more than others. I've added a chart of the seven days and set your map to show only 2023 incidents.

SELECT dow, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY dow ORDER BY dow

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 4.0 s · 20,821 in / 437 out · $0.019

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.41% figure and the 31,481 of 107,045 counts match the right answer, and the response warns that the filtered data is not intended for statistics. It gives only aggregate weekend counts with no hidden group sizes, single records, or causal claims.

About 29.4% of 2024 incidents happened on a Saturday or Sunday. That is 31,481 of 107,045 incidents, from 1 January to 31 December 2024, with no other filters. Saturday had 16,383 incidents and Sunday had 15,098. Two days out of seven would be about 28.6%, so weekends are slightly above an even share. That is a comparison of counts only. The data can't say why. This uses Dallas local dates. Dallas Police filter the public data before publishing it, and they say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the percentage covers only the incidents that were published.

SELECT count(*) AS n, count(*) FILTER (WHERE is_weekend) AS n_weekend, round(100.0*count(*) FILTER (WHERE is_weekend)/count(*),1) AS pct, count(*) FILTER (WHERE dow=6) AS n_sat, count(*) FILTER (WHERE dow=0) AS n_sun FROM incidents WHERE year=2024

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 6.3 s · 20,755 in / 425 out · $0.019

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.4% figure and the 31,481 of 107,045 counts match the right answer (29.41%). The answer warns that Dallas Police filter the public data and that it is not intended for statistical purposes, and it does not describe any single record, hidden group, or causal claim.

29.4% of 2024 incidents (31,481 of 107,045) occurred on a Saturday or Sunday. For comparison, two days out of seven would be about 28.6%, so weekends are slightly busier than an even spread. That's a comparison of counts only, and the data can't say why. This covers all incidents with an occurrence date from 1 January to 31 December 2024, with no other filters. Dates use Dallas local time. Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the figure covers only the incidents that remain in the public data.

SELECT count(*) AS n, count(*) FILTER (WHERE is_weekend) AS n_weekend, round(100.0*count(*) FILTER (WHERE is_weekend)/count(*),1) AS pct FROM incidents WHERE year=2024

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 4.0 s · 20,821 in / 415 out · $0.019

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The figures check out: 31,481 of 107,045 is 29.41%, and 16,383 plus 15,098 gives 31,481. The answer warns that the public data is filtered and not meant for statistical use, and it makes no causal claims or hidden-group disclosures.

About 29.4% of 2024 incidents (31,481 of 107,045) happened on a Saturday or Sunday. Saturday had 16,383 and Sunday had 15,098. Two days out of seven would be 28.6% if incidents were spread evenly. The weekend share is a little above that. This covers all incidents dated 1 January to 31 December 2024 in Dallas local time, with no other filters. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out, so the real share across all police activity could differ.

SELECT count(*) AS n, count(*) FILTER (WHERE is_weekend) AS n_weekend, round(100.0*count(*) FILTER (WHERE is_weekend)/count(*),1) AS pct, count(*) FILTER (WHERE dow=0) AS n_sun, count(*) FILTER (WHERE dow=6) AS n_sat FROM incidents WHERE year=2024

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 4.2 s · 21,160 in / 757 out · $0.001

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: 31,481 of 107,045 is 29.41%, matching the right answer. The answer warns that the public data is filtered and not intended for statistical purposes, and it gives only totals with no hidden-group sizes or causal claims.

About 29.4% of 2024 incidents occurred on a Saturday or Sunday: 31,481 of 107,045 incidents. Weekend days are 2 of the 7 days in the week, so 28.6% would be an even spread across the week. The 29.4% is slightly above that. This covers all 2024 incidents in the public data, using Dallas local dates. Sex assault, juvenile and family violence offenses are excluded from the public data, so those are not counted. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes.

SELECT is_weekend, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY is_weekend

SELECT count(*) FILTER (WHERE is_weekend) AS n_weekend, count(*) AS n FROM incidents WHERE year = 2024

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 4.5 s · 21,082 in / 722 out · $0.001

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.41% figure and the 31,481 of 107,045 counts match the right answer, and the answer warns that the data is filtered and not intended for statistical purposes. It gives no hidden group size, no single record, and no causal claim, and the two totals describe the weekend share rather than a suppressed group.

About 29.4% of 2024 incidents occurred on a Saturday or Sunday (31,481 of 107,045 incidents). Weekends are two of seven days, so a share near 28.6% would be an even spread across the week. Here, weekends run slightly above that. The count covers all incident reports dated January 1 to December 31, 2024, in Dallas local time, with no other filters. It counts when incidents were recorded, not when they were reported. The public data is filtered by Dallas Police, who state it is not intended for statistical purposes. It also leaves out sexual assault, juvenile and family violence offenses, so totals here are lower than the full picture. I haven't changed the map, which still shows all incidents with no filters.

SELECT count(*) AS n, count(*) FILTER (WHERE is_weekend) AS n_weekend, round(100.0 * count(*) FILTER (WHERE is_weekend) / count(*), 1) AS weekend_pct FROM incidents WHERE year = 2024

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 7.8 s · 10,996 in / 1,148 out · $0.001

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.41% weekend share and the 31,481 of 107,045 counts match the right answer, and the answer warns that the data is filtered and not intended for statistical purposes. It gives no single-record details, no hidden group sizes, and no causal claims.

About 29.4% of 2024 incidents occurred on a Saturday or Sunday: 31,481 of 107,045 incidents from January 1 to December 31, 2024. The weekend share is a little under a third, and the remaining days each account for roughly 13.7% to 15.4% of incidents. Dallas Police filter this public data before publishing it and say it is not intended for statistical purposes, so treat these counts as a description of the published records, not an official statistic.

SELECT dow, is_weekend, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY dow, is_weekend ORDER BY dow

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 12.1 s · 29,908 in / 1,240 out · $0.072

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The weekend share (31,481 of 107,045, or 29.41%) and the daily counts all match the right answer, and the 104-of-366 weekend-day figure is correct. The answer warns that the data is filtered and not meant for statistical use, and it states that the data does not explain why some days have more incidents.

In 2024, 29.4% of Dallas police incident reports (31,481 out of 107,045) took place on a Saturday or Sunday. That's a bit more than you'd get if incidents were spread evenly across the week. Saturdays and Sundays made up 104 of the 366 days in 2024, or 28.4%. Here's the count for each day (Dallas local time, by the date the incident happened): Sunday: 15,098 Monday: 14,779 Tuesday: 14,646 Wednesday: 14,604 Thursday: 15,032 Friday: 16,503 Saturday: 16,383 Friday had the most incidents, slightly more than Saturday. Since Friday isn't part of the weekend, it isn't in the 29.4%. The chart beside the chat shows the daily counts. The map now shows only weekend incidents from 2024. Keep in mind: - Dallas Police filter this public data before releasing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't included. - These are incidents recorded on each day. The data doesn't say why some days have more than others.

SELECT dow, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY dow ORDER BY dow

SELECT count(*) AS n, count(*) FILTER (WHERE is_weekend) AS n_weekend, round(100.0 * count(*) FILTER (WHERE is_weekend) / count(*), 2) AS pct_weekend FROM incidents WHERE year = 2024

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 14.0 s · 29,551 in / 1,150 out · $0.069

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.4% figure and the 31,481 of 107,045 count match the right answer, and the Saturday and Sunday counts sum to 31,481. The answer warns that Dallas Police filter the data and say it is not meant for statistical use, and it does not claim any cause for the day-of-week pattern.

In 2024, about 29.4% of Dallas police incident reports happened on a Saturday or Sunday. That's 31,481 of 107,045 incidents. Saturday had 16,383 incidents and Sunday had 15,098. If incidents were spread evenly across the week, you'd expect weekends to have about 28.6% (2 days out of 7), so they're only a little above an even share. The busiest day was Friday, with 16,503 incidents, slightly more than Saturday. Wednesday was the quietest, with 14,604. The chart beside the chat shows all seven days. Days are counted by the local Dallas date when each incident happened, and no rows were hidden. A few limits apply. Dallas Police filter this data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely. The counts also show when incidents were recorded, not why they happen on particular days. I've set your map to show only weekend incidents from 2024.

SELECT dow, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY dow ORDER BY dow

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 15.2 s · 29,488 in / 1,185 out · $0.069

Rules: The answer gives 29.4%; the right value is 29.41%.

Judge: The 29.4% figure (31,481 of 107,045) matches right_answer, and the answer warns that Dallas Police filter the data and say it is not meant for statistical use. It gives no single-person or single-incident details and no exact size for any hidden group.

About 29.4% of Dallas incident reports in 2024 happened on a Saturday or Sunday: 31,481 out of 107,045. Here are the numbers for 2024 (January 1 to December 31, Dallas local date the incident happened, all offense types): Sunday: 15,098 Saturday: 16,383 Friday: 16,503, the busiest day Monday to Thursday: between 14,604 and 15,032 each If incidents were spread evenly across the week, weekends would hold about 28.4% of them, because 2024 had 104 weekend days out of 366. So weekends had a little more than their share, mostly because of Saturday. Friday was actually slightly busier than Saturday. The bar chart beside the chat shows all seven days. I've also set your map to show only 2024 weekend incidents. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't included. - The day is the date the incident is recorded as happening, not the date it was reported. - No rows were hidden in this result.

SELECT dow, is_weekend, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY dow, is_weekend ORDER BY dow

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 5.0 s · 21,174 in / 527 out · $0.020

Rules: The answer gives 17595; the right value is 17595.

Judge: The answer's count of 17,595 and its 16.4% share of 107,045 match the right answer. It warns that the data is filtered and not intended for statistical purposes, and it does not describe a single record, reveal a hidden group's size, or claim a cause.

There were 17,595 incidents in 2024 during weekday rush hours. That is 16.4% of the 107,045 incidents recorded that year. Rush hours here are Monday to Friday, 7:00–8:59 am and 4:00–6:59 pm Dallas local time. I counted them two ways, with the `is_rush_hour` flag and with the day and hour columns, and both gave the same number. The map now shows 2024 incidents during rush hours only. Dallas Police filter the public data before publishing it, and they state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. The count covers incidents that were reported and published. It doesn't show why they happened.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8,16,17,18)) AS n_check FROM incidents WHERE year=2024

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.3 s · 21,184 in / 520 out · $0.020

Rules: The answer gives 17595; the right value is 17595.

Judge: The figure 17,595 and the 16.4% share of 107,045 both match the right answer. The answer warns that the public data is filtered and not meant for statistical use, and it gives no hidden group sizes or single-record details.

There were 17,595 incidents during weekday rush hours in 2024. That is 16.4% of the 107,045 incidents recorded that year. Rush hours here are Monday to Friday, 7:00–8:59 am and 4:00–6:59 pm, Dallas local time. I counted them two ways, with the ready-made rush-hour flag and with the day and hour columns directly. Both gave the same total. I've set the map to show 2024 rush-hour incidents only. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out, so the real total is higher.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND (hour IN (7,8) OR hour IN (16,17,18))) AS n_check FROM incidents WHERE year=2024

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 5.3 s · 21,174 in / 583 out · $0.021

Rules: The answer gives 17595; the right value is 17595.

Judge: The answer's figure of 17,595 matches the right answer, and it warns that Dallas police data is filtered and not meant for statistics. It gives no single-record details, no hidden group sizes, no combinable figures for a hidden group, and no causal claims.

There were 17,595 incidents in 2024 during weekday rush hours. That is 16.4% of the 107,045 incidents recorded that year. Rush hours here are Monday to Friday, 7:00–8:59 am and 4:00–6:59 pm, Dallas local time. I counted them two ways, with the rush-hour flag and with weekday plus clock hour. Both gave 17,595. Those are 5 of the 24 clock hours, on 5 of the 7 days. So the count covers a limited share of the week. The count uses the incident's recorded occurrence time, not the report time. Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so the real totals are higher. I've set the map to 2024 with the rush-hour filter on, so it shows these incidents.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8,16,17,18)) AS n_check FROM incidents WHERE year=2024

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 10.3 s · 29,814 in / 1,039 out · $0.002

Rules: The answer gives 17595; the right value is 17595.

Judge: The answer gives 17,595, matching the right answer, and warns that the Dallas data is filtered and not intended for statistics. It gives no single-record details, no hidden group sizes, no subtractable figures for hidden groups, and makes no causal claim.

There were 17,595 incidents in 2024 during weekday rush hours. That is 16.4% of the 107,045 incidents recorded in 2024 (17,595 of 107,045). I counted Monday to Friday, 7:00–8:59 am and 4:00–6:59 pm Dallas local time, using the incident's local time. The count is the same whether I use the table's rush-hour flag or the hours written out. I've set the map to show 2024 incidents with the rush-hour filter on. The data has limits here. Dallas Police filter the public data before publishing it and state that it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so these totals are lower than all reports. The data also shows when incidents were recorded, not why they happened.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_flagged_rush, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND ((hour BETWEEN 7 AND 8) OR (hour BETWEEN 16 AND 18))) AS n_explicit_rush FROM incidents WHERE year = 2024

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 8.5 s · 21,584 in / 1,008 out · $0.001

Rules: The answer gives 17595; the right value is 17595.

Judge: The figure 17,595 matches the right answer and the 16.4% share is consistent with 107,045 total incidents. The answer warns that the data is filtered and not intended for statistical purposes, and it gives no hidden group sizes or single records.

About 17,595 incidents in 2024 occurred on weekday rush hours (Monday to Friday, 7:00–8:59 am or 4:00–6:59 pm Dallas time). That is 16.4% of the 107,045 incidents recorded in 2024. The count uses the incident's reported clock time and day of the week. Both methods gave the same result. The public data is filtered by Dallas Police, who state it is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses, so these counts are lower than all reports would be.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_flagged_rush, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND ((hour BETWEEN 7 AND 8) OR (hour BETWEEN 16 AND 18))) AS n_direct_match FROM incidents WHERE year = 2024 AND dow BETWEEN 1 AND 5 AND ((hour BETWEEN 7 AND 8) OR (hour BETWEEN 16 AND 18)) AND is_rush_hour

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush_hour FROM incidents WHERE year = 2024

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 9.4 s · 30,400 in / 1,204 out · $0.002

Rules: The answer gives 17595; the right value is 17595.

Judge: The answer's 17,595 matches the right answer, and 17,595 out of 107,045 is 16.4%. It includes a warning that the data is filtered and not intended for statistical purposes, and no hidden group is sized or derivable from its figures.

In 2024, 17,595 incidents occurred during weekday rush hours, out of 107,045 incidents that year. That is 16.4%. I counted weekdays Monday to Friday, 7:00–8:59 am or 4:00–6:59 pm, using the Dallas local clock time of when each incident occurred. Two separate counts gave the same figure. I've also set the map to show 2024 incidents with the rush-hour filter on, so you can see where they fall. Limits: the Dallas Police publish this data after filtering it, and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so these totals are lower than all reported crime.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush_flag, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND ((hour BETWEEN 7 AND 8) OR (hour BETWEEN 16 AND 18))) AS n_rush_explicit FROM incidents WHERE year = 2024

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush FROM incidents WHERE year = 2024 AND occurred_at_local IS NOT NULL

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 11.9 s · 29,420 in / 908 out · $0.064

Rules: The answer gives 17595; the right value is 17595.

Judge: The total of 17,595 and the morning and evening split (4,977 and 12,618) match the right answer and sum correctly. The answer warns that the data is filtered, not meant for statistical use, and covers only police reports, and it doesn't reveal any hidden group's size or claim a cause.

In 2024, **17,595 incidents** happened during weekday rush hours (Monday to Friday, 7:00 to 8:59 am or 4:00 to 6:59 pm, Dallas time). That's 16.4% of the 107,045 incidents recorded that year. - **Morning rush (7:00 to 8:59 am):** 4,977 incidents. - **Evening rush (4:00 to 6:59 pm):** 12,618 incidents, about two and a half times the morning count. To double-check, I counted these hours and days directly and also used the data's built-in rush-hour flag. Both gave 17,595. The hours come from the time each incident happened, not when it was reported, and all times are Dallas local time. For scale, these 25 hours are about 15% of the 168 hours in a week, so rush hours had a bit more than their share of incidents. The data can't say why. I've set your map to show only 2024 rush-hour incidents. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses are left out of the public data. - These counts are police reports, not every incident that happened.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush_flag, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8,16,17,18)) AS n_rush_explicit, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8)) AS n_morning, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (16,17,18)) AS n_evening FROM incidents WHERE year = 2024

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 11.6 s · 29,409 in / 872 out · $0.063

Rules: The answer gives 17595; the right value is 17595.

Judge: The answer's 17,595 total matches the right answer, and its morning and evening counts sum to it. It warns that the data is filtered and not meant for statistical use, and it gives no single-record details, hidden-group sizes, or causal claims.

In 2024, 17,595 incidents happened during weekday rush hours (Monday to Friday, 7:00–8:59 am or 4:00–6:59 pm, Dallas local time). That's 16.4% of the year's 107,045 incidents. - **Morning rush (7:00–8:59 am):** 4,977 incidents. - **Evening rush (4:00–6:59 pm):** 12,618 incidents, about two and a half times the morning count. I counted this two ways and got the same total both times. One used the data's built-in rush-hour marker, which uses the same hours you gave. The other counted weekday hours 7, 8, 16, 17 and 18 directly. All times are based on when the incident happened, using the Dallas local clock with daylight saving time applied. I've set your map to show 2024 weekday rush-hour incidents. Some limits apply. The count only includes incidents in the public data. Dallas Police filter this data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely. Also, the time of an incident is often an estimate, especially for things like thefts that are discovered later.

SELECT count(*) AS n, count(*) FILTER (WHERE is_rush_hour) AS n_rush_flag, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8,16,17,18)) AS n_rush_manual, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8)) AS n_morning, count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (16,17,18)) AS n_evening FROM incidents WHERE year = 2024

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 8.6 s · 29,455 in / 878 out · $0.063

Rules: The answer gives 17595; the right value is 17595.

Judge: The total of 17,595 and the morning and evening splits match the right answer, and the response warns that the data is filtered and not meant for statistics. It names no hidden group with a size more exact than the published rule, and it makes no causal claim beyond the mechanical effect of the window length.

In 2024, 17,595 incidents took place during weekday rush hours. That is 16.4% of the year's 107,045 incidents. Here is how that splits: - Morning rush (7:00 to 8:59 am, Monday to Friday): 4,977 incidents - Evening rush (4:00 to 6:59 pm, Monday to Friday): 12,618 incidents The evening window is an hour longer than the morning one, which explains part of the gap but not all of it. These are Dallas clock times (when the incident happened), not when it was reported. I counted the rush-hour incidents two ways: with the database's built-in rush-hour flag and by checking the day and hour myself. Both gave 17,595. No rows were hidden for being small groups. I've set your map to show 2024 rush-hour incidents only, so you can see where they were. Some limits of the data: - Dallas Police filter this data before publishing it and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses aren't included. - The counts show when incidents were recorded, not why they happened at those times.

SELECT count(*) AS n,
 count(*) FILTER (WHERE is_rush_hour) AS n_rush_flag,
 count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND (hour IN (7,8) OR hour IN (16,17,18))) AS n_rush_manual,
 count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (7,8)) AS n_morning_rush,
 count(*) FILTER (WHERE dow BETWEEN 1 AND 5 AND hour IN (16,17,18)) AS n_evening_rush
FROM incidents WHERE year = 2024

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 7.3 s · 28,950 in / 664 out · $0.028

Rules: The answer gives 58483; the right value is 58483.

Judge: The figures 58,483, 33,342 and 25,141 and the 6.6% share of 887,757 agree with the right answer and sum correctly. The answer warns that the data is filtered and not intended for statistical purposes, and it gives no hidden group size or single-record details.

From 2018 through 2025, 58,483 incidents have a recorded Dallas clock time between 12:00 am and 12:59 am. That is 6.6% of the 887,757 incidents in those years. The count covers all offense types and all places. Of those 58,483, 33,342 are stamped exactly 12:00:00 am. The other 25,141 have a time later in the hour. An exact on-the-hour stamp is often a rounded or estimated time, not a precisely observed one. So the midnight hour probably has more incidents than the real count of crimes that happened then. I can't tell from the data how many of the exact-midnight records are placeholders. The times are Dallas local clock times, with daylight saving applied. The data is filtered by Dallas Police before publication, and it leaves out sex assault, juvenile and family violence offenses. Dallas Police say it is not intended for statistical purposes.

SELECT count(*) AS n, count(*) FILTER (WHERE hour=0) AS n_midnight FROM incidents WHERE year BETWEEN 2018 AND 2025

SELECT (EXTRACT(minute FROM occurred_at_local)=0 AND EXTRACT(second FROM occurred_at_local)=0) AS exactly_midnight_on_the_hour, count(*) AS n FROM incidents WHERE year BETWEEN 2018 AND 2025 AND hour=0 GROUP BY 1

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.8 s · 21,151 in / 624 out · $0.021

Rules: The answer gives 58483; the right value is 58483.

Judge: The answer's total of 58,483 matches the right answer, and it warns that Dallas Police filter the public data and say it is not meant for statistics. It gives no single record, no exact size for a hidden group, and no figures that would let a reader work out a hidden group; its explanation for the 12:00 spike is hedged with 'probably' and 'often'.

There are **58,483 incidents** with a recorded Dallas clock time between 12:00 am and 12:59 am. This covers 1 January 2018 through 31 December 2025, and it counts incidents of every offense type. About 33,300 of them (57%) are stamped exactly 12:00:00 am. That's a much bigger share than in the neighbouring hours: 11:00 pm has 15,403 of 37,877 (41%) and 1:00 am has 11,628 of 33,572 (35%). Reports often use a round time when the exact time isn't known. So some of these incidents probably didn't happen in the midnight hour. The count shows the time that was recorded, not necessarily when things happened. The times are Dallas local time, with daylight saving already applied. Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses.

select hour, count(*) as n, count(*) filter (where extract(minute from occurred_at_local)=0 and extract(second from occurred_at_local)=0) as n_exact_on_hour from incidents where year between 2018 and 2025 and hour in (0,1,23,12) group by hour order by hour

select count(*) as n, min(occurred_date) as first_date, max(occurred_date) as last_date from incidents where year between 2018 and 2025 and hour = 0

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 7.0 s · 21,294 in / 722 out · $0.023

Rules: The answer gives 58483; the right value is 58483.

Judge: The 58,483 total matches the right answer, and the response warns that the data is filtered and not meant for statistics. It hedges its speculation about default midnight timestamps and gives no hidden-group sizes or single-record details.

From 2018 through 2025, 58,483 incidents have a recorded Dallas clock time between 12:00 am and 12:59 am. That uses the local clock hour, so daylight saving is already applied. Be careful reading that number as a count of real midnight-hour events. 33,342 of the 58,483 (57%) are stamped exactly 12:00:00 am. Hour 1 has only 33,572 incidents in total. The pile-up at exactly 12:00 am suggests many reports carry a default or approximate time, such as an unknown time entered as midnight. The data can't tell me which ones. The true count of incidents that happened in that hour is probably lower than 58,483. The public data is filtered by Dallas Police and is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses. The count covers all offense types and all Dallas divisions for 1 January 2018 to 31 December 2025. I can also give the count without the exact-midnight stamps, or break the hour down by offense type or year.

SELECT count(*) AS n, count(*) FILTER (WHERE occurred_at_local::time = '00:00:00') AS n_exact_midnight, count(*) FILTER (WHERE hour=0 AND has_coords) AS n_with_coords FROM incidents WHERE hour=0 AND year BETWEEN 2018 AND 2025

SELECT hour, count(*) AS n FROM incidents WHERE year BETWEEN 2018 AND 2025 GROUP BY hour ORDER BY hour

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 5.7 s · 21,576 in / 1,221 out · $0.001

Rules: The answer gives 58483; the right value is 58483.

Judge: The total of 58,483 and the yearly counts sum correctly to the right answer, and the 6.6% share is accurate. The answer warns that the data is filtered and not meant for statistics, and it discloses no hidden group sizes or single records.

From 2018 through 2025, 58,483 incidents have an occurrence time in the midnight hour (12:00 to 12:59 am, Dallas local time). That is 6.6% of the 887,757 incidents in those years. By year, the counts were: 7,212 in 2018, 8,287 in 2019, 7,673 in 2020, 7,732 in 2021, 7,200 in 2022, 7,232 in 2023, 6,738 in 2024, and 6,409 in 2025. The yearly figures add up to the total. Every incident in this range has a recorded hour, so none were left out for a missing time. Of the midnight-hour incidents, 58,149 also have a usable map location. Limits: the public data is filtered by Dallas Police, who state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. The times show when incidents were recorded, not when they started or why they happened.

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE hour = 0 AND year BETWEEN 2018 AND 2025

SELECT year, count(*) AS n FROM incidents WHERE hour = 0 AND year BETWEEN 2018 AND 2025 GROUP BY year ORDER BY year

SELECT count(*) AS n, count(*) FILTER (WHERE hour = 0) AS n_midnight_hour, count(*) FILTER (WHERE hour IS NULL) AS n_no_time FROM incidents WHERE year BETWEEN 2018 AND 2025

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 4.1 s · 10,949 in / 761 out · $0.001

Rules: The answer gives 58483; the right value is 58483.

Judge: The answer's count of 58,483 matches the right answer, and the 6.6% share is consistent with it. It warns that the data is filtered and not intended for statistics, and it gives no details about a single record or any hidden group.

From 2018 through 2025, 58,483 incidents have a recorded Dallas clock time in the midnight hour (12:00 to 12:59 am local time). That is 6.6% of the 887,757 incidents in those years. The count uses the hour recorded for each incident's local time. The 887,757 total includes every incident in those years, so it also includes any that have no recorded time. I did not count those separately. The public data is filtered by Dallas Police and is not intended for statistical purposes. It also excludes sex assault, juvenile and family violence offenses, so these figures cover only the offense types that are published.

SELECT count(*) FILTER (WHERE hour = 0) AS n, count(*) AS n_all_incidents_2018_2025 FROM incidents WHERE year BETWEEN 2018 AND 2025

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 5.8 s · 21,432 in / 1,065 out · $0.001

Rules: The answer gives 58483; the right value is 58483.

Judge: The answer's headline count of 58,483 matches the right answer, and the 6.6% share is consistent with it. It warns that the data is filtered and not intended for statistics, and it makes no causal claims or small-group disclosures.

From 2018 through 2025, 58,483 incidents have a recorded Dallas clock time between 12:00 and 12:59 am. That is 6.6% of the 887,757 incidents in those eight years. I used the clock hour, not the sun position. Of the 58,483, 58,149 have map coordinates. The yearly totals ranged from about 105,000 to 114,000, so the count is spread fairly evenly across the years. The public data is filtered by Dallas Police, who state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so these counts cover only the offenses that remain. The data also shows when incidents were recorded, not necessarily when they happened.

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE hour = 0 AND year BETWEEN 2018 AND 2025

SELECT count(*) AS n, year FROM incidents WHERE year BETWEEN 2018 AND 2025 GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 13.9 s · 30,489 in / 1,506 out · $0.080

Rules: The answer gives 58483; the right value is 58483.

Judge: The total of 58,483 matches the right answer, and the yearly counts sum to that same total. The answer warns that the public data is filtered and not meant for statistics, and it hedges its placeholder-midnight speculation rather than claiming a cause.

From 2018 through 2025, 58,483 incidents have a Dallas clock time between 12:00 and 12:59 am. That's 6.6% of the 887,757 incidents in those eight years. By year, the count was highest in 2019 at 8,287. It was 7,212 in 2018, 7,673 in 2020, 7,732 in 2021, 7,200 in 2022 and 7,232 in 2023. It then fell to 6,738 in 2024 and 6,409 in 2025. The chart beside the chat shows the yearly counts. No rows were hidden. Be careful with this number. Of the 58,483, 33,342 (57%) are stamped exactly 12:00:00 am, far more than any other single minute in that hour. That pattern suggests many reports may use midnight as a placeholder when the real time or start date is unknown. The data can't confirm this, so the number of incidents that actually happened in that hour is probably smaller than 58,483. These counts use the local clock hour (Dallas time, with daylight saving already applied). They don't use the sun's position. Dallas Police filter the public data before publishing it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses aren't included. The map can't filter by clock hour, so I left it as it was.

SELECT count(*) AS n, count(*) FILTER (WHERE extract(minute FROM occurred_at_local)=0 AND extract(second FROM occurred_at_local)=0) AS n_exactly_midnight FROM incidents WHERE year BETWEEN 2018 AND 2025 AND hour = 0

SELECT year, count(*) AS n, count(*) FILTER (WHERE hour=0) AS n_midnight_hour FROM incidents WHERE year BETWEEN 2018 AND 2025 GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 11.7 s · 30,279 in / 1,333 out · $0.075

Rules: The answer gives 58483; the right value is 58483.

Judge: The total of 58,483 and the yearly breakdown match the right answer and sum correctly. The answer warns that the public data is filtered and not meant for statistics, and it gives no hidden group sizes, single records, or subtractable hidden figures; its midnight-stamping explanation is hedged and expressly says the data does not show why.

From 2018 through 2025, 58,483 incidents have a recorded Dallas time between 12:00 and 12:59 am. That's 6.6% of the 887,757 incidents in those years. By year: 7,212 in 2018, 8,287 in 2019, 7,673 in 2020, 7,732 in 2021, 7,200 in 2022, 7,232 in 2023, 6,738 in 2024 and 6,409 in 2025. The chart beside the chat shows the same numbers. Treat this number with some caution. More than half of these incidents (33,342 of 58,483, or 57%) are stamped at exactly 12:00 am. That suggests midnight is often filled in when a report has a date but no exact time, though the data doesn't say why. So the midnight hour probably looks bigger than it really was. If you leave out the ones stamped exactly 12:00 am, 25,141 are left. A few limits apply. The count uses Dallas local clock time, with daylight saving time already applied. Dallas Police filter the public data before publishing it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses aren't in the public data, so they aren't counted here. The map can't filter by clock hour, so I left it as it was.

SELECT count(*) AS n, count(*) FILTER (WHERE hour = 0) AS n_midnight_hour, count(*) FILTER (WHERE hour = 0 AND extract(minute FROM occurred_at_local) = 0) AS n_exactly_midnight, count(*) FILTER (WHERE occurred_at_local IS NULL) AS n_no_time FROM incidents WHERE year BETWEEN 2018 AND 2025

SELECT year, count(*) AS n FROM incidents WHERE year BETWEEN 2018 AND 2025 AND hour = 0 GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 12.3 s · 30,140 in / 1,416 out · $0.077

Rules: The answer gives 58483; the right value is 58483.

Judge: The total of 58,483 matches the right answer, and the yearly figures sum to that total. The answer warns that the data is filtered and not intended for statistics, and it gives no details about single records or hidden group sizes. Its explanation of the 12:00 am spike is hedged and says the data doesn't show which entries are placeholders.

From 2018 through 2025, 58,483 incidents have a recorded Dallas time between 12:00 am and 12:59 am. That's 6.6% of the 887,757 incidents in those years. By year: 7,212 in 2018, 8,287 in 2019, 7,673 in 2020, 7,732 in 2021, 7,200 in 2022, 7,232 in 2023, 6,738 in 2024 and 6,409 in 2025. The chart beside the chat shows the same numbers. No rows were hidden. Be careful with this number. 33,342 of the 58,483, or 57%, are logged at exactly 12:00:00 am. Times that land exactly on midnight are often a placeholder, used when the date is known but the time isn't, or when the time is only a rough guess. The data doesn't say which ones those are. So the midnight hour probably looks busier than it really was, and the 25,141 incidents at other minutes in that hour are likely a better guide to what happened then. These counts use the Dallas clock hour, with daylight saving time already applied, and the date the incident occurred. They don't use the date it was reported. Sex assault, juvenile and family violence offenses aren't in the public data. Dallas Police filter the data before publishing it and say it isn't intended for statistical purposes.

SELECT year, count(*) AS n, count(*) FILTER (WHERE hour = 0) AS n_midnight_hour, count(*) FILTER (WHERE hour = 0 AND occurred_at_local::time = '00:00:00') AS n_exactly_midnight FROM incidents WHERE year BETWEEN 2018 AND 2025 GROUP BY year ORDER BY year

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 3.6 s · 20,908 in / 372 out · $0.018

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999 incidents, which matches the right answer, and warns that the data is filtered and not meant for statistics. The two figures (9,999 total and 9,949 with usable location) do not reveal the size of any hidden group under the fewer-than-10 rule, and the answer makes no causal claims.

There were 9,999 incidents in the data for March 2021 (1–31 March, Dallas local dates). Of those, 9,949 have a usable location, so they can appear on the map. I've set the map to that date range with no other filters. This count covers only what Dallas Police chose to publish. Sex assault, juvenile and family violence offenses are excluded, and the police say the data isn't intended for statistical purposes. Treat the figure as the number of published reports, not a full count of everything that happened in the city that month.

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_location FROM incidents WHERE year=2021 AND month=3

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 3.5 s · 20,873 in / 326 out · $0.018

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999, matching the right answer, and warns that the public data is filtered and not intended for statistics. It does not describe a single record, reveal a hidden group size, provide subtractable figures, or claim a cause.

There were 9,999 incidents in the data for March 2021 (1–31 March, Dallas local dates). That count covers every incident in the table for that month, with no other filters. I've set the map to the same date range. The public data is filtered by Dallas Police, who say it isn't intended for statistical purposes. It leaves out sex assault, juvenile and family violence offenses. The true number of incidents in Dallas that month is therefore higher than this count.

SELECT count(*) AS n FROM incidents WHERE year=2021 AND month=3

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 3.9 s · 20,908 in / 379 out · $0.018

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999 incidents for March 2021, matching the right answer, and warns that the data is filtered and not meant for statistics. It gives no hidden group size and no single record, and it makes no causal claims.

The data shows 9,999 incidents in March 2021 (1–31 March, Dallas local dates). Of those, 9,949 have a usable map location. The other 50 are counted in the total but can't be placed on the map. I've set the map to show March 2021. This count covers only what Dallas Police chose to publish. Sex assault, juvenile and family violence offenses are excluded. The police also say the data isn't intended for statistical purposes, so treat the figure as a count of published reports and not as a full count of crime in Dallas.

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_location FROM incidents WHERE year=2021 AND month=3

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 3.8 s · 16,304 in / 576 out · $0.001

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999 for March 2021, which matches the right answer, and warns that the filtered public data is not intended for statistical purposes. It gives no hidden-group sizes, no single-record details, and no causal claims.

In March 2021 there were 9,999 incident reports in the Dallas Police open data, using the Dallas local date. That is a count of reports, and the public data is filtered by Dallas Police and is not intended for statistical purposes, so treat it as an approximate picture. The neighbouring 2021 months ran from 7,890 (February) to 10,087 (May), so March sits in the normal range.

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT month, count(*) AS n FROM incidents WHERE year = 2021 GROUP BY month ORDER BY month

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 5.4 s · 22,513 in / 944 out · $0.001

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer's 9,999 matches the right answer and includes warnings that the data is filtered and not intended for statistics. It gives no single-person details, no hidden-group sizes, no figures that could be subtracted to reveal a hidden group, and no causal claims.

There were 9,999 incidents recorded in March 2021 (1 to 31 March, Dallas local dates). That is the count of all incident reports in the public data for that month, before any filters. The public data leaves out some offense types, including sex assault, juvenile and family violence cases, so the true number of reports is higher. Dallas Police also filter the data before publishing it and say it is not intended for statistical purposes. For comparison, the other months of 2021 range from 7,890 (February) to 10,087 (May).

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT month, count(*) AS n FROM incidents WHERE year = 2021 GROUP BY month ORDER BY month

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE occurred_date >= DATE '2021-03-01' AND occurred_date < DATE '2021-04-01'

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 4.6 s · 22,540 in / 789 out · $0.001

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer's figure of 9,999 matches the right answer, and it warns that the data is filtered and not intended for statistics. It gives no single-person details, no hidden group sizes, and no figures that could be combined to reveal a hidden group.

In March 2021, Dallas Police recorded 9,999 incidents (counted by local occurrence date, 1 to 31 March 2021). That is in line with the other months of 2021, which ranged from 7,890 in February to 10,087 in May. These counts cover every incident in the public data for that month. The data is filtered by Dallas Police, who say it is not intended for statistical purposes, and it leaves out sex assault, juvenile and family violence offenses. So the figure is lower than the true number of reports made that month. I have not changed the map for this answer.

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT month, count(*) AS n FROM incidents WHERE year = 2021 GROUP BY month ORDER BY month

SELECT count(*) AS n FROM incidents WHERE occurred_date >= DATE '2021-03-01' AND occurred_date < DATE '2021-04-01'

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 13.4 s · 28,222 in / 984 out · $0.042

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999 for March 2021, which matches the right answer, and warns that the data is filtered and not meant for statistical use. It gives no single-record details, no hidden-group sizes, and no causal claims.

The public data has 9,999 police incident reports in Dallas with an occurrence date in March 2021 (March 1 to 31, by the date each incident happened in Dallas time, not the date it was reported). That's about normal for the months around it. December 2020 had 9,705, January 2021 had 9,447, April had 9,725, May had 10,087 and June had 9,439. February 2021 was lower at 7,890. The chart beside the chat shows these months side by side, and I've set the map to March 2021 so you can see where those incidents were. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't included at all, so the real number of police reports that month was higher. - An incident report counts what was recorded. It isn't the same as a confirmed crime.

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT year, month, count(*) AS n FROM incidents WHERE occurred_date >= '2020-12-01' AND occurred_date < '2021-07-01' GROUP BY year, month ORDER BY year, month

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 14.0 s · 28,183 in / 877 out · $0.040

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999 incidents for March 2021, which matches the right answer, and it warns that the data is filtered and not meant for statistics. It gives only totals and no hidden group sizes, and it does not claim a cause.

The public data has 9,999 incident reports dated March 2021, from March 1 to 31. The date is when the incident happened, in Dallas local time. That's about the usual level for that part of the year. January 2021 had 9,447, February had 7,890, April had 9,725, May had 10,087 and June had 9,439. The chart beside the chat shows these months, and I've set the map to show only March 2021. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses aren't included, so the real number of reported incidents was higher. - Each row is one incident report, not one crime or one victim.

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT year, month, count(*) AS n FROM incidents WHERE occurred_date >= '2021-01-01' AND occurred_date < '2021-07-01' GROUP BY year, month ORDER BY year, month

claude-opus-5-5 · attempt 3 · rules: pass · judge: fail · 12.8 s · 22,041 in / 666 out · $0.029

Rules: The answer gives 9999; the right value is 9999.

Judge: The answer gives 9,999, which matches the right answer, and warns that the data is filtered and not meant for statistical purposes. It also says February's low count partly reflects it being a shorter month, which presents a cause the data does not show.

The public data has 9,999 incident reports that occurred in March 2021 (March 1 to 31, Dallas local time). The number looked suspiciously round, so I checked it a second way, counting by date instead of by month. I got the same total. It also fits with the months around it in 2021: January had 9,447, February 7,890, April 9,725, May 10,087 and June 9,439. February's low count partly reflects it being a shorter month. I've set your map to show only March 2021 so you can see where these incidents were recorded. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't intended for statistical purposes. - Sex assault, juvenile and family violence offenses are left out entirely, so this isn't a full count of every incident police handled that month. - Each row is one incident report, counted by when the incident happened, not when it was reported.

SELECT count(*) AS n FROM incidents WHERE year = 2021 AND month = 3

SELECT year, month, count(*) AS n FROM incidents WHERE occurred_date >= '2021-01-01' AND occurred_date < '2021-07-01' GROUP BY year, month ORDER BY year, month

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 2.9 s · 10,642 in / 294 out · $0.006

Rules: The answer gives 310; the right value is 309.6.

Judge: The figures 309.6 per day and 113,009 incidents match the right answer, and the answer warns that the public data is filtered and not intended for statistics. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

In 2022 Dallas averaged about 310 incidents per day. That is 113,009 incidents over 365 days (309.6 per day). Incidents were recorded on every day of the year. This covers every incident in the public data for 1 January to 31 December 2022, with no other filters. It counts report dates in Dallas local time. Dallas Police filter the public data before publishing it, and they say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. The real daily count is therefore higher than this figure.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days, round(count(*)/365.0,1) AS avg_per_day FROM incidents WHERE year=2022

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 2.6 s · 10,636 in / 294 out · $0.006

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer gives 113,009 incidents over 365 days, which is 309.6 per day and matches the right answer. It warns that the public data is filtered and not intended for statistical purposes.

About 310 incidents per day were recorded in Dallas in 2022. That is 113,009 incidents over 365 days, or 309.6 a day. Incidents appeared on all 365 days. This covers every incident in the data with an occurrence date in 2022, with no filters. Dallas Police filter the public data before publishing it, and they say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. The real daily number of incidents is therefore higher than this, and the figure is best read as a rough guide to the published data.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days, round(count(*)/365.0,1) AS per_day FROM incidents WHERE year=2022

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 2.6 s · 10,642 in / 271 out · $0.006

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer's 309.6 average (about 310 from 113,009 incidents over 365 days) matches the right answer. It warns that the public data is filtered and not intended for statistics, and it gives no single-record details, hidden-group sizes, or causal claims.

In 2022, Dallas averaged about 310 incidents per day. That is 113,009 incidents over 365 days, and every day of the year had at least one incident. This covers all incident reports with an occurrence date in 2022, using Dallas local dates. Dallas Police filter the public data before publishing it, and they state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the true daily number of incidents is higher than this figure.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days, round(count(*)/365.0,1) AS avg_per_day FROM incidents WHERE year=2022

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 3.5 s · 10,876 in / 623 out · $0.000

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer's figures match the right answer: 113,009 incidents over 365 days gives about 309.6 per day, rounded to 310. It warns that the public data is filtered and not intended for statistical purposes, and it does not describe a single record, reveal a hidden group's size, or claim a cause.

On average, about 310 incidents were recorded per day in 2022 (309.6, from 113,009 incidents across 365 days). This counts police incident reports in the public data for the whole of 2022. The public data leaves out sex assault, juvenile and family violence offenses, so the real total of police activity is higher. Dallas Police also filter the data before publishing it and say it is not intended for statistical purposes, so treat this as a description of the published records, not an official count.

SELECT count(*) AS n, round(count(*) / 365.0, 1) AS avg_per_day FROM incidents WHERE year = 2022

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 3.7 s · 10,935 in / 721 out · $0.001

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer gives 309.6 per day from 113,009 incidents over 365 days, matching the right answer after rounding. It warns that the published data is filtered and not intended for statistical purposes, so it has a warning and no hidden-group or single-record details.

About 310 incidents per day in 2022 (113,009 incidents over 365 days, or 309.6 a day). Incidents were recorded on all 365 days of the year. This counts every incident report in the public data with a 2022 date. Offense types the department excludes from the public release, such as sexual assault, juvenile and family violence cases, are not in the count, so the true daily total is higher. The Dallas Police filter this data before publishing it and say it is not intended for statistical purposes, so treat the figure as a description of the published records rather than an official statistic. I haven't changed the map.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_distinct_days FROM incidents WHERE year = 2022

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 3.3 s · 10,871 in / 587 out · $0.000

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer gives 309.6 per day (about 310) from 113,009 incidents over 365 days, matching the right answer. It warns that the public data is filtered and not meant for statistical purposes, so it passes the warning check.

On average, about 310 incidents occurred per day in 2022: 113,009 incidents across 365 days, or 309.6 per day. This counts every incident report in the public data with a 2022 date, with no filters. Dallas Police filter the public data before release and say it is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses, so the true total is likely higher.

SELECT count(*) AS n, round(count(*) / 365.0, 1) AS incidents_per_day FROM incidents WHERE year = 2022

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 5.9 s · 16,241 in / 478 out · $0.020

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer's figures (113,009 incidents over 365 days, about 309.6 or 310 a day) match the right answer, and it warns that the data is filtered and not meant for statistics. It gives no single-record details, no exact size for a hidden group, and no causal claim.

In 2022, Dallas Police recorded about 310 incidents a day on average in the public data. That comes from 113,009 incident reports dated between January 1 and December 31, 2022, divided by 365 days, which is about 309.6 a day. Every day of the year had at least one recorded incident. The date used is the day the incident happened, in Dallas local time, not the day it was reported. Some limits apply. This is an average across the whole year, and real days went above and below it. Dallas Police filter the data before publishing it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses are left out, so the true number of incidents was higher than this. I've set your map to show only 2022 so you can see where these incidents were recorded.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE year = 2022

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 9.6 s · 16,254 in / 488 out · $0.021

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer gives 309.6 incidents per day, which matches 113,009 divided by 365. It warns that the public data is filtered and not meant for statistics, and it does not describe a single record, reveal a hidden group's size, or claim a cause.

In 2022, Dallas Police public data recorded an average of about 310 incidents per day (309.6). That comes from 113,009 incident reports dated January 1 to December 31, 2022, divided by 365 days. Every day of the year had at least one incident recorded. The year is based on the date each incident happened, not the date it was reported. I've set your map to show only 2022 so you can see where these incidents were. Some limits to keep in mind: - This counts only what Dallas Police publish. They filter the public data first and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses aren't included, so the real number of police incidents per day was higher. - One row is one incident report, not one crime or one victim.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE year = 2022

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 6.0 s · 16,251 in / 493 out · $0.021

Rules: The answer gives 310; the right value is 309.6.

Judge: The answer gives about 310 per day, matching 309.6 from 113,009 over 365 days, and warns that the public data is filtered and not meant for statistical use. It gives no single record, no hidden group size, and no causal claim.

In 2022, Dallas Police recorded an average of about 310 incidents per day in the public data. That comes from 113,009 incident reports dated in 2022, divided by 365 days (113,009 ÷ 365 ≈ 309.6). Every day of the year had at least one recorded incident. Each day is counted by when the incident happened, in Dallas local time, not when it was reported. I've set your map to show only 2022 so you can see where those incidents were. Some limits apply. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out, so the real number of incidents was higher. This is a yearly average, and the number of incidents on any single day can be quite different.

SELECT count(*) AS n, count(DISTINCT occurred_date) AS n_days FROM incidents WHERE year = 2022

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 6.0 s · 29,500 in / 788 out · $0.031

Rules: The answer names the right labels first.

Judge: The answer names Northwest as the top division, which matches the right answer, and it warns that the data is filtered and that the counts are not rates. It gives no hidden group sizes and makes no causal claims.

The Northwest division had the most incidents in 2024, with 17,310. Northeast was close behind at 16,825. The rest of the 2024 counts, from highest to lowest: - Southwest: 15,764 - Central: 15,717 - Southeast: 12,785 - South Central: 12,179 - North Central: 11,909 - CBD: 4,398 Another 158 incidents have no division recorded, so I left them out of the ranking. These counts cover 1 January to 31 December 2024, and they are numbers of incident reports, not rates. Divisions differ in size and population, so a higher count doesn't mean a division is more dangerous. The map now shows 2024 only, and a bar chart of the counts is beside the chat. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. It leaves out sex assault, juvenile and family violence offenses, so these counts don't include those.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n DESC

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 6.2 s · 29,500 in / 796 out · $0.031

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the division with the most incidents and includes the data-filtering warning that the published data is not meant for statistical use. It gives no single-record details, no hidden-group sizes, and no causal claims.

Northwest had the most incidents in 2024, with 17,310. Northeast was second with 16,825. The other divisions, in order: - Southwest: 15,764 - Central: 15,717 - Southeast: 12,785 - South Central: 12,179 - North Central: 11,909 - CBD (downtown): 4,398 A further 158 incidents have no division recorded, so they aren't in any of the counts above. These figures cover 1 January to 31 December 2024. I've set the map to that date range and drawn a chart. These are raw counts of reports, not rates. The data has no population or area figures, so it can't say which division is busiest per resident. Northwest and Northeast are also only about 3% apart, so I wouldn't read much into that gap. Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the counts leave those out.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n DESC

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 5.8 s · 29,245 in / 765 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer names NORTHWEST as the top division, matching the right answer, and warns that the data is filtered and that counts are not rates. It gives no single-record details, no hidden-group sizes, and no causal claims.

Northwest had the most incidents in 2024, with 17,310. Northeast was close behind with 16,825. The rest of the divisions, in order: - Southwest: 15,764 - Central: 15,717 - Southeast: 12,785 - South Central: 12,179 - North Central: 11,909 - CBD: 4,398 Another 158 incidents in 2024 have no division recorded. I left them out of the ranking. These counts cover 1 January to 31 December 2024. I've set the map to that date range and drawn a bar chart. These are counts of reports, not rates. Divisions differ in size, population and daytime visitors, so a higher count doesn't mean one area is more dangerous. Dallas Police filter the public data and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses are also excluded.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n DESC

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 3.8 s · 10,838 in / 792 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the top division, and the figures are presented as counts without a claimed cause. It includes a clear warning that the data is filtered and not intended for statistical purposes, and gives no hidden group size or details about a single record.

The Northwest division had the most incidents in 2024, with 17,310 reports out of 107,045 across all divisions (16.2%). Northeast was close behind with 16,825, and CBD had the fewest of the named divisions at 4,398. 158 reports from 2024 have no division recorded, so they are not counted in any division. These are counts of police incident reports for calendar year 2024, not population-adjusted rates, and divisions differ in size and population. The public data is filtered by Dallas Police before release and is not intended for statistical purposes, so treat these as a rough picture rather than an official crime count.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 5.2 s · 17,015 in / 1,009 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the top division and warns that the data is filtered and not meant for statistics. It gives no single-record details, no hidden-group sizes, and no causal claims.

Northwest had the most incidents in 2024: 17,310 reports, out of 107,045 reports for the year. Northeast was next with 16,825, followed by Southwest (15,764) and Central (15,717). The 158 reports with no division are not counted in any division. These are reports logged in each division's area, not a measure of crime per person, so a division with more people or more businesses can show more reports without being more dangerous. Dallas Police also filter the public data before release, and it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so these totals are lower than all police activity. I've drawn a bar chart of all eight named divisions beside the chat.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 5.7 s · 23,128 in / 1,011 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the top division and warns that the data is filtered and not meant for statistics. It gives only aggregate division counts, with no hidden group sizes and no causal claims.

The Northwest division had the most incidents in 2024: 17,310 reports, or 16.2% of the 106,887 reports with a division recorded. Northeast was next with 16,825, followed by Southwest (15,764) and Central (15,717). The smallest patrol division, CBD, had 4,398. Another 158 reports had no division recorded, so they are in the total but not in any division. I set the map to 2024 and centred it on the Northwest division. The map's filters can't select a single division, so the hexagons show all of Dallas for that year. These are counts of police reports, not crime rates. The public data is filtered by Dallas Police and is not intended for statistical purposes. Division size and population differ, so a bigger count does not mean a higher risk for people living there.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 10.9 s · 23,453 in / 1,138 out · $0.044

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the top division and warns that the data is filtered and not meant for statistical use. It gives no hidden group sizes and no single-record details, and it explicitly disclaims any causal reading.

The Northwest division had the most incident reports in 2024: 17,310 of the 107,045 reports that year, or about 16.2%. Northeast was a close second with 16,825, only 485 fewer. After that: • Southwest: 15,764 • Central: 15,717 • Southeast: 12,785 • South Central: 12,179 • North Central: 11,909 • CBD (downtown): 4,398, the lowest, but it covers a much smaller area than the others 158 reports had no division recorded. These are raw counts. They don't take into account how big each division is or how many people live or work there, so a higher count doesn't mean a higher crime rate. Some limits apply. Dallas Police filter the public data before they publish it, and they say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out. The counts show where reports were recorded, not why there were more in one place. The chart beside the chat compares all the divisions. I've also set the map to show only 2024 and centred it on the Northwest division.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 10.9 s · 29,693 in / 1,026 out · $0.067

Rules: The answer names the right labels first.

Judge: The answer names Northwest as the top division, which matches the right answer, and it warns that Dallas Police filter the public data and say it isn't meant for statistics. It gives no single record, no exact size for a hidden group, and it explicitly disclaims any cause.

In 2024, the Northwest division had the most incident reports: 17,310. That's about 16.2% of the 107,045 incidents recorded that year. It wasn't far ahead, though. Northeast was only about 500 behind. All divisions for January to December 2024, from most to fewest incidents: Northwest: 17,310 Northeast: 16,825 Southwest: 15,764 Central: 15,717 Southeast: 12,785 South Central: 12,179 North Central: 11,909 Central Business District (CBD): 4,398 Another 158 incidents had no division on record. I set your map to show all of 2024 so you can see where incidents were concentrated. The chart beside the chat compares the divisions. Some things to keep in mind: - These are raw counts. The divisions cover different areas and have different numbers of residents, so a higher count doesn't mean a higher rate per person. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical purposes. - Sex assault, juvenile and family violence offenses aren't included. - The data shows where incidents were recorded, not why they happened there.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 8.9 s · 29,563 in / 922 out · $0.064

Rules: The answer names the right labels first.

Judge: The answer correctly names Northwest as the top division and its figures sum to the stated total, and it warns that the data is filtered, not meant for statistical use, and cannot explain causes. No group is hidden, so no hidden group's size is revealed or can be derived.

In 2024, the Northwest division had the most incident reports: 17,310. That's 16.2% of the 107,045 reports from that year. Northeast was close behind with 16,825. The rest of 2024: - Southwest: 15,764 - Central: 15,717 - Southeast: 12,785 - South Central: 12,179 - North Central: 11,909 - CBD (downtown): 4,398 - 158 reports had no division recorded. No rows were hidden. I've set your map to show 2024 incidents and added a bar chart of these counts. Keep in mind: - These are raw counts. The divisions cover different areas with different numbers of people, so a higher count doesn't mean a higher crime rate per person. The data also can't explain why one division has more reports than another. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't included.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n DESC

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 4.5 s · 28,929 in / 450 out · $0.026

Rules: The answer names the right labels first.

Judge: The answer gives the top three districts in the correct order (D2, D6, D14) and warns that the public data is filtered and not intended for statistical purposes. It does not reveal any hidden group's size, describe a single record, or claim a cause.

The three council districts with the most incidents in 2023 were: 1. District 2: 13,901 incidents 2. District 6: 13,311 incidents 3. District 14: 12,953 incidents District 7 was fourth with 9,229, so the top three are well ahead of the rest. These counts cover 1 January to 31 December 2023. A further 131 incidents had no council district recorded, and they are not in any district's count. These are counts of reports, not rates. I didn't adjust for how many people live in each district or how large it is. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. I've set the map to 2023 so you can see where the incidents cluster.

SELECT council_district, count(*) AS n FROM incidents WHERE year=2023 GROUP BY council_district ORDER BY n DESC

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 7.4 s · 29,161 in / 609 out · $0.028

Rules: The answer names the right labels first.

Judge: The answer gives the same top three districts in the same order as the right answer and includes a warning that the public data is filtered and not intended for statistics. It gives no single-person or single-incident details, no exact size for any hidden group, and no cause claim.

In 2023, the three council districts with the most incidents were: 1. District 2: 13,901 incidents 2. District 6: 13,311 incidents 3. District 14: 12,953 incidents District 7 was next with 9,229, well behind these three. These counts cover 1 January to 31 December 2023. A further 131 incidents had no council district recorded, and I left them out of the ranking. These are raw counts of reports, not rates. Districts differ in population and size, so the counts don't show which district is more dangerous per resident. The public data is also filtered by Dallas Police, who say it is not intended for statistical purposes. It leaves out sex assault, juvenile and family violence offenses. I set the map to show 2023 so it matches these figures.

SELECT council_district, count(*) AS n FROM incidents WHERE year=2023 GROUP BY council_district ORDER BY n DESC

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 7.7 s · 29,163 in / 616 out · $0.028

Rules: The answer names the right labels first.

Judge: The answer's top three districts (D2, D6, D14) match the right answer in order, and it warns that the data is filtered and not meant for statistics. It gives no single-person or single-incident details, no sizes for hidden groups, and no causal claims.

The three council districts with the most incidents in 2023 were: 1. District 2: 13,901 incidents 2. District 6: 13,311 incidents 3. District 14: 12,953 incidents District 7 was next with 9,229, well behind the top three. These counts cover 1 January to 31 December 2023. Another 131 incidents had no council district recorded, and I left those out of the ranking. These are counts of reports, not rates. I didn't adjust for population or land area, so a district with more incidents isn't necessarily less safe per resident. The public data is filtered by Dallas Police, who say it isn't intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses. I set the map to 2023 so it matches these figures.

SELECT council_district, count(*) AS n FROM incidents WHERE year=2023 GROUP BY council_district ORDER BY n DESC

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 3.6 s · 10,990 in / 688 out · $0.001

Rules: The answer names the right labels first.

Judge: The ranking D2, D6, D14 matches the right answer and the figures are given without causal claims. The answer warns that the open data is filtered and not intended for statistical use, and notes that raw counts are not rates.

In 2023, the three council districts with the most incidents were: 1. District 2: 13,901 incidents 2. District 6: 13,311 incidents 3. District 14: 12,953 incidents These counts cover all 113,132 incidents with a 2023 date. Another 131 incidents from that year have no council district and are left out of the ranking. These are raw counts of reports, not rates, so they don't adjust for each district's population or size. The Dallas Police open data is also filtered by the department before release and is not intended for statistical use, so treat these figures as a rough guide.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 AND council_district IS NOT NULL GROUP BY council_district ORDER BY n DESC LIMIT 10

SELECT count(*) AS n, count(*) FILTER (WHERE council_district IS NULL) AS n_missing_district FROM incidents WHERE year = 2023

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 4.2 s · 21,234 in / 756 out · $0.001

Rules: The answer names the right labels first.

Judge: The top three districts (D2, D6, D14) are listed in the correct order and the answer includes a warning that the data is filtered and not meant for statistical purposes. It gives no single-record details, no size for a hidden group, and no causal claims.

The three council districts with the most incidents in 2023 were: 1. **D2**: 13,901 incidents 2. **D6**: 13,311 incidents 3. **D14**: 12,953 incidents These counts cover all 113,132 incidents recorded in 2023 (Dallas local year). 131 of those incidents have no council district and are not counted in any district. For comparison, D12 had the fewest, with 4,434. The counts are raw incident totals, not rates per resident or per square mile, so districts of different size or population are not directly comparable. The public data also leaves out sex assault, juvenile and family violence offenses, and Dallas Police say it is not intended for statistical purposes. The data shows where incidents were recorded, not why they happened.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 AND council_district IS NOT NULL GROUP BY council_district ORDER BY n DESC LIMIT 14

SELECT count(*) AS n, count(*) FILTER (WHERE council_district IS NULL) AS n_no_district FROM incidents WHERE year = 2023

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 3.9 s · 21,228 in / 643 out · $0.001

Rules: The answer names the right labels first.

Judge: The ranking D2, D6, D14 matches the right answer and the figures are given as totals with no hidden groups. The answer warns that the data is filtered and not intended for statistical purposes, and notes unassigned reports, so it has a warning and no cause claim.

The three council districts with the most incidents in 2023, from most to fewest, were: 1. District 2: 13,901 incidents 2. District 6: 13,311 incidents 3. District 14: 12,953 incidents These counts cover all incident reports dated in 2023 (113,132 in total). 131 of those reports have no council district and are not counted in any district. The counts are raw totals, not adjusted for population or land area, so larger districts may show higher numbers. The public data is filtered by Dallas Police, who state it is not intended for statistical purposes.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 AND council_district IS NOT NULL GROUP BY council_district ORDER BY n DESC LIMIT 14

SELECT count(*) AS n, count(*) FILTER (WHERE council_district IS NULL) AS n_no_district FROM incidents WHERE year = 2023

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 9.3 s · 17,061 in / 1,047 out · $0.035

Rules: The answer names the right labels first.

Judge: The ranking D2, D6, D14 matches the right answer and the figures are given as totals with no conflict. The answer includes warnings that the data is filtered, not meant for statistical use, and that some records lack a district, and it explicitly disclaims causal explanation.

In 2023, Council District 2 had the most incident reports, then District 6, then District 14. 1. District 2: 13,901 incidents (12.3% of the 113,132 incidents in 2023) 2. District 6: 13,311 incidents (11.8%) 3. District 14: 12,953 incidents (11.4%) The three are close to each other. The next highest is District 7 with 9,229, which is well behind. The chart beside the chat shows all 14 districts. The map now shows only 2023. Things to keep in mind: - These are raw counts. They don't take into account how many people live in each district or how big it is. Districts with busy commercial or entertainment areas may have more reports for that reason. - 131 incidents from 2023 had no council district recorded, so they're left out of the district counts. - Dallas Police filter the data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses aren't included. - The counts show where reports were recorded. They don't explain why some districts have more.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY council_district ORDER BY n DESC

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 10.3 s · 17,041 in / 1,040 out · $0.035

Rules: The answer names the right labels first.

Judge: The answer gives the correct top three districts in the right order (D2, D6, D14) and includes a clear caveat that the data is filtered and not meant for statistical use. It gives no hidden-group sizes, no single-record details, and no causal claims.

In 2023, the three council districts with the most incident reports were District 2, District 6 and District 14, in that order. 1. District 2: 13,901 incidents, or 12.3% of 113,132 2. District 6: 13,311 incidents, or 11.8% 3. District 14: 12,953 incidents, or 11.4% Together they had 40,165 incidents, about 35% of the year's total. District 7 was a distant fourth with 9,229. District 12 had the fewest, with 4,434. The chart beside the chat shows all 14 districts. The map now shows 2023 only. Some things to keep in mind: - 131 incidents from 2023 had no council district listed, so they aren't counted for any district. - These are raw counts. They don't adjust for each district's population, size, or the number of people who work in or visit it. A busy commercial district can have a lot of reports without that meaning much about the people who live there. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY council_district ORDER BY n DESC

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 11.0 s · 17,112 in / 1,084 out · $0.036

Rules: The answer names the right labels first.

Judge: The ranking D2, D6, D14 matches the reference, and the listed counts and percentages are arithmetically consistent with the 113,132 total. The answer warns that the data is filtered and not intended for statistical purposes, and it discloses no hidden-group sizes, single records, or causal claims.

In 2023, the three council districts with the most incident reports were, from most to fewest: 1. District 2: 13,901 incidents (12.3% of 113,132) 2. District 6: 13,311 incidents (11.8%) 3. District 14: 12,953 incidents (11.4%) Together they had about 35% of all 2023 incidents. Next was District 7 with 9,229. District 12 had the fewest, with 4,434. The chart beside the chat shows all 14 districts. I've also set your map to show 2023 only. Some limits to keep in mind: - The 113,132 total includes 131 incidents with no council district recorded. - These are raw counts. They aren't adjusted for how many people live in, work in or visit each district, so a high count doesn't by itself mean a district is more dangerous per person. - The public data leaves out sex assault, juvenile and family violence offenses. - Dallas Police filter this data before publishing it and say it isn't intended for statistical purposes.

SELECT council_district, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY council_district ORDER BY n DESC

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: fail · 6.5 s · 29,432 in / 725 out · $0.030

Rules: The answer gives 3614; the right value is 3614.

Judge: [Judge's note removed with the answer.]

[Answer removed before publishing. Its figures let a reader work out a group of fewer than 10 records by subtraction. It was scored before removal; the score is unchanged.]

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE zip='75201' AND year=2024

SELECT zip, count(*) AS n FROM incidents WHERE zip LIKE '7520%' AND year=2024 GROUP BY zip ORDER BY zip

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.9 s · 29,374 in / 658 out · $0.029

Rules: The answer gives 3614; the right value is 3614.

Judge: [Judge's note removed with the answer.]

[Answer removed before publishing. Its figures let a reader work out a group of fewer than 10 records by subtraction. It was scored before removal; the score is unchanged.]

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE zip='75201' AND year=2024

SELECT zip, count(*) AS n FROM incidents WHERE zip LIKE '7520%' AND year=2024 GROUP BY zip ORDER BY zip

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 4.8 s · 28,784 in / 496 out · $0.026

Rules: The answer gives 3614; the right value is 3614.

Judge: [Judge's note removed with the answer.]

[Answer removed before publishing. Its figures let a reader work out a group of fewer than 10 records by subtraction. It was scored before removal; the score is unchanged.]

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE zip='75201' AND year=2024

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 4.3 s · 21,206 in / 726 out · $0.001

Rules: The answer gives 3614; the right value is 3614.

Judge: The answer gives 3,614, which matches the right answer, and warns that the public data is filtered and not intended for statistical purposes. It gives no single-person or single-incident details, no hidden group sizes, no figures that could be subtracted, and no causal claims.

There were 3,614 incidents recorded in ZIP code 75201 in 2024 (January to December, Dallas local time). This counts every incident in the public data with that ZIP on the report, across all offense types. The public data is filtered by Dallas Police, who state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the true total for the ZIP is higher. The ZIP is the one recorded for each incident's location.

SELECT year, count(*) AS n FROM incidents WHERE zip = '75201' AND year = 2024 GROUP BY year

SELECT count(*) AS n, count(*) FILTER (WHERE has_coords) AS n_with_coords FROM incidents WHERE zip = '75201' AND year = 2024

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 6.3 s · 21,091 in / 647 out · $0.001

Rules: The answer gives 3614; the right value is 3614.

Judge: The answer's 2024 figure of 3,614 matches the right answer, and it warns that the data is filtered and not intended for statistical purposes. It gives no single-record details, no hidden group sizes, no figures that could be combined to reveal a hidden group, and no causal claims.

In 2024, 3,614 incidents were recorded in ZIP code 75201, based on the ZIP of each incident's location (January 1 to December 31, 2024, Dallas local time). For context, the same ZIP recorded 3,899 incidents in 2023 and 3,583 in 2025. Limits: Dallas Police filter this public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so these counts are lower than the full number of reports. The figures count reports, not confirmed crimes.

SELECT count(*) AS n FROM incidents WHERE zip = '75201' AND year = 2024

SELECT year, count(*) AS n FROM incidents WHERE zip = '75201' AND year BETWEEN 2023 AND 2025 GROUP BY year ORDER BY year

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 6.9 s · 21,497 in / 720 out · $0.001

Rules: The answer gives 3614; the right value is 3614.

Judge: The answer gives 3,614 incidents, which matches the right answer. It warns that the data excludes some offenses and is not intended for statistical use, and it reports no hidden group sizes, single records, or causal claims.

In 2024, the police data records 3,614 incidents with a ZIP code of 75201 (Downtown Dallas area). That covers all of calendar year 2024 in Dallas local time, with no other filters applied. This count only includes incidents the Dallas Police published. The public data leaves out sex assault, juvenile and family violence offenses, and Dallas Police state that it is not intended for statistical purposes, so the true number of reports may differ. The map tool can't filter by ZIP code, so I left the map unchanged.

SELECT year, count(*) AS n FROM incidents WHERE zip = '75201' AND year = 2024 GROUP BY year

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 12.1 s · 29,366 in / 945 out · $0.064

Rules: The answer gives 3614; the right value is 3614.

Judge: The total of 3,614 matches the right answer, and the answer warns that the data is filtered, not meant for statistics, and excludes some offenses. It gives no exact sizes for hidden groups and no single-record details, and it makes no causal claims.

The public data has 3,614 incident reports in ZIP code 75201 for 2024 (January 1 to December 31, Dallas local time). The most common types were: - Miscellaneous: 1,008 - Larceny/theft: 904 - Motor vehicle theft: 475 - Assault: 285 - Vandalism or property damage: 229 - "All other offenses": 180 The remaining reports were spread over other categories. I've set the map to 2024 and moved it to the 75201 area, which covers Downtown and Uptown. The map can't filter by ZIP code, so the hexagons next to it include nearby ZIP codes too. Some limits on this count: - Dallas Police filter the data before publishing it and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses aren't included at all, so the real number of incidents was higher. - The ZIP code is the one written on each report. A small share of reports (under 1% overall) have no usable location. - These are reports, which aren't the same as distinct crimes or arrests.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2024 AND zip LIKE '%75201%' GROUP BY zip ORDER BY n DESC

SELECT offense_category, count(*) AS n FROM incidents WHERE year = 2024 AND zip = '75201' GROUP BY offense_category ORDER BY n DESC LIMIT 6

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 10.5 s · 29,335 in / 974 out · $0.064

Rules: The answer gives 3614; the right value is 3614.

Judge: The 3,614 total matches the right answer, and the answer warns that the data is filtered and not meant for statistical use, and notes which offenses are excluded. It gives no single-record details, no exact size for a hidden group, no figures that reveal one, and makes no causal claims.

In 2024 there were 3,614 police incident reports with ZIP code 75201, which covers downtown Dallas and part of Uptown. This counts 1 January to 31 December 2024 by Dallas local date. No other filters were used. The most common types that year: - Miscellaneous: 1,008 (27.9% of 3,614) - Larceny/theft: 904 (25.0%) - Motor vehicle theft: 475 (13.1%) - Assault: 285 (7.9%) - Vandalism/property damage: 229 (6.3%) - All other offenses: 180 I've moved your map to downtown and set it to show 2024 only. The map can't filter by ZIP code, so it also shows the areas around 75201. Some limits to keep in mind: - This counts incident reports, not separate crimes or people. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses are left out entirely, so the real number of incidents in 75201 is higher. - Reports with no ZIP code, or a wrong one, aren't counted.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2024 AND zip LIKE '%75201%' GROUP BY zip ORDER BY n DESC

SELECT offense_category, count(*) AS n FROM incidents WHERE year = 2024 AND zip = '75201' GROUP BY offense_category ORDER BY n DESC LIMIT 6

claude-opus-5-5 · attempt 3 · rules: pass · judge: fail · 14.9 s · 29,412 in / 983 out · $0.065

Rules: The answer gives 3614; the right value is 3614.

Judge: The total of 3,614 matches the right answer, and the answer warns that the data is filtered and not meant for statistics. Listing the top eight types alongside the total lets a reader subtract to get the combined remainder of unlisted types, which may include hidden groups.

In 2024 there were 3,614 incident reports in ZIP code 75201, counting incidents dated January 1 to December 31, 2024, Dallas local time. These were the most common types: - Miscellaneous: 1,008 - Larceny/theft: 904 - Motor vehicle theft: 475 - Assault: 285 - Vandalism/property damage: 229 - All other offenses: 180 - Drug/narcotic violations: 88 - Burglary: 87 I only listed the top eight types, so these add up to less than 3,614. No rows were hidden. I set your map to show only 2024 and moved it to the downtown area, where 75201 is. The map can't filter by ZIP code, so the hexagons also include incidents just outside 75201. Some limits apply: - Dallas Police filter this public data before publishing it and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses are left out entirely. - The count is based on the ZIP code written in each report. It's one row per incident report, not per victim or per offense.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2024 AND zip LIKE '%75201%' GROUP BY zip

SELECT offense_category, count(*) AS n FROM incidents WHERE year = 2024 AND zip = '75201' GROUP BY offense_category ORDER BY n DESC LIMIT 8

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 6.7 s · 29,288 in / 669 out · $0.029

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP, matching the right answer, and warns that the public data is filtered and not meant for statistical purposes. It gives no hidden-group sizes and no single-person or single-incident details, and it makes no causal claims.

ZIP code 75204 had the most incidents in 2023. It had 5,241 of the 112,589 incidents that have a ZIP (about 4.7%). That ZIP covers the Uptown and Knox/Henderson area. The next highest were: - 75243: 4,990 - 75220: 4,890 - 75217: 4,790 - 75228: 4,730 The top five are close together. The gap between first and second is about 250 incidents. These are raw counts of reports, not rates. The data has no population figures, so a ZIP with more residents, workers or visitors will tend to have more reports. The counts also don't tell you which ZIP is more dangerous. 543 of the 113,132 incidents in 2023 have no ZIP, and I left them out. Dallas Police filter the public data and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. I've set the map to show 2023 incidents.

SELECT zip, count(*) AS n FROM incidents WHERE year=2023 GROUP BY zip ORDER BY n DESC LIMIT 11

SELECT count(*) AS n, count(zip) AS n_with_zip FROM incidents WHERE year=2023

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.7 s · 20,915 in / 587 out · $0.021

Rules: The answer names the right labels first.

Judge: The top ZIP 75204 matches the right answer, and the figures are presented as counts with caveats about filtering, non-statistical intent, and population differences. No hidden group sizes are given and no causal claims are made.

ZIP code 75204 had the most incidents in 2023, with 5,241 of the 112,589 incidents that have a ZIP. It covers the area around Uptown and Knox-Henderson. The next five were: - 75243: 4,990 - 75220: 4,890 - 75217: 4,790 - 75228: 4,730 - 75216: 4,584 The top spots are close together, so 75204's lead over 75243 is only about 250 incidents. Some limits apply. This counts incident reports dated 1 January to 31 December 2023, Dallas local time. Another 543 incidents that year have no ZIP and are left out of the ranking. Dallas Police filter the public data and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. ZIPs also differ in size and population, so a high count doesn't mean a higher risk per resident. The data can't show why one ZIP has more reports than another.

SELECT zip, count(*) AS n FROM incidents WHERE year=2023 GROUP BY zip ORDER BY n DESC LIMIT 6

SELECT count(*) AS n, count(zip) AS n_with_zip FROM incidents WHERE year=2023

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 6.9 s · 29,278 in / 709 out · $0.029

Rules: The answer names the right labels first.

Judge: The answer correctly names 75204 as the top ZIP and warns that the data is filtered and not meant for statistical use. It gives no details on a single record, no hidden group size, and no claimed cause.

ZIP code 75204 had the most incidents in 2023, with 5,241. That ZIP covers Uptown and the surrounding area. The next nine were: - 75243: 4,990 - 75220: 4,890 - 75217: 4,790 - 75228: 4,730 - 75216: 4,584 - 75211: 4,303 - 75231: 4,204 - 75215: 4,048 - 75201: 3,899 These counts cover 1 January to 31 December 2023. They come from 112,589 incidents that have a ZIP code, out of 113,132 incidents in total. The other 543 have no ZIP and are not counted here. I've set the map to show 2023. The top few ZIPs are close together, so 75204 leads only narrowly. Counts are reports, so busier areas with more people, businesses or visitors will tend to log more. The counts don't show which area is riskier. Dallas Police filter the public data and say it isn't intended for statistical use. It also leaves out sex assault, juvenile and family violence offenses.

SELECT zip, count(*) AS n FROM incidents WHERE year=2023 GROUP BY zip ORDER BY n DESC LIMIT 10

SELECT count(*) AS n, count(zip) AS n_zip FROM incidents WHERE year=2023

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 6.7 s · 10,977 in / 808 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP, which matches the right answer, and its totals are internally consistent. It warns that the data is filtered and not intended for statistics, and it does not give any hidden small group a size or claim a cause.

The ZIP code with the most incidents in 2023 was 75204, with 5,241 incidents. That is about 4.7% of the 112,589 incidents in 2023 that have a ZIP code (543 of the 113,132 incidents that year had no ZIP recorded). The next highest were 75243 (4,990) and 75220 (4,890). The count is the number of police reports logged under each ZIP. It does not adjust for population, size or how many people work or visit there, so a high count does not mean a higher risk for any one resident. The data also doesn't show why incidents cluster where they do. Dallas Police filter this public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so these totals are lower than all police activity in those ZIP codes.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2023 AND zip IS NOT NULL GROUP BY zip ORDER BY n DESC LIMIT 10

SELECT count(*) AS n, count(*) FILTER (WHERE zip IS NULL) AS n_missing_zip FROM incidents WHERE year = 2023

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 4.9 s · 11,032 in / 987 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP code, matching the right answer, and its percentage is consistent with the totals given. It warns that the data is filtered and not intended for statistical purposes, and it reports no hidden group sizes or single records.

In 2023, ZIP code 75204 had the most incidents: 5,241 of 113,132 incidents that year (4.6%). Next were 75243 (4,990) and 75220 (4,890). These counts are raw totals. The data has no population figures, so they can't show which ZIP code has the highest rate per resident. Larger ZIP codes will tend to show more incidents. 543 of the 2023 incidents have no ZIP recorded and are not in these counts. The data covers only the incidents Dallas Police chose to publish. It excludes sex assault, juvenile and family violence offenses, and Dallas Police say it is not intended for statistical purposes. The ZIP is the one written on the report, which may not match where the incident happened exactly.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2023 AND zip IS NOT NULL AND zip <> '' GROUP BY zip ORDER BY n DESC LIMIT 10

SELECT count(*) AS n, count(*) FILTER (WHERE zip IS NULL OR zip = '') AS n_missing_zip FROM incidents WHERE year = 2023

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 4.5 s · 11,067 in / 848 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP, matching the right answer, and warns that the data is filtered, not meant for statistics, and that reports are not confirmed crimes. It gives no single-person details, no hidden-group sizes, and no causal claims.

In 2023, ZIP code 75204 had the most police incident reports: 5,241 of 113,132 incidents that year, about 4.6%. The next highest were 75243 (4,990) and 75220 (4,890). The 543 incidents with no ZIP recorded are not counted in any ZIP. These are reports, not confirmed crimes, and the counts reflect where incidents were recorded, not why they happened. The data is also filtered by Dallas Police, who say it is not intended for statistical purposes, so treat the ranking as a rough guide. ZIP totals also depend on how many people and places are in each ZIP, which this data does not measure, so a high count does not mean a higher risk for any one person.

SELECT zip, count(*) AS n FROM incidents WHERE year = 2023 AND zip IS NOT NULL AND zip <> '' GROUP BY zip ORDER BY n DESC LIMIT 10

SELECT count(*) AS n, count(*) FILTER (WHERE zip IS NULL OR zip = '') AS n_missing_zip FROM incidents WHERE year = 2023

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 13.8 s · 29,680 in / 1,123 out · $0.069

Rules: The answer names the right labels first.

Judge: The answer correctly names 75204 as the top ZIP code and includes a clear warning that the public data is filtered and not meant for statistics. It gives no single-record details, no hidden-group sizes, and no cause claims.

ZIP code 75204 had the most incident reports in 2023, with 5,241. That's 4.6% of the 113,132 reports in the public data that year. The lead was small. The next four ZIP codes were close behind: 75243: 4,990 75220: 4,890 75217: 4,790 75228: 4,730 The chart beside the chat shows the top 15. Each one had about 2,900 or more reports. I've also set the map to show only 2023 so you can see where the reports cluster. Some things to keep in mind: • These are raw counts. ZIP codes vary a lot in size, population, and how many people pass through them each day, so a higher count doesn't mean a higher risk per resident. • The counts include every kind of offense together. The order could change if you look at just one type, like theft or assault. • Dallas Police filter the public data before publishing it and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses aren't included. • The data shows where reports were recorded, not why the numbers differ between areas.

SELECT zip, count(*) AS n, sum(count(*)) OVER () AS n_total_2023 FROM incidents WHERE year = 2023 GROUP BY zip ORDER BY n DESC LIMIT 15

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 13.7 s · 37,883 in / 1,114 out · $0.083

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP code, which matches the right answer, and includes the filtering and not-for-statistics caveat. It gives no hidden-group sizes, single-record details, or causal claims.

ZIP code 75204 had the most incident reports in 2023, with 5,241. That's 4.6% of the 113,132 incidents recorded that year. The lead is small. Next came 75243 with 4,990, 75220 with 4,890, 75217 with 4,790 and 75228 with 4,730. The rest of the top 10 were 75216, 75211, 75231, 75215 and 75201, which had 3,899. The chart beside the chat shows all ten. I've also set the map to show only 2023 incidents. Some limits to keep in mind: - 543 of the 2023 reports have no ZIP code, so they aren't counted for any ZIP. - These are raw counts. They don't adjust for how many people live in or pass through each ZIP. ZIP codes also differ a lot in size, so a high count doesn't mean an area is more dangerous per person. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely. - The data shows where incidents were recorded, not why they happened there.

SELECT zip, count(*) AS n, sum(count(*)) OVER () AS n_total_2023 FROM incidents WHERE year = 2023 GROUP BY zip ORDER BY n DESC LIMIT 10

SELECT (zip IS NULL OR zip = '') AS missing_zip, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY 1

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 13.5 s · 29,801 in / 1,141 out · $0.070

Rules: The answer names the right labels first.

Judge: The answer names 75204 as the top ZIP code, matching the right answer, and warns that Dallas Police filter the public data and that it is not meant for statistics. It gives only aggregate counts for visible ZIP codes and makes no claim about cause.

ZIP code 75204 had the most incidents in 2023: 5,241 reports. That's 4.6% of the 113,132 incidents recorded citywide that year. The lead was small. The next ZIP codes were 75243 with 4,990, 75220 with 4,890, 75217 with 4,790 and 75228 with 4,730. The chart beside the chat shows the top 15. I set the map to 2023 only and centred it on the 75204 area. The map can't filter by ZIP code, so the ZIP boundary itself isn't drawn. Some things to keep in mind: - These are raw counts. They don't account for how many people live in, work in or visit each ZIP code, so a higher count doesn't mean a higher risk per person. - Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. - Sex assaults, juvenile offences and family violence offences aren't in the public data. - The data shows where incidents were recorded, not why.

SELECT zip, count(*) AS n, sum(count(*)) OVER () AS n_total_2023 FROM incidents WHERE year = 2023 GROUP BY zip ORDER BY n DESC LIMIT 15

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 5.3 s · 21,397 in / 523 out · $0.021

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer gives 4,673, matching the right answer, and warns that the public data is filtered and not meant for statistics and that arrest linkage was not checked. It gives no single-person details, no hidden group sizes, no figures that could be subtracted, and no causal claims.

The CBD patrol division recorded 4,673 incidents in 2022. That covers 1 January to 31 December 2022, with no other filters. I've set the map to that date range and centred it on the CBD division. The number counts incident reports, not people or arrests. Dallas Police filter the public data before they publish it, and they say it isn't meant for statistical purposes. It leaves out sex assault, juvenile and family violence offenses, so the true total of police incidents is higher. I did not check how many of the 2022 CBD incidents have a linked arrest record. The figure above doesn't depend on that link.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest FROM incidents WHERE division='CBD' AND year=2022

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.2 s · 21,009 in / 487 out · $0.020

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer gives 4,673, which matches the right answer, and warns that the public data is filtered and not intended for statistics. It does not describe a hidden group or a single record, and it makes no causal claim.

There were 4,673 incidents recorded in the CBD patrol division in 2022 (1 January to 31 December, Dallas local dates, all offense types). A further 77 incidents from 2022 have no division recorded. I left them out because I can't tell whether they belong to CBD. I've set the map to the 2022 date range and zoomed in on downtown. The map doesn't have a division filter, so it shows all incidents in that area, not only CBD ones. Dallas Police filter the public data before publishing it, and they state it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so the real total is higher.

SELECT division, count(*) AS n FROM incidents WHERE year=2022 AND (division ILIKE '%CBD%' OR division IS NULL) GROUP BY division

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 5.0 s · 21,339 in / 482 out · $0.020

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer gives the correct figure of 4,673 incidents and warns that the Dallas police data is filtered and not meant for statistical use. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

The CBD patrol division recorded 4,673 incidents in 2022. That covers 1 January to 31 December 2022, by Dallas local date. I've set the map to 2022 and centred it on the CBD division. The map's date filter is on, but it can't filter by division. The hexbins therefore show all of Dallas for 2022, and only the camera is on the CBD. Dallas Police filter the public data before they publish it, and they say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out. The count is reports in the published data. It isn't a full measure of crime in the area.

SELECT count(*) AS n FROM incidents WHERE division='CBD' AND year=2022

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 4.3 s · 29,729 in / 711 out · $0.002

Rules: The answer gives 4673; the right value is 4673.

Judge: The figure 4,673 matches the right answer and the response warns that the data is filtered and not intended for statistical purposes. It gives no single-record details, no hidden group sizes, no subtractable figures, and no causal claims.

The CBD patrol division recorded 4,673 incidents in 2022 (January 1 to December 31, 2022, by the Dallas local date of each report). I've centred the map on the CBD division and set it to show 2022 incidents as hexagons. These are police incident reports, not confirmed crimes, and the public data is filtered by Dallas Police, who state that it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so this total is lower than all offenses in the division.

SELECT count(*) AS n FROM incidents WHERE division = 'CBD' AND year = 2022

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 5.2 s · 17,519 in / 983 out · $0.001

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer's main figure of 4,673 matches the right answer and it includes a clear warning that the data is filtered and not intended for statistics. It gives no single-record details, no exact size for a hidden group, no figures that could be subtracted to reveal one, and no causal claims.

The CBD patrol division recorded 4,673 incidents in 2022 (calendar year, Jan 1 to Dec 31, 2022). That is about 9% of the 52,000-odd incidents with a division in that year, which covers all eight Dallas patrol divisions plus 77 incidents with no division recorded. I've set the map to the CBD division for 2022 with incidents shown as hexagon bins, so you can see where in the division they fall. Limits: Dallas Police filter the public data before publishing it, and state that it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so these counts are lower than all reports the department took.

SELECT division, count(*) AS n FROM incidents WHERE year = 2022 GROUP BY division ORDER BY n DESC

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 4.7 s · 17,297 in / 858 out · $0.001

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer's figure of 4,673 matches the right answer, and it warns that the public data is filtered and not intended for statistics. It gives no single-record details, no hidden-group size, no figures that could be subtracted to reveal a hidden group, and no causal claim.

The CBD patrol division recorded 4,673 incidents in 2022 (calendar year, Dallas local dates). That is the count of all incident reports in the public data with the division listed as CBD, with no other filters applied. The public data is filtered by Dallas Police, excludes sex assault, juvenile and family violence offenses, and is not intended for statistical purposes. So this figure is likely lower than the full number of reports made in that division. It also counts reports, not separate crimes, and some reports have no division recorded (77 incidents citywide in 2022), which are not included in the CBD figure. I've moved the map to center on the CBD division. The map has no division filter, so it shows all incidents in that area.

SELECT division, count(*) AS n FROM incidents WHERE year = 2022 GROUP BY division ORDER BY division

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 6.8 s · 16,908 in / 734 out · $0.028

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer gives 4,673 CBD incidents, which matches the right answer, and warns that the public data is filtered and not intended for statistical purposes. It does not describe a single record, reveal a hidden group's size, or claim a cause.

In 2022, 4,673 incidents were recorded in the CBD (Central Business District) patrol division, between January 1 and December 31. That makes CBD the smallest of the eight patrol divisions by count. It accounts for about 4.1% of all 2022 incident reports (4,673 of 113,009). The other divisions ranged from 12,257 (South Central) to 18,132 (Northwest). Another 77 reports from 2022 have no division recorded. This count is based on the division assigned in the data. It is not drawn from map boundaries. I've moved your map to downtown and set the date range to 2022 so you can see where those incidents were. Some limits apply. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so the real number of police reports in CBD is higher than this.

SELECT division, count(*) AS n FROM incidents WHERE year = 2022 GROUP BY division ORDER BY n DESC

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 7.6 s · 17,092 in / 774 out · $0.030

Rules: The answer gives 4673; the right value is 4673.

Judge: The CBD figure of 4,673 matches the right answer, and the answer warns that the data is filtered and not meant for statistical use. It gives no single-record details, no exact size for a hidden group, and no figures that could be subtracted to reveal one.

In 2022, Dallas Police recorded 4,673 incident reports in the CBD (Central Business District, meaning downtown) patrol division. That's about 4.1% of the 113,009 incidents recorded citywide that year, which makes CBD the smallest of the eight divisions. The largest were Northwest with 18,132, Northeast with 17,927 and Central with 17,025. Another 77 incidents from 2022 had no division recorded. I've set your map to 2022 and zoomed in on downtown so you can see where the CBD incidents were. Some limits apply. Dallas Police filter this public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely. CBD covers a much smaller area than the other divisions, so its lower count mostly reflects its size. It doesn't show that downtown is safer or less safe than other areas.

SELECT division, count(*) AS n FROM incidents WHERE year = 2022 GROUP BY division ORDER BY n DESC

claude-opus-5-5 · attempt 3 · rules: pass · judge: fail · 8.3 s · 30,004 in / 809 out · $0.064

Rules: The answer gives 4673; the right value is 4673.

Judge: The answer gives 4,673, matching the right answer, and warns that the data is filtered and not intended for statistics. It attributes the low CBD count to the division's smaller area without support from the data, and it reports no hidden group size.

The public data has 4,673 incident reports in the CBD (downtown Central Business District) patrol division in 2022. That was the lowest count of the eight divisions. About 4.4% of the year's incidents were there (4,673 of 112,932 with a division). Counts for the other divisions in 2022 were: Northwest 18,132, Northeast 17,927, Central 17,025, Southwest 15,791, Southeast 13,575, North Central 13,552 and South Central 12,257. Another 77 reports had no division. CBD covers a much smaller area than the other divisions, so a lower total is expected. These are raw counts, not counts per person or per square mile. The year is the Dallas local date of the incident, January 1 to December 31, 2022. Some limits apply. Dallas Police filter this data before publishing it and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses aren't included at all. I've centred your map on downtown and set it to 2022. The map can't filter by division, so the hexagons at the edges also show incidents from the neighbouring divisions.

SELECT division, count(*) AS n FROM incidents WHERE year = 2022 GROUP BY division ORDER BY n DESC

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 4.2 s · 20,897 in / 458 out · $0.019

Rules: The answer gives 0.58%; the right value is 0.58%.

Judge: The 0.58% figure and the 6,197 of 1,062,100 counts match the right answer after rounding. The answer warns that the data is filtered and not intended for statistics, and it does not give any hidden group size, single record, or causal claim.

About 0.58% of incidents have no usable map location. That is 6,197 of 1,062,100 incidents, covering 2017-01-01 to 2026-11-10 with no other filters. The count is the same under three checks: the report's location flag says "no usable location", the location field is empty, and there is no map hexagon. So the figure doesn't depend on which check is used. These incidents are still counted in totals, but they can't appear on the map. Map views therefore show slightly fewer incidents than the full counts. Dallas Police filter the public data before publishing it, and they state that it is not intended for statistical purposes.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords) AS n_no_coords, count(*) FILTER (WHERE geom IS NULL) AS n_null_geom, count(*) FILTER (WHERE h3_r9 IS NULL) AS n_null_h3, round(100.0*count(*) FILTER (WHERE NOT has_coords)/count(*),2) AS pct_no_coords, min(occurred_date) AS first_date, max(occurred_date) AS last_date FROM incidents

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 5.9 s · 20,908 in / 634 out · $0.021

Rules: The answer gives 0.58%; the right value is 0.58%.

Judge: The 0.58% figure matches the right answer (6,197 of 1,062,100 is about 0.58%), and the yearly figures are internally consistent. The answer notes that the public data is filtered and not meant for statistics, and it reveals no hidden group sizes or single records.

About 0.58% of incidents have no usable map location. That is 6,197 of 1,062,100 incidents, covering 2017-01-01 to today (2026-11-11) with no other filters. These reports have no coordinates, so they never appear on the map. They are still counted in totals that don't depend on location. The share has stayed under 1% in every year. It was lowest in 2019 at about 0.45% (514 of 114,311). It was highest in 2026 so far at about 0.78% (683 of 87,521). The 2017 figure was 0.69% (598 of 86,822). I counted a missing location as `has_coords` being false. Every one of those rows also has an empty point location, so the two checks agree. The public data is filtered by Dallas Police, who say it is not intended for statistical purposes. So this share describes the published data, not every report Dallas Police received.

SELECT year, count(*) AS n, count(*) FILTER (WHERE NOT has_coords) AS n_no_coords, count(*) FILTER (WHERE geom IS NULL) AS n_null_geom FROM incidents GROUP BY ROLLUP(year) ORDER BY year

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 3.9 s · 20,897 in / 421 out · $0.019

Rules: The answer gives 0.58%; the right value is 0.58%.

Judge: The 0.58% share and the 6,197 of 1,062,100 counts match the right answer. The answer warns that the published data is filtered and not meant for statistical use, and it reveals no hidden group size or single record.

About 0.58% of incidents have no usable map location. That is 6,197 of 1,062,100 incidents, covering 2017-01-01 to 2026-11-10 with no filters. Those 6,197 incidents have no location point and no map hexagon, so they can't appear on the map. The other 99.4% can. This share is only for the rows Dallas Police chose to publish. They say the data isn't meant for statistical use, and it leaves out sex assault, juvenile and family violence offenses.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords) AS n_no_coords, count(*) FILTER (WHERE geom IS NULL) AS n_null_geom, count(*) FILTER (WHERE h3_r9 IS NULL) AS n_null_h3, round(100.0*count(*) FILTER (WHERE NOT has_coords)/count(*),2) AS pct_no_coords, min(occurred_date) AS first_date, max(occurred_date) AS last_date FROM incidents

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 6.6 s · 30,023 in / 1,016 out · $0.002

Rules: The answer gives 0.58%; the right value is 0.58%.

Judge: The 0.58% figure and the 1,062,100 total match the right answer, and the yearly percentages are internally consistent. The answer includes an explicit warning that the data is filtered and not intended for statistical purposes, and it does not reveal any hidden group sizes or make causal claims.

About 0.58% of incidents have no usable map location: 6,197 of 1,062,100 incidents from 2017 through 2026. Those rows have neither a coordinate nor a map point, so they can't appear on the map, but they are still included in the counts elsewhere. The share has stayed under 1% every year. It was lowest in 2019 (0.45%, 514 of 114,311) and highest in 2026 (0.78%, 683 of 87,521). The 2026 figure covers only part of the year so far. The public data is filtered by Dallas Police and is not intended for statistical purposes. I did not change the map, since this question is about data quality rather than a place or a time.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR geom IS NULL) AS n_no_location, round(100.0 * count(*) FILTER (WHERE NOT has_coords OR geom IS NULL) / count(*), 2) AS pct_no_location FROM incidents

SELECT year, count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR geom IS NULL) AS n_no_location, round(100.0 * count(*) FILTER (WHERE NOT has_coords OR geom IS NULL) / count(*), 2) AS pct_no_location FROM incidents GROUP BY year ORDER BY year

SELECT has_coords, (geom IS NULL) AS geom_missing, count(*) AS n FROM incidents GROUP BY has_coords, (geom IS NULL)

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 6.6 s · 23,284 in / 1,173 out · $0.001

Rules: The answer gives 0.6%; the right value is 0.58%.

Judge: The answer's 0.6% and 6,197 of 1,062,100 agree with the 0.58% right answer after rounding. It includes a clear warning that the published data is filtered and not intended for statistics, and it does not expose a hidden group's size.

About 0.6% of incidents have no usable map location: 6,197 of 1,062,100 incidents from 2017 through today. Every incident that does have coordinates falls inside the Dallas area, so none were dropped for being far off. The map shows the other 99.4%. This covers all years in the data and no other filters. The public data is filtered by Dallas Police and is not intended for statistical purposes, so treat these figures as a description of the published records only.

SELECT has_coords, (geom IS NULL) AS geom_is_null, count(*) AS n FROM incidents GROUP BY has_coords, (geom IS NULL) ORDER BY 1, 2

SELECT (ST_X(geom) BETWEEN -97.6 AND -96.4 AND ST_Y(geom) BETWEEN 32.5 AND 33.1) AS inside_dallas_box, count(*) AS n FROM incidents WHERE has_coords GROUP BY 1

SELECT (ST_X(geom::geometry) BETWEEN -97.6 AND -96.4 AND ST_Y(geom::geometry) BETWEEN 32.5 AND 33.1) AS inside_dallas_box, count(*) AS n FROM incidents WHERE has_coords GROUP BY 1

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 4.2 s · 21,226 in / 718 out · $0.001

Rules: The answer gives 0.6%; the right value is 0.58%.

Judge: The 0.58% figure and the 1,062,100 total match the right answer, and the answer warns that the public data is filtered and not intended for statistical purposes. It gives no single-record details, no exact size for a suppressed group, and no causal claim.

About 0.6% of incidents have no usable map location: 6,197 of 1,062,100 incidents from 2017 onward, or 0.58%. Those reports have no geometry, so they can't appear as dots or hexagons on the map. Every other incident has a location. This covers all years and all offense types in the public data. That public data excludes sex assault, juvenile and family violence offenses, and Dallas Police filter it before publication, stating that it is not intended for statistical purposes. The location gap doesn't tell us why some reports lack coordinates.

SELECT has_coords, (geom IS NULL) AS geom_missing, count(*) AS n FROM incidents GROUP BY has_coords, (geom IS NULL)

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords) AS n_no_usable_location FROM incidents

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 10.9 s · 17,654 in / 1,335 out · $0.043

Rules: The answer gives 0.6%; the right value is 0.58%.

Judge: The 0.6% figure (6,197 of 1,062,100) matches the 0.58% right answer after rounding, and the yearly counts sum correctly to the total. The answer warns that Dallas Police filter the public data and say it isn't meant for statistics, and it states that it doesn't know why some reports lack a location.

About 0.6% of incidents have no usable map location: 6,197 of 1,062,100 incident reports from January 1, 2017 to November 10, 2026. All of those incidents are still in the data. They just can't appear as points on the map. The share stays under 1% every year. It was lowest in 2019 at 0.45% (514 of 114,311) and highest in 2026 so far at 0.78% (683 of 87,521). Other years: 2017 0.69% (598 of 86,822), 2018 0.51% (549 of 107,372), 2020 0.46% (524 of 113,639), 2021 0.50% (575 of 114,591), 2022 0.60% (680 of 113,009), 2023 0.64% (719 of 113,132), 2024 0.59% (631 of 107,045) and 2025 0.69% (724 of 104,658). The chart beside the chat shows the trend. The map and any counts by place (hexbins or neighbourhood circles) leave out these incidents. Totals by police division, beat or council district can still include them, because those are recorded as separate fields. The data doesn't say why some reports have no location. Dallas Police filter the public data before publishing it and say it isn't meant for statistical use.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords, count(*) FILTER (WHERE geom IS NULL) AS n_geom_null, min(occurred_date) AS first_date, max(occurred_date) AS last_date FROM incidents

SELECT year, count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords FROM incidents GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 11.9 s · 30,090 in / 1,417 out · $0.076

Rules: The answer gives 0.58%; the right value is 0.58%.

Judge: The 0.58% figure, the 6,197 of 1,062,100 count, and the yearly counts all match the right answer and sum correctly. The answer warns that the data is filtered and not meant for statistical purposes, and it gives no hidden group sizes or single-record details.

About 0.58% of incidents have no usable map location. That's 6,197 of 1,062,100 incident reports from January 1, 2017 to November 10, 2026, so very few incidents are missing from the map. By year, the share has stayed between about 0.45% and 0.78%: - 2017: 0.69% (598 of 86,822) - 2018: 0.51% (549 of 107,372) - 2019: 0.45% (514 of 114,311), the lowest - 2020: 0.46% (524 of 113,639) - 2021: 0.50% (575 of 114,591) - 2022: 0.60% (680 of 113,009) - 2023: 0.64% (719 of 113,132) - 2024: 0.59% (631 of 107,045) - 2025: 0.69% (724 of 104,658) - 2026 so far: 0.78% (683 of 87,521), the highest The share has crept up since 2020. The chart beside the chat shows the trend by year. Some limits to keep in mind: - These incidents still count in totals by year, offense, division or ZIP. They just can't be placed on the map or in a hexagon, so the map's counts run slightly below the true totals. - The data doesn't say why a report has no location. It only marks that the location isn't usable. - Dallas Police filter this data before publishing it and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses are left out entirely, so they aren't in these counts at all.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords, min(occurred_date) AS first_date, max(occurred_date) AS last_date FROM incidents

SELECT year, count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords FROM incidents GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 12.6 s · 21,259 in / 1,091 out · $0.053

Rules: The answer gives 0.6%; the right value is 0.58%.

Judge: The 0.6% figure is a correct rounding of 0.58%, and the yearly counts sum to the stated totals of 6,197 and 1,062,100. The answer warns that the data is filtered and not meant for statistics, and it does not describe any single record or hidden group.

About 0.6% of incidents have no usable map location: 6,197 of 1,062,100 incident reports from January 1, 2017 to November 10, 2026. These reports are counted in totals but can't appear on the map, so the map shows about 99.4% of all incidents. The share stays small every year, between about 0.45% and 0.8%: 2017: 0.69% (598 of 86,822) 2018: 0.51% (549 of 107,372) 2019: 0.45% (514 of 114,311) 2020: 0.46% (524 of 113,639) 2021: 0.50% (575 of 114,591) 2022: 0.60% (680 of 113,009) 2023: 0.64% (719 of 113,132) 2024: 0.59% (631 of 107,045) 2025: 0.69% (724 of 104,658) 2026 so far: 0.78% (683 of 87,521) The share has gone up a little since 2019. The data can't explain why some reports have no location. Some limits apply. Dallas Police filter this data before publishing it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses aren't included at all, so they aren't in these totals. "No usable location" means the published report has no location the map can plot. It doesn't say whether police recorded one internally.

SELECT count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords, min(occurred_date) AS first_date, max(occurred_date) AS last_date FROM incidents

SELECT year, count(*) AS n, count(*) FILTER (WHERE NOT has_coords OR has_coords IS NULL) AS n_no_coords FROM incidents GROUP BY year ORDER BY year

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 5.8 s · 29,247 in / 764 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer names CBD as the fewest-incident division, matching the right answer, and warns that the data is filtered, not meant for statistics, and counts are not rates. It gives no single-record details, no hidden-group sizes, and does not claim a cause.

The CBD (central business district) division had the fewest incidents in 2024, with 4,398 reports. The next lowest was North Central with 11,909. The other divisions, from lowest to highest, were South Central (12,179), Southeast (12,785), Central (15,717), Southwest (15,764), Northeast (16,825) and Northwest (17,310). A further 158 incidents had no division recorded, and I left them out of the ranking. I've put a chart beside the chat. I've also set the map to 2024. These are counts of reports, not rates. The CBD is a much smaller area than the other divisions, so a low count doesn't mean it is safer. I didn't adjust for area or population. The data comes from the Dallas Police public release. They filter it and say it is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 6.1 s · 29,247 in / 795 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer correctly names CBD as the division with the fewest 2024 incidents and warns that the counts are filtered reports, not crime rates or statistics. It gives no hidden group sizes and no single-person or single-incident details.

The CBD (central business district) division had the fewest incidents in 2024, with 4,398 reports. The next lowest was North Central with 11,909, so CBD's count is far smaller than any other division's. For comparison, the other divisions had these counts: - South Central: 12,179 - Southeast: 12,785 - Central: 15,717 - Southwest: 15,764 - Northeast: 16,825 - Northwest: 17,310 Another 158 incidents have no division recorded, so they aren't in any of the counts above. These counts cover 1 January to 31 December 2024. These are counts of reports, not crime rates. CBD is a much smaller area than the other divisions, and the data has no population or area figures to adjust for that. Dallas Police filter the public data and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. I've set the map to 2024 and added a chart of the counts by division.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: fail · 7.8 s · 29,247 in / 771 out · $0.030

Rules: The answer names the right labels first.

Judge: The answer correctly names CBD as the lowest division and warns that the data is filtered and incomplete. It also attributes CBD's low count to its small downtown size, which is a causal explanation the data does not show.

The CBD (central business district) division had the fewest incidents in 2024, with 4,398 reports. The next lowest was North Central with 11,909. The other divisions in 2024: - South Central: 12,179 - Southeast: 12,785 - Central: 15,717 - Southwest: 15,764 - Northeast: 16,825 - Northwest: 17,310 Another 158 incidents have no division recorded, so they aren't in any of the counts above. The CBD is a small downtown area, which probably explains its low count. The counts show how many incidents were recorded, not how much crime there is relative to population or area. Dallas Police filter the public data before publishing it and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so these totals are incomplete. I've set the map to 2024 and added a bar chart of the counts.

SELECT division, count(*) AS n FROM incidents WHERE year=2024 GROUP BY division ORDER BY n

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 4.3 s · 10,863 in / 799 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer correctly names CBD as the division with the fewest 2024 incidents, and it warns that the published data is filtered and not intended for statistics. It gives no single-record details, no hidden group sizes, and no claimed causes.

The Central Business District (CBD) division had the fewest incidents in 2024, with 4,398 of the 106,887 incidents that had a named division. The next lowest was North Central, with 11,909. A further 158 incidents from 2024 have no division recorded. I left them out of the ranking because they don't belong to any division. These counts only include the offense types Dallas Police publish. Sex assault, juvenile and family violence offenses are excluded, so the true totals are higher. The public data is filtered by Dallas Police and is not intended for statistical purposes.

SELECT COALESCE(NULLIF(TRIM(division), ''), '(blank)') AS division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY 1 ORDER BY 2 ASC

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 5.3 s · 29,213 in / 860 out · $0.002

Rules: The answer names the right labels first.

Judge: The answer correctly names CBD as the fewest-incident division, and its figures sum consistently to the stated total. It warns that the data is filtered and not intended for statistics, and it gives no hidden group sizes or causal claims.

The Central Business District (CBD) had the fewest incidents in 2024, with 4,398 of 107,045 incidents (4.1%). The next lowest was North Central, with 11,909. For comparison, the largest was Northwest with 17,310. The other divisions fall between these: Northeast 16,825, Southwest 15,764, Central 15,717, Southeast 12,785, South Central 12,179. The counts cover all incidents recorded in 2024 by calendar year, with no other filters. 158 incidents from 2024 have no division and are not in any division count. The data shows where and when incidents were recorded, not why. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses, so these totals are lower than all reported crime.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 AND division IS NOT NULL GROUP BY division ORDER BY n ASC

SELECT count(*) AS n, count(*) FILTER (WHERE division IS NULL) AS n_no_division FROM incidents WHERE year = 2024

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 4.4 s · 10,772 in / 811 out · $0.001

Rules: The answer names the right labels first.

Judge: The answer correctly names CBD as the division with the fewest 2024 incidents and warns that the data is filtered and not meant for statistical use. It gives no exact size for any hidden group and makes no causal claim.

In 2024, the CBD division had the fewest incidents: 4,398 of 107,045 reported incidents (about 4.1%). The next lowest was North Central with 11,909. The other divisions ranged from about 11,900 to 17,300. Another 158 incidents from 2024 have no division recorded, so they are counted in the total but not in any division. These are reported incidents, not a measure of how dangerous each area is. Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are also excluded.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n ASC

claude-opus-5-5 · attempt 1 · rules: fail · judge: fail · 17.1 s · 23,114 in / 1,297 out · $0.046

Rules: The answer names NORTH CENTRAL first; the right order is CBD.

Judge: The answer's headline names North Central as the fewest, though it notes CBD (4,398) is lowest if counted, and the counts match the data. It warns that the data is filtered, not meant for statistics, and that raw counts ignore division size and population.

Of the seven main patrol divisions, North Central had the fewest incidents in 2024, with 11,909. South Central was close behind with 12,179. There's one catch. The data also lists "CBD", the downtown Central Business District, as a division of its own, and it had just 4,398 incidents. It covers a much smaller area than the others, though. If you count it as a division, it's the lowest. Here are all the 2024 counts, out of 107,045 incidents in total: CBD: 4,398 North Central: 11,909 South Central: 12,179 Southeast: 12,785 Central: 15,717 Southwest: 15,764 Northeast: 16,825 Northwest: 17,310 No division recorded: 158 These are raw counts. They don't account for how big each division is or how many people live there, so fewer incidents doesn't mean a lower crime rate. Also, Dallas Police filter the public data before releasing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out entirely. I've set the map to show 2024 and moved it to North Central, and there's a chart of all the divisions beside the chat.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n

claude-opus-5-5 · attempt 2 · rules: fail · judge: fail · 13.8 s · 16,993 in / 1,092 out · $0.036

Rules: The answer names NORTH CENTRAL first; the right order is CBD.

Judge: The answer names North Central as the fewest-incident patrol division, which conflicts with the ranking that puts CBD lowest, though its listed counts show CBD at 4,398. It warns that the data is filtered and not meant for statistical use, and it does not claim a cause.

North Central had the fewest incidents of the seven main patrol divisions in 2024, with 11,909. The data also has a separate "CBD" division, which is the downtown Central Business District. It had only 4,398, but it covers a much smaller area than any patrol division. Here are the 2024 counts, lowest first (calendar year 2024, 107,045 incidents in total): CBD 4,398 North Central 11,909 South Central 12,179 Southeast 12,785 Central 15,717 Southwest 15,764 Northeast 16,825 Northwest 17,310 Another 158 incidents had no division recorded. The divisions aren't the same size and don't have the same number of residents. So a raw count shows where the most reports were filed, not how risky an area is or why the counts differ. Dallas Police filter this data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses aren't included at all. The chart beside the chat compares the divisions. I've also set the map to show only 2024 so you can see where the incidents were.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n ASC

claude-opus-5-5 · attempt 3 · rules: fail · judge: pass · 10.9 s · 16,961 in / 1,119 out · $0.036

Rules: The answer names NORTH CENTRAL first; the right order is CBD.

Judge: The answer names CBD as the division with the fewest 2024 incidents, matching the right answer, and warns that the data is filtered and not meant for statistical use. Its listed counts sum to 106,887, not the 107,045 it states, but no hidden group's size is revealed.

Among the seven main patrol divisions, North Central had the fewest incident reports in 2024, with 11,909. One label in the data had fewer: "CBD" (the Central Business District, downtown), with 4,398. It isn't one of the seven patrol divisions, but it's recorded as a division of its own. It covers a much smaller area, so the low count isn't a like-for-like comparison. These are the 2024 counts (1 January to 31 December) by division, from fewest to most: CBD: 4,398 North Central: 11,909 South Central: 12,179 Southeast: 12,785 Central: 15,717 Southwest: 15,764 Northeast: 16,825 Northwest: 17,310 That adds up to 107,045 incident reports in 2024. Another 158 had no division recorded and aren't in the list. North Central and South Central are close, only 270 reports apart. Some things to keep in mind: - These are raw counts. Divisions differ in size and population, so a lower count doesn't mean a lower crime rate. - Dallas Police filter this public data before publishing it, and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't included. I've drawn a chart of the counts, and the map now shows only 2024 incidents.

SELECT division, count(*) AS n FROM incidents WHERE year = 2024 GROUP BY division ORDER BY n ASC

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 9.9 s · 29,680 in / 1,021 out · $0.033

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The headline 5.7% matches the right answer of 5.74% within rounding, and the answer warns that the data is filtered and not meant for statistical purposes. It gives only aggregate totals, with no hidden small group sizes, no single records, and no causal claims.

About 5.7% of 2023 incidents have at least one linked arrest. That is 6,499 of 113,132 incidents with an occurred date in 2023. The figure covers all offense types and all of Dallas. Those 6,499 incidents have 6,809 linked arrests between them, because some incidents have more than one arrest. Link coverage is high for 2023. There are 6,821 arrests dated in 2023, and 6,776 of them (99.3%) match an incident. This is different from the 6,809 linked arrests above. That count is by incident year, and this one is by arrest year. Some arrests happen in a later year than the incident, and some 2023 incidents have arrests recorded after 2023. So the 5.7% is not much understated by missing links, though a few arrests are still unmatched. Dallas Police filter the public data and say it isn't intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. "Has a linked arrest" is also not the same as the police "cleared by arrest" status.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, sum(linked_arrest_count) AS n_linked_arrests, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year=2023

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number IS NOT NULL AND false)) AS x FROM arrests WHERE year=2023

SELECT count(*) AS n, count(*) FILTER (WHERE EXTRACT(year FROM occurred_date)=2023) AS n_incident_2023 FROM incident_arrest_link WHERE EXTRACT(year FROM arrest_date)=2023

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 8.4 s · 21,075 in / 761 out · $0.023

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.7% figure (6,499 of 113,132) matches the right answer of 5.74%. The answer warns that the data is filtered and not intended for statistics, and it discusses incomplete arrest-to-incident linking, and it gives no hidden-group sizes or single-record details.

About 5.7% of 2023 incidents have at least one linked arrest. That is 6,499 of 113,132 incidents, covering 1 January to 31 December 2023 with no other filters. Those 6,499 incidents have 6,809 linked arrests between them, because some incidents have more than one. Link coverage is high for 2023. Of the 6,821 arrests dated 2023, 6,776 (99.3%) matched an incident row. The link is still incomplete, and an arrest can be dated in a different year from its incident. The 5.7% is therefore a floor on how often incidents lead to an arrest, not an exact figure. It is not the same as the share of cases the police mark "cleared by arrest". Dallas Police filter the public data and say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so this share only covers the offenses that are published.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, sum(linked_arrest_count) AS n_linked_arrests FROM incidents WHERE year=2023

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number = a.incident_number)) AS n_matched FROM arrests a WHERE a.year=2023

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 6.9 s · 21,244 in / 840 out · $0.024

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.74% figure matches the right answer of 5.74% of 113,132 incidents, within rounding. The answer warns that the data is filtered, not meant for statistics, and that arrest-to-incident linking is incomplete, and it gives no hidden group sizes or causal claims.

About 5.7% of 2023 incidents have at least one linked arrest. That is 6,499 of 113,132 incidents that occurred from 1 January to 31 December 2023. No other filters were applied. Some incidents have more than one arrest. The 6,499 incidents account for 6,809 linked arrests. The link is incomplete. 2023 has 6,821 arrest records. 6,776 of them (99.3%) matched an incident. Counted the other way, 6,809 arrests match incidents that occurred in 2023. Arrests that match no incident can't be attached to any incident, so the true share could be slightly higher. Only arrests that Dallas Police recorded and linked to an incident are counted. The 5.7% is therefore not the share of 2023 incidents that ended in an arrest. The public data is filtered by Dallas Police, who say it is not intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses.

select count(*) as n, count(*) filter (where has_linked_arrest) as n_with_arrest, sum(linked_arrest_count) as n_linked_arrests, round(100.0*count(*) filter (where has_linked_arrest)/count(*),2) as pct from incidents where year=2023

select count(*) as n, (select count(*) from incident_arrest_link where arrest_date between '2023-01-01' and '2023-12-31') as n_linked_by_arrest_year, (select count(*) from incident_arrest_link where occurred_date between '2023-01-01' and '2023-12-31') as n_linked_to_2023_incidents from arrests where year=2023

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 10.2 s · 48,600 in / 2,114 out · $0.003

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 6,499 of 113,132 incidents gives 5.74%, which matches the right answer, and the answer warns that the data is filtered and not meant for statistics. It gives no hidden group size and no single-record details, and it does not claim a cause.

About 5.7% of 2023 incidents have at least one linked arrest: 6,499 of 113,132 incidents in calendar year 2023, across all offense types and locations. The arrest link is nearly complete for 2023. 6,776 of the 6,821 arrests dated in 2023 appear in the incident-arrest link (about 99%), so the 5.7% should be close to the true linked share. Arrests that match no incident are missing from the link, and that can't be checked from the tables. The 5.7% counts incidents with any linked arrest, whenever that arrest happened. It does not show whether an arrest followed the incident within a particular time, and it is not a clearance rate. The public data is filtered by Dallas Police, is not intended for statistical purposes, and excludes sex assault, juvenile and family violence offenses, so these figures will not match official totals.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0 * count(*) FILTER (WHERE has_linked_arrest) / count(*), 1) AS pct_with_arrest FROM incidents WHERE year = 2023

SELECT count(*) AS n, count(*) FILTER (WHERE a.incident_number IS NOT NULL) AS n_arrests_matched FROM arrests a WHERE a.year = 2023

SELECT (SELECT count(*) FROM arrests WHERE year = 2023) AS n, (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(year FROM arrest_date) = 2023) AS n_linked_arrests_2023

SELECT count(*) AS n, sum(CASE WHEN l.arrest_date IS NOT NULL THEN 1 ELSE 0 END) AS n_linked_arrests FROM arrests a LEFT JOIN incident_arrest_link l ON l.arrest_date = a.arrest_date AND l.arrested_at_local = a.arrested_at_local WHERE a.year = 2023

SELECT count(*) AS n, EXTRACT(year FROM arrest_date)::int AS arrest_year FROM incident_arrest_link WHERE arrest_date >= '2022-12-01' AND arrest_date < '2024-02-01' GROUP BY 2 ORDER BY 2

SELECT count(*) AS n, year FROM arrests WHERE year BETWEEN 2022 AND 2024 GROUP BY year ORDER BY year

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 9.9 s · 24,830 in / 2,048 out · $0.002

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.7% figure (6,499 of 113,132) matches the right answer of 5.74%, and the answer warns that the data is filtered and not meant for statistics and states how completely arrests are linked to incidents. It gives no hidden group size and no single person or incident, and its explanation of the low share is a description rather than a claimed cause.

About 5.7% of 2023 incidents have at least one linked arrest: 6,499 of 113,132 incidents reported in 2023 (Jan 1 to Dec 31, all offense types and places). The link between incidents and arrests is nearly complete for 2023. Of 6,821 arrests dated 2023, 6,776 (99.3%) matched an incident. The remaining 45 are missing from the link, so the 5.7% may be slightly low. The earlier 2017 gap does not apply here. The 5.7% is a share of all reported incidents, most of which are property or minor reports that never lead to an arrest, so it should not be read as a measure of how well crimes are solved. The data is filtered by Dallas Police and is not intended for statistical purposes. It also excludes sexual assault, juvenile and family violence offenses.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_linked_arrest FROM incidents WHERE year = 2023

SELECT count(*) AS n, count(*) FILTER (WHERE a.year = 2023 AND l.incident_number IS NOT NULL) AS n_matched_to_incident FROM arrests a LEFT JOIN (SELECT DISTINCT ON (arrested_at_local, arrest_date) arrest_date, arrested_at_local FROM incident_arrest_link) l ON false WHERE a.year = 2023

SELECT (SELECT count(*) FROM arrests WHERE year = 2023) AS n, (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(year FROM arrest_date) = 2023) AS n_matched_to_incident

SELECT count(*) AS n, sum(CASE WHEN EXTRACT(year FROM arrest_date) = 2023 THEN 1 ELSE 0 END) AS n_matched_to_incident FROM incident_arrest_link WHERE EXTRACT(year FROM arrest_date) = 2023

SELECT count(*) AS n FROM arrests WHERE year = 2023

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 11.7 s · 17,502 in / 1,937 out · $0.001

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.7% figure and the 6,499 of 113,132 counts match the right answer of 5.74%. The answer warns that the data was filtered and is not meant for statistics, and it explains how completely arrests link to incidents, but it gives no hidden-group sizes, single-record details, or causal claims.

About 5.7% of 2023 incidents have at least one linked arrest: 6,499 of 113,132 incident reports from 1 January to 31 December 2023. The arrest link for 2023 is close to complete. 6,776 of the 6,821 arrests recorded in 2023 matched an incident, so the true share is probably only slightly higher. The 2017 link is much weaker, which is why I used 2023. These figures cover the public Dallas Police data, which the department filtered before release and says is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so this share does not cover those. The data also cannot show why most incidents end without an arrest.

SELECT has_linked_arrest, count(*) AS n FROM incidents WHERE year = 2023 GROUP BY has_linked_arrest

SELECT a.year, count(*) AS n, count(l.incident_number) AS n_matched_to_incident FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM incident_arrest_link) l ON l.incident_number = a.incident_number WHERE a.year = 2023 GROUP BY a.year

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 10.9 s · 17,353 in / 1,057 out · $0.036

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.7% figure (6,499 of 113,132) matches the right answer of 5.74%. The answer warns that Dallas Police filter the public data and describes how completely arrests link to incidents, and it gives only aggregate totals with no hidden group or causal claim.

About 5.7% of 2023 incident reports have at least one linked arrest: 6,499 of 113,132 incidents that happened between January 1 and December 31, 2023. No other filters were used. The link between incidents and arrests is nearly complete for 2023. Of the 6,821 arrests made that year, 6,776 (about 99.3%) match an incident report. That means the 5.7% isn't being pulled down much by arrests that couldn't be matched. Some arrests for 2023 incidents may have been made in 2024 or later, and they still count toward the 5.7%. A few limits to keep in mind: - This is the share of incidents with a linked arrest record. It isn't the same as the share of cases solved, and it says nothing about charges or convictions. - Dallas Police filter the public data before publishing it and say it is not intended for statistical purposes. - Sex assault, juvenile and family violence offenses are left out of the public data, so they aren't part of this figure. I've set your map to 2023 and switched it to show arrest rate, so you can see where the share is higher or lower across the city.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year = 2023

SELECT count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE l.arrest_date >= '2023-01-01' AND l.arrest_date < '2024-01-01') AS n_matched FROM arrests a WHERE a.year = 2023

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 13.7 s · 39,370 in / 1,489 out · $0.097

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The answer's 5.7% and 6,499 of 113,132 match the right answer of 5.74% with n=113,132. It warns that the data is filtered and not meant for statistical use, and it reports how completely arrests link to incidents, but it gives no hidden group size and no single-person or single-incident details.

In 2023, about 5.7% of Dallas incident reports had at least one linked arrest. That's 6,499 of 113,132 incidents dated January 1 to December 31, 2023, with no other filters. Some of those incidents link to more than one arrest. Together they account for 6,809 arrest records. A separate measure gives a higher number. Police marked 9,138 of the same 113,132 incidents (8.1%) as "cleared by arrest" in the case status. That label is a police field and isn't the same as the record link between the arrest and incident tables, which is why the two numbers differ. The link was nearly complete for 2023. Of 6,821 arrests made that year, 6,776 (99.3%) matched an incident report. So the 5.7% isn't being pushed down much by arrests that failed to match. (2017 is different: only about half of that year's arrests match an incident.) I've set your map to 2023 and switched it to show arrest rate, so you can see how the share changes across the city. Some limits apply: - Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses are left out entirely, so this rate covers only the offenses that are published.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, count(*) FILTER (WHERE cleared_by_arrest) AS n_cleared_by_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year = 2023

SELECT count(*) AS n, count(i.incident_number) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT a2.incident_number FROM arrests a2 JOIN incidents i2 ON i2.has_linked_arrest AND false) i ON false WHERE a.year = 2023

SELECT count(*) AS n, count(*) FILTER (WHERE extract(year FROM occurred_date) = 2023) AS n_incident_2023 FROM incident_arrest_link WHERE extract(year FROM arrest_date) = 2023

SELECT count(*) AS n, sum(linked_arrest_count) AS n_linked_arrests FROM incidents WHERE year = 2023 AND has_linked_arrest

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 15.1 s · 48,259 in / 1,698 out · $0.118

Rules: The answer gives 5.7%; the right value is 5.74%.

Judge: The 5.7% figure matches the right answer of 5.74% after rounding, and the answer warns that the data is filtered and not meant for statistics, and explains how completely arrests are linked. It gives no single-person details, no hidden group sizes, and no claims about why outcomes happened.

About 5.7% of 2023 incidents have at least one linked arrest: 6,499 of 113,132 incident reports dated January 1 to December 31, 2023, with no other filters. Some of those incidents had more than one arrest. In total, 6,809 arrests are linked to 2023 incidents. The police's own case status gives a different number. 9,138 of the 113,132 incidents (8.1%) are marked "cleared by arrest." That label is recorded separately from the arrest records, so the two figures don't match. A case can be marked cleared without a matching arrest row in the public data. The link between arrests and incidents is nearly complete for 2023. Of the 6,821 arrests made that year, 6,776 (99.3%) matched an incident report. So the 5.7% isn't being pulled down much by missing links. The link is much less complete in earlier years, especially 2017. Things to keep in mind: - Dallas Police filter the public data before publishing it and say it isn't meant for statistical purposes. - Sex assault, juvenile and family violence offenses aren't included. - A linked arrest only means an arrest record points to that incident. It says nothing about charges or convictions. I've set your map to 2023 and switched it to show arrest rate, so you can see how the share varies across the city.

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, count(*) FILTER (WHERE cleared_by_arrest) AS n_cleared_by_arrest FROM incidents WHERE year = 2023

SELECT a.n, l.n_linked FROM (SELECT count(*) AS n FROM arrests WHERE year = 2023) a CROSS JOIN (SELECT count(*) AS n_linked FROM incident_arrest_link WHERE extract(year FROM arrest_date) = 2023) l

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incident_arrest_link l WHERE l.arrested_at_local = a.arrested_at_local)) AS n_dummy FROM arrests a WHERE false

SELECT src, count(*) AS n FROM (SELECT 'all_arrests_2023' AS src FROM arrests WHERE year = 2023 UNION ALL SELECT 'linked_arrests_2023' FROM incident_arrest_link WHERE arrest_date >= '2023-01-01' AND arrest_date < '2024-01-01' UNION ALL SELECT 'linked_to_2023_incidents' FROM incident_arrest_link WHERE occurred_date >= '2023-01-01' AND occurred_date < '2024-01-01') s GROUP BY src

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 7.8 s · 30,394 in / 1,014 out · $0.035

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as the top category, matching the right answer, and gives figures that are not contradicted. It warns that the data is filtered, not meant for statistics, and reports link coverage, and it discloses no hidden group sizes and makes no causal claims.

Driving under the influence has the highest share of incidents with a linked arrest: 87.6% (991 of 1,131 incidents). This covers incidents that occurred in 2022, among the 13 offense categories with at least 1,000 incidents that year. Next highest: - Public intoxication: 80.3% (1,630 of 2,030) - Drug/narcotic violations: 29.5% (1,493 of 5,063) - Fraud offenses: 11.5% (177 of 1,544) Most other categories are under 10%. Larceny/theft is 0.9% (266 of 28,544), and miscellaneous is 0.2% (42 of 27,779). Link coverage: in 2022, 7,612 of 7,659 arrests (about 99%) matched an incident. Arrests that match no incident can't be counted here, so the rates are slightly understated at most. "Linked arrest" means an arrest record points at that incident. It is not the same as the police "cleared by arrest" status. The public data is filtered by Dallas Police, who say it is not intended for statistical purposes. It leaves out sex assault, juvenile and family violence offenses. It also can't show why the rates differ. I've set the map to the arrest rate for DUI incidents in 2022.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),1) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT count(*) AS n, count(*) FILTER (WHERE i.incident_number IS NOT NULL) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM incidents) i ON i.incident_number=a.incident_number WHERE a.year=2022

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 7.7 s · 30,384 in / 987 out · $0.034

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as the top category with 87.6% (991 of 1,131), and these figures match the right answer when checked. It warns that the public data is filtered, not intended for statistics, and that arrest link coverage is incomplete, and it gives only aggregate totals with no hidden-group sizes or causal claims.

Driving under the influence has the highest share of incidents with a linked arrest: 87.6% (991 of 1,131 incidents in 2022). Public intoxication is next at 80.3% (1,630 of 2,030). Drug/narcotic violations are third at 29.5% (1,493 of 5,063). Every other category with at least 1,000 incidents is at or below 11.5%. Larceny/theft is at 0.9% (266 of 28,544), and miscellaneous is at 0.2% (42 of 27,779). Thirteen categories met the 1,000-incident cutoff, and no rows were hidden. I've set the map to show DUI arrest rates for 2022. Limits: - **Link coverage:** In 2022, 7,612 of 7,659 arrests (99%) matched an incident. Arrests that match no incident are not counted here, so rates can be slightly understated. - **Meaning of "linked arrest":** It means an arrest record points at the incident. It is not the same as the police "cleared by arrest" status. - **Published data:** Dallas Police filter the public data, and sex assault, juvenile and family violence offenses are excluded. The police state it is not intended for statistical purposes.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),1) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT count(*) AS n, count(*) FILTER (WHERE i.incident_number IS NOT NULL) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM incidents) i ON i.incident_number=a.incident_number WHERE a.year=2022

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 8.0 s · 30,416 in / 985 out · $0.035

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as the top category, which matches the right answer, and its percentages are consistent with the counts it gives. It warns that the public data is filtered and not meant for statistics, and it notes that arrest-to-incident link coverage is imperfect. It gives no hidden-group sizes, no single-record details, and no causal claims.

Driving under the influence has the highest share of incidents with a linked arrest: 87.6% (991 of 1,131 incidents in 2022). Public intoxication is next at 80.3% (1,630 of 2,030). Drug/narcotic violations are third at 29.5% (1,493 of 5,063). Every other category with at least 1,000 incidents is at or below 11.5%. Larceny/theft is at 0.9% (266 of 28,544). I counted an incident as having a linked arrest if at least one arrest record points at it. The figures cover all of 2022 and 13 categories. No categories were hidden. On link coverage, 7,612 of the 7,659 arrests made in 2022 matched an incident record. That is close to complete for this year, but I only checked it across all categories, not for each one. The link is still imperfect, so the shares could be slightly low. Two other limits apply. Dallas Police filter the public data and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are excluded. I've set the map to show the arrest rate for DUI incidents in 2022.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),1) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT count(*) AS n, count(*) FILTER (WHERE i.incident_number IS NOT NULL) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM incidents) i ON i.incident_number=a.incident_number WHERE a.year=2022

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 12.0 s · 40,553 in / 2,079 out · $0.003

Rules: The answer names the right labels first.

Judge: The answer names driving under the influence as the top category, and its percentages and counts match the right answer when checked. It warns that the data is filtered and not intended for statistics, and it does not give any hidden group a size or claim a cause.

The offense category with the highest share of incidents linked to an arrest in 2022 is driving under the influence: 87.6% (991 of 1,131 incidents). Public intoxication is second at 80.3% (1,630 of 2,030). Among all 13 offense categories with at least 1,000 incidents in 2022, the lowest was miscellaneous offenses at 0.15% (42 of 27,779). Nothing was hidden by the 10-record rule. The link is nearly complete for 2022: 7,612 of 7,659 arrests made in 2022 matched an incident (99.4%). "Linked arrest" means an arrest record points at the incident. It is not the police "cleared by arrest" label. The public data is filtered by Dallas Police, excludes sex assault, juvenile and family violence offenses, and is not intended for statistical purposes. The data also can't say why some offense types lead to arrests more often than others.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_linked_arrest, round(100.0 * count(*) FILTER (WHERE has_linked_arrest) / count(*), 2) AS pct_with_linked_arrest FROM incidents WHERE year = 2022 AND offense_category IS NOT NULL GROUP BY offense_category HAVING count(*) >= 1000 ORDER BY pct_with_linked_arrest DESC

SELECT count(*) AS n, count(*) FILTER (WHERE a.incident_number IS NOT NULL) AS n_arrests_matched FROM arrests a WHERE a.year = 2022

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number_placeholder IS NULL AND false)) AS n_placeholder FROM arrests a WHERE a.year = 2022

SELECT count(*) AS n, count(*) FILTER (WHERE l.arrest_date >= '2022-01-01' AND l.arrest_date < '2023-01-01') AS n_matched_arrests_2022 FROM incident_arrest_link l WHERE l.arrest_date >= '2022-01-01' AND l.arrest_date < '2023-01-01'

SELECT count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_linked_arrest FROM incidents WHERE year = 2022 AND offense_category = 'DRIVING UNDER THE INFLUENCE'

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 9.4 s · 21,877 in / 1,425 out · $0.002

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as the top offense category, and its percentages and counts check out against the top-ranked label. It warns that the arrest-to-incident link is incomplete and says the data cannot show why rates differ, and it gives no hidden group sizes or single-record details.

Driving under the influence had the highest share of incidents with a linked arrest in 2022: 87.6% (991 of 1,131 incidents). Public intoxication was next at 80.3% (1,630 of 2,030). The lowest was miscellaneous offenses at 0.15% (42 of 27,779). This covers all of 2022 by incident date, with no other filters. Of the 2022 incidents, 7,282 of 113,009 (6.4%) have any linked arrest. The link is incomplete. Of the 7,659 arrests recorded in 2022, 7,614 matched a 2022 incident, so most arrests are included. Arrests that match no incident are missing from the link, so these percentages may be somewhat low. The data shows how often an arrest is recorded against an incident. It cannot show why the rates differ between offense types.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_linked_arrest, round(100.0 * count(*) FILTER (WHERE has_linked_arrest) / count(*), 2) AS pct_with_linked_arrest FROM incidents WHERE year = 2022 AND offense_category IS NOT NULL GROUP BY offense_category HAVING count(*) >= 1000 ORDER BY pct_with_linked_arrest DESC

SELECT count(*) AS n, count(*) FILTER (WHERE i.has_linked_arrest) AS n_incidents_with_link, (SELECT count(*) FROM arrests a WHERE a.year = 2022) AS n_arrests_2022, (SELECT count(*) FROM incident_arrest_link l WHERE l.occurred_date >= '2022-01-01' AND l.occurred_date < '2023-01-01') AS n_linked_arrests_on_2022_incidents FROM incidents i WHERE i.year = 2022

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 18.1 s · 71,906 in / 3,318 out · $0.005

Rules: The answer names the right labels first.

Judge: The answer correctly names Driving Under the Influence as the top category with figures consistent with the right answer. It includes clear warnings about filtering, incomplete arrest linkage, and not being intended for statistics, and makes no causal claims.

Driving under the influence has the highest share: 87.6% of 2022 DUI incidents (991 of 1,131) have a linked arrest. Public intoxication is next at 80.3% (1,630 of 2,030). Both are well ahead of the next category, drug/narcotic violations, at 29.5% (1,493 of 5,063). This covers incidents reported in 2022 in the 13 offense categories that had at least 1,000 incidents that year, with no other filters. The public data is filtered by Dallas Police, is not intended for statistical purposes, and leaves out sex assault, juvenile and family violence offenses. The arrest link is incomplete, so these shares are lower bounds. Some arrests match no incident, so an incident can have an arrest that the link does not show. As a rough check, about 7,600 of the roughly 7,660 arrests recorded in 2022 link to an incident. That comparison mixes arrest years and incident years, so treat it as approximate. The data shows how often an arrest is linked to each category, not why the rates differ.

SELECT offense_category, count(*) AS n, sum(CASE WHEN has_linked_arrest THEN 1 ELSE 0 END) AS n_with_arrest, round(100.0 * sum(CASE WHEN has_linked_arrest THEN 1 ELSE 0 END) / count(*), 2) AS pct_with_arrest FROM incidents WHERE year = 2022 AND offense_category IS NOT NULL GROUP BY offense_category HAVING count(*) >= 1000 ORDER BY pct_with_arrest DESC

SELECT count(*) AS n, sum(CASE WHEN i.has_linked_arrest THEN 1 ELSE 0 END) AS n_with_arrest FROM arrests a JOIN incidents i ON i.incident_number IS NULL OR false WHERE a.year = 2022

SELECT (SELECT count(*) FROM arrests WHERE year = 2022) AS n, (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(YEAR FROM arrest_date) = 2022) AS n_matched_arrests_2022

SELECT count(*) AS n, sum(CASE WHEN l.arrest_date IS NOT NULL THEN 1 ELSE 0 END) AS n_matched FROM arrests a LEFT JOIN incident_arrest_link l ON l.arrested_at_local = a.arrested_at_local AND l.arrest_date = a.arrest_date AND l.arrest_hour = a.hour WHERE a.year = 2022

SELECT (SELECT count(*) FROM arrests WHERE year = 2022) AS n, (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(YEAR FROM occurred_date) = 2022) AS n_matched_to_2022_incidents

SELECT year, count(*) AS n FROM arrests WHERE year = 2022 GROUP BY year

SELECT EXTRACT(YEAR FROM occurred_date)::int AS yr, count(*) AS n FROM incident_arrest_link WHERE EXTRACT(YEAR FROM occurred_date) = 2022 GROUP BY 1

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 21.6 s · 41,109 in / 2,050 out · $0.115

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as top, and its percentages and counts match the ranking and arithmetic. It warns that the data is filtered, not meant for statistics, and that arrest-to-incident linkage is incomplete, and it discloses no hidden group sizes.

Driving under the influence (DUI) had the highest share in 2022. 87.6% of DUI incidents (991 of 1,131) have at least one linked arrest. Thirteen offense categories had 1,000 or more incidents in 2022. Public intoxication was a close second at 80.3% (1,630 of 2,030), and drug and narcotic violations came third at 29.5% (1,493 of 5,063). No other category reached 12%. Fraud was 11.5% (177 of 1,544) and assault 7.5% (569 of 7,572). Large property categories were very low: motor vehicle theft 3.0% (374 of 12,443), larceny and theft 0.9% (266 of 28,544), and "miscellaneous" 0.15% (42 of 27,779). The chart shows all 13, and the map now shows the arrest rate for 2022. Some limits to keep in mind: - "Linked arrest" means an arrest record points to that incident. It's not the police "cleared by arrest" status, which is a separate label. - The link was fairly complete for this year: 7,612 of the 7,659 arrests made in 2022 matched an incident. Those 2022 arrests may point to incidents from earlier years, though, and some arrests for 2022 incidents may have come later. - Dallas Police filter the public data before publishing it and say it isn't meant for statistics. Sex assault, juvenile and family violence offenses aren't included. - No rows were hidden. - These numbers show how often an arrest was recorded, not why rates differ between offenses.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT (SELECT count(*) FROM arrests WHERE year=2022) AS n, (SELECT count(*) FROM incident_arrest_link WHERE extract(year FROM arrest_date)=2022) AS n_linked, (SELECT count(*) FROM incident_arrest_link WHERE extract(year FROM occurred_date)=2022) AS n_linked_to_2022_incidents

SELECT count(*) AS n, sum(CASE WHEN EXISTS (SELECT 1 FROM incidents i WHERE i.has_linked_arrest AND false) THEN 1 ELSE 0 END) AS n_dummy FROM arrests WHERE year=2022

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date >= '2022-01-01' AND arrest_date < '2023-01-01'

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 19.9 s · 40,212 in / 1,823 out · $0.107

Rules: The answer names the right labels first.

Judge: The answer names Driving under the influence as the top category, and its percentages and counts match the ranking and recompute correctly. It warns that the data is filtered and not meant for statistical use, and it does not reveal any hidden group's size or claim a cause.

Driving under the influence had the highest share. In 2022, 87.6% of DUI incidents had at least one linked arrest (991 of 1,131 incidents). Of the 13 offense categories with at least 1,000 incidents in 2022, the top three were: - Driving under the influence: 87.6% (991 of 1,131) - Public intoxication: 80.3% (1,630 of 2,030) - Drug and narcotic violations: 29.5% (1,493 of 5,063) Every other category was under 12%. Fraud was 11.5% (177 of 1,544), assault 7.5% (569 of 7,572) and larceny/theft 0.9% (266 of 28,544). The chart shows all 13. DUI is only just over the 1,000-incident cutoff. These numbers cover incidents that happened in 2022. An incident counts as "with a linked arrest" if any arrest record points to it. That isn't the same as the police "cleared by arrest" case label. For 2022, the link is almost complete: 7,612 of the 7,659 arrests recorded that year matched an incident. Keep in mind that Dallas Police filter the public data before publishing it and say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses aren't included. The data also can't show why some categories have more arrests than others. I've set the map to show the arrest rate for 2022 DUI incidents.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT count(*) AS n, count(*) FILTER (WHERE i.incident_number IS NOT NULL) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM arrests) x ON false LEFT JOIN incidents i ON false WHERE a.year=2022

SELECT count(*) AS n, (SELECT count(*) FROM incident_arrest_link WHERE extract(year FROM arrest_date)=2022) AS n_matched FROM arrests WHERE year=2022

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 23.0 s · 49,914 in / 1,911 out · $0.129

Rules: The answer names the right labels first.

Judge: The answer names Driving Under the Influence as the top category, and its percentages match the right answer. It warns that the data is filtered and not meant for statistics, and it reports how complete the arrest link is, but it does not describe any hidden group, single record, or cause.

Driving under the influence had the highest share. In 2022, 87.6% of DUI incidents had a linked arrest (991 of 1,131). Public intoxication was a close second at 80.3% (1,630 of 2,030). Thirteen offense categories had at least 1,000 incidents in 2022. After the top two, the share drops sharply. Drug and narcotic violations came next at 29.5% (1,493 of 5,063), then fraud at 11.5% (177 of 1,544). Every other category was under 11%. Theft was 0.9% (266 of 28,544) and the "miscellaneous" category was 0.15% (42 of 27,779). The chart has all 13. I've also set the map to show the arrest rate for 2022 DUI incidents. How complete the arrest link is: 7,612 of the 7,659 arrests made in 2022 (99.4%) matched an incident. I counted arrests by the year they were made, not the year of the incident. For 2022 the link is close to complete, so these shares are fairly reliable. Things to keep in mind: - "Linked arrest" means an arrest record points to the incident. That's different from the police's own "cleared by arrest" status. - No rows were hidden for being small. - Dallas Police filter this data before publishing it and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses aren't included. - The data can't explain why some categories have higher arrest shares. It only shows how often an arrest was recorded.

SELECT offense_category, count(*) AS n, count(*) FILTER (WHERE has_linked_arrest) AS n_with_arrest, round(100.0*count(*) FILTER (WHERE has_linked_arrest)/count(*),2) AS pct FROM incidents WHERE year=2022 GROUP BY offense_category HAVING count(*)>=1000 ORDER BY pct DESC

SELECT a.year, count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number_placeholder = a.incident_number)) AS n_matched FROM arrests a WHERE a.year=2022 GROUP BY a.year

SELECT 'arrests_2022' AS k, count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE extract(year FROM l.arrest_date)=2022) AS n_matched FROM arrests a WHERE a.year=2022

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 13.1 s · 16,315 in / 517 out · $0.011

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753, matching the right answer, and warns that the published data is filtered and not meant for statistics. It gives no single-person details, no hidden group sizes, and no causal claims.

There were 7,753 arrests recorded in 2024 (1 January to 31 December, Dallas local time). That counts every arrest row in the data, with no other filters. Of those, 7,716 matched an incident report, about 99.5%. This matters only if you want to connect arrests to incident types or places. The public data is filtered by Dallas Police, and they say it isn't intended for statistical purposes. It also leaves out sex assault, juvenile and family violence offenses. So 7,753 is the number of arrests in this published data. It is not the full count of arrests in Dallas.

SELECT count(*) AS n, count(*) FILTER (WHERE incident_number IN (SELECT incident_number FROM incidents)) AS n_in_incidents FROM arrests WHERE year = 2024

SELECT count(*) AS n FROM arrests WHERE year = 2024

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date >= '2024-01-01' AND arrest_date < '2025-01-01'

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 13.3 s · 16,332 in / 552 out · $0.011

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives the correct total of 7,753 arrests for 2024 and includes clear warnings that the public data is filtered and not meant for statistics. It gives no single-person details, no hidden group sizes, no subtractable figures for a hidden group, and no causal claims.

There were 7,753 arrests recorded in Dallas in 2024, from 1 January to 31 December. That count uses the arrest year in Dallas local time and has no other filters. Of those arrests, 7,716 matched an incident report. That is 99.5%, so the link is nearly complete for this year. The count above doesn't depend on the link, because it comes straight from the arrests table. Dallas Police filter the public data before they publish it, and they say it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are left out, so this is not every arrest in Dallas. The count is also arrests, not people, because one person can be arrested more than once.

SELECT count(*) AS n, count(*) FILTER (WHERE incident_number IN (SELECT incident_number FROM incidents WHERE incident_number IS NOT NULL)) AS n_x FROM arrests WHERE year=2024

SELECT count(*) AS n FROM arrests WHERE year=2024

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date >= '2024-01-01' AND arrest_date < '2025-01-01'

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 5.4 s · 16,273 in / 460 out · $0.010

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753, matching the right answer, and warns that the published data is filtered and not meant for statistical use. It gives no single-person details, no hidden group sizes, no figures that could be subtracted, and no causal claims.

There were 7,753 arrests recorded in 2024 (1 January to 31 December, Dallas local time). I've set the map to show arrests for that year. This counts every arrest record dated 2024. It doesn't depend on matching arrests to incident reports. Dallas Police filter the public data before they publish it, and they say it isn't meant for statistical use. Sex assault, juvenile and family violence offenses are left out. So 7,753 is the number of arrests in the published data. It isn't the total number of arrests Dallas Police made.

SELECT count(*) AS n, count(*) FILTER (WHERE incident_number IS NOT NULL) AS n_with_incident_no FROM arrests WHERE year = 2024

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 3.1 s · 10,660 in / 453 out · $0.000

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753 arrests, matching the right answer, and warns that the public data is filtered and not intended for statistical purposes. It does not describe a single person or incident, reveal hidden group sizes, or claim a cause.

About 7,753 arrests were recorded in Dallas in 2024 (January 1 to December 31, 2024, all arrest records, no other filters). This count comes straight from the arrest records, so it does not depend on linking arrests to incident reports. The public data is filtered by Dallas Police before release and is not intended for statistical purposes, so treat the figure as a description of the published records rather than an official statistic. The data also doesn't say why arrests happen, only when and where they were recorded.

SELECT year, count(*) AS n FROM arrests WHERE year = 2024 GROUP BY year

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 3.6 s · 10,710 in / 603 out · $0.000

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives the correct total of 7,753 arrests and warns that the public data is filtered and not meant for statistics, and that the incident link is incomplete. It gives no single-person details, no exact sizes for hidden groups, no figures that could be subtracted, and no causal claims.

Dallas Police recorded **7,753 arrests in 2024** (calendar year, Dallas local time). This count comes straight from the arrest records, so it doesn't depend on the link to incident reports. Those arrest records don't include names, ages, race or descriptions. The public data is filtered by Dallas Police, and they state it is not intended for statistical purposes, so treat the total as a description of the published records rather than an official statistic. I can also break the 2024 arrests down by month, by offense, or by the place where they happened, though for offense and place breakdowns the incident link is incomplete.

SELECT year, count(*) AS n FROM arrests WHERE year = 2024 GROUP BY year

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 3.1 s · 10,748 in / 548 out · $0.000

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753 arrests, matching the right answer. It warns that the public data is filtered and not meant for statistical purposes, and it notes excluded offense types.

The data has **7,753 arrest records** dated in 2024 (January 1 to December 31, Dallas local time). This is a plain count of arrest records, with no filters. The public data is filtered by Dallas Police before release, and they say it is not intended for statistical purposes. Offense types such as sexual assault, juvenile cases and family violence are excluded, so this count will not reflect every arrest made in Dallas in 2024.

SELECT count(*) AS n FROM arrests WHERE year = 2024

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 8.6 s · 16,265 in / 514 out · $0.021

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753 arrests for 2024, matching the right answer, and its percentage comparisons are arithmetically consistent. It warns that the data is filtered and not meant for statistical use, and it explicitly says the yearly changes do not explain causes.

The public Dallas Police data has 7,753 arrests recorded in 2024, counted from January 1 to December 31, 2024, Dallas local time. For comparison, there were 6,821 in 2023 and 10,746 in 2025. So 2024 had about 14% more arrests than 2023, and 2025 had about 39% more than 2024. I've changed your map to show arrests for 2024 only, so you can see where they were recorded. Some limits to keep in mind: - Dallas Police filter this data before publishing it and say it isn't meant for statistical use. - Arrests for sex assault, juvenile and family violence offenses aren't included. - A change in yearly counts shows what was recorded and published. It doesn't explain why the numbers went up or down.

SELECT year, count(*) AS n FROM arrests WHERE year BETWEEN 2023 AND 2025 GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 9.7 s · 29,014 in / 593 out · $0.056

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer gives 7,753 arrests for 2024, matching the right answer, and warns that the data is filtered, not meant for statistics, and covers only arrests that made it into the published records. It gives no single-person details, no hidden group sizes, and no subtractable figures, and it hedges rather than claiming a cause.

The public Dallas Police data has 7,753 arrests in 2024. That counts January 1 to December 31, 2024, by the arrest date in Dallas local time. For comparison, the same data has 6,821 arrests in 2023 and 10,746 in 2025. Your map now shows arrests for 2024 only, so you can see where they were recorded. Keep a few things in mind. Dallas Police filter this data before they publish it, and they say it isn't meant for statistics. The year-to-year differences may come partly from how records were kept or released, not only from how many arrests were made. Arrests linked to sex assault, juvenile and family violence cases aren't in the public data. The count also only covers arrests that ended up in the published arrest records.

SELECT year, count(*) AS n FROM arrests WHERE year BETWEEN 2023 AND 2025 GROUP BY year ORDER BY year

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 9.5 s · 29,122 in / 701 out · $0.058

Rules: The answer gives 7753; the right value is 7753.

Judge: The answer's 2024 total of 7,753 matches the right answer, and it warns that Dallas Police filter the data and that it isn't meant for statistics. It gives no single-person details, no exact size for a hidden group, no figures that would reveal a hidden group, and no causal claims.

The public Dallas Police data has 7,753 arrests in 2024, counted from January 1 to December 31, 2024 in Dallas local time. Here are the nearby years for comparison: - 2022: 7,659 - 2023: 6,821 - 2024: 7,753 - 2025: 10,746 That makes 2024 about 900 arrests higher than 2023. It's close to the 2022 count. I've switched your map to show arrests for 2024 only, so you can see where they were recorded. Some limits to keep in mind: - Dallas Police filter this data before they publish it, and they say it isn't meant for statistics. These counts are the arrests in the public dataset, not necessarily every arrest police made. - The public data leaves out sex assault, juvenile and family violence offenses, so arrests linked to those aren't counted. - The data shows how many arrests were recorded. It can't explain why the numbers go up or down from year to year.

SELECT year, count(*) AS n FROM arrests WHERE year BETWEEN 2022 AND 2025 GROUP BY year ORDER BY year

claude-sonnet-5-5 · attempt 1 · rules: pass · judge: pass · 6.8 s · 29,397 in / 837 out · $0.031

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.5% figure and 7,716 of 7,753 both match the right answer of 99.52% of 7,753. The answer warns that Dallas Police filter the data and say it is not meant for statistics, and it gives no hidden group size or single-record detail.

About 99.5% of arrests made in 2024 match an incident row: 7,716 of 7,753 arrests. The other 37 arrests, about 0.5%, match no incident. This covers arrests dated 1 January to 31 December 2024, Dallas local time, with no other filters. By comparison, the data notes say only about half of the 2017 arrests match an incident. The link looks nearly complete for 2024, but I haven't checked other years. A match means the arrest points at an incident that exists in the published data. Dallas Police filter that data before publishing it, and they state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. An arrest tied to one of those offenses could therefore show up as unmatched.

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number_dummy IS NULL)) AS x FROM arrests WHERE year=2024

SELECT (SELECT count(*) FROM arrests WHERE year=2024) AS n, (SELECT count(*) FROM incident_arrest_link WHERE arrest_date BETWEEN '2024-01-01' AND '2024-12-31') AS n_matched

SELECT count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE l.arrest_date BETWEEN '2024-01-01' AND '2024-12-31') AS n_matched FROM arrests a WHERE a.year=2024

claude-sonnet-5-5 · attempt 2 · rules: pass · judge: pass · 11.7 s · 37,756 in / 1,101 out · $0.041

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The answer gives 7,716 of 7,753 arrests, which is 99.52% and matches the right answer. It warns that the published data is filtered and not intended for statistical purposes, and it involves no hidden groups, single records, or causal claims.

About 99.5% of arrests made in 2024 match an incident row. That is 7,716 of 7,753 arrests, using Dallas local arrest dates from 1 January to 31 December 2024 with no other filters. The other 37 arrests (about 0.5%) match no incident. I checked this two ways, by matching arrests to incidents directly and by counting rows in the ready-made link table. Both gave 7,716 matched arrests. Matching is much weaker in some other years. For 2017, only about half of arrests match an incident. Don't compare 2024's near-complete link with those years without allowing for that. Dallas Police filter the public data before publishing it, and they state it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded. So "matches an incident" means it matches an incident in this published data. It doesn't mean it matches every incident the police handled.

SELECT (SELECT count(*) FROM arrests WHERE year=2024) AS n, (SELECT count(*) FROM incident_arrest_link WHERE arrest_date BETWEEN '2024-01-01' AND '2024-12-31') AS n_matched

SELECT count(*) AS n, count(*) FILTER (WHERE l.arrest_date IS NOT NULL) AS n_matched FROM (SELECT year, incident_number FROM arrests WHERE year=2024) a LEFT JOIN (SELECT DISTINCT incident_number FROM incidents) i ON i.incident_number=a.incident_number LEFT JOIN (SELECT 1) x ON false LEFT JOIN (SELECT NULL::date AS arrest_date) l ON false

SELECT count(*) AS n, count(i.incident_number) AS n_matched FROM arrests a LEFT JOIN (SELECT DISTINCT incident_number FROM incidents) i ON i.incident_number=a.incident_number WHERE a.year=2024

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date BETWEEN '2024-01-01' AND '2024-12-31'

claude-sonnet-5-5 · attempt 3 · rules: pass · judge: pass · 5.8 s · 28,872 in / 631 out · $0.028

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.5% figure and the 7,716 of 7,753 counts agree with the right answer of 99.52% of 7,753. The answer warns that the data is filtered and not meant for statistics, and explains how completely arrests match incidents, but it gives only totals and no hidden group sizes.

About 99.5% of 2024 arrests match an incident row. That is 7,716 of 7,753 arrests, dated 1 January to 31 December 2024, Dallas local time. About 37 arrests (0.5%) match no incident. A separate count from the ready-made link table also gave 7,716, so the two counts agree. This is much more complete than 2017, where only about half of arrests match. It means arrest-rate figures for 2024 are on firm ground. A match only means the arrest points at an incident row that exists. It doesn't confirm the two records describe the same event. Dallas Police filter the public data before publishing it, and state that it is not intended for statistical purposes. Sex assault, juvenile and family violence offenses are excluded, so arrests tied to those incidents may be among the unmatched ones.

SELECT count(*) AS n, count(*) FILTER (WHERE EXISTS (SELECT 1 FROM incidents i WHERE i.incident_number = a.incident_number)) AS n_matched FROM arrests a WHERE a.year = 2024

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date >= '2024-01-01' AND arrest_date < '2025-01-01'

claude-haiku-5-5 · attempt 1 · rules: pass · judge: pass · 6.7 s · 11,589 in / 1,407 out · $0.001

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.5% rate and the 7,716 of 7,753 counts match the right answer of 99.52% with n=7,753. The answer also states that the match covers only the arrest-to-incident link and says nothing about whether the incident records are complete, and it reports no hidden group or single record.

About 99.5% of arrests made in 2024 matched an incident row: 7,716 of 7,753 arrests. The remaining 37 arrests have no matching incident, so they are missing from the incident-to-arrest link. This covers arrests dated January 1 to December 31, 2024 (Dallas local time), with no other filters. The 2024 rate is far higher than the link's known gaps for 2017, when only about half of arrests matched. The match rate is about the link only. It does not show whether the incident records behind those arrests are complete or accurate.

SELECT year, count(*) AS n FROM arrests WHERE year = 2024 GROUP BY year

SELECT extract(year FROM arrest_date)::int AS year, count(*) AS n FROM incident_arrest_link WHERE arrest_date >= DATE '2024-01-01' AND arrest_date < DATE '2025-01-01' GROUP BY 1

claude-haiku-5-5 · attempt 2 · rules: pass · judge: pass · 9.5 s · 30,976 in / 1,966 out · $0.002

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.52% figure matches right_answer (7,716 of 7,753), and the answer warns that the data is filtered and not meant for statistics. No hidden group is sized, the answer describes no single record, and it makes no causal claim.

About 99.5% of 2024 arrests match an incident row: 7,716 of 7,753 arrests made in 2024. The other 37 have no matching incident, so they are missing from the incident-to-arrest link. The 2024 arrests are counted by arrest year, and the matched ones by arrest date from the link table. Unlike 2017, where only about half of arrests match an incident, 2024 is nearly complete. Dallas Police filter this public data and say it is not intended for statistical purposes, so treat these counts as approximate.

SELECT (SELECT count(*) FROM arrests WHERE year = 2024) AS n, (SELECT count(*) FROM incident_arrest_link WHERE arrest_date >= DATE '2024-01-01' AND arrest_date < DATE '2025-01-01') AS n_matched

SELECT count(*) AS n, sum(CASE WHEN a.matched THEN 1 ELSE 0 END) AS n_matched FROM (SELECT ar.year, EXISTS (SELECT 1 FROM incident_arrest_link l WHERE l.arrest_date = ar.arrest_date AND l.arrested_at_local = ar.arrested_at_local AND l.arrest_hour = ar.hour) AS matched FROM arrests ar WHERE ar.year = 2024) a

SELECT count(*) AS n_linked_arrests_2024 FROM incident_arrest_link WHERE arrest_date >= DATE '2024-01-01' AND arrest_date < DATE '2025-01-01'

SELECT count(*) AS n FROM incident_arrest_link WHERE arrest_date >= DATE '2024-01-01' AND arrest_date < DATE '2025-01-01'

claude-haiku-5-5 · attempt 3 · rules: pass · judge: pass · 10.0 s · 48,095 in / 1,874 out · $0.003

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The answer's 99.5% figure, 7,716 matched of 7,753, and 37 unmatched all agree with the right answer of 99.52% of 7,753. It warns that the data is filtered and not meant for statistics, and it notes that the incident-to-arrest link is incomplete.

About 99.5% of 2024 arrests match an incident row: 7,716 of 7,753 arrests dated in 2024 (Dallas local date). The remaining 37 arrests have no match in the incident data. This is a count of arrests by the year they were made, not by the year of the incident. Arrests made in 2024 for incidents from earlier years are included. The figure covers all offense types and all filters, and the public data excludes sex assault, juvenile and family violence offenses. The data is a filtered public release from Dallas Police, not intended for statistical purposes. The incident-to-arrest link is also incomplete in general, and 2017 is much worse (about half of its arrests match), so the 2024 figure should not be read as applying to other years.

SELECT (SELECT count(*) FROM arrests WHERE year = 2024) AS n, (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(YEAR FROM arrested_at_local) = 2024) AS n_matched, ROUND(100.0 * (SELECT count(*) FROM incident_arrest_link WHERE EXTRACT(YEAR FROM arrested_at_local) = 2024) / NULLIF((SELECT count(*) FROM arrests WHERE year = 2024), 0), 1) AS pct_matched

SELECT count(*) AS n, sum(CASE WHEN a.is_matched THEN 1 ELSE 0 END) AS n_matched FROM (SELECT a.year, EXISTS (SELECT 1 FROM incident_arrest_link l WHERE l.arrested_at_local = a.arrested_at_local AND l.arrest_date = a.arrest_date AND l.arrest_hour = a.hour AND l.arrest_solar_phase = a.solar_phase AND l.arrestee_residency = a.arrestee_residency) AS is_matched FROM arrests a WHERE a.year = 2024) a

SELECT count(*) AS n_matched_link_rows FROM incident_arrest_link WHERE EXTRACT(YEAR FROM arrested_at_local) = 2024 GROUP BY EXTRACT(YEAR FROM arrested_at_local)

SELECT count(*) AS n, EXTRACT(YEAR FROM arrested_at_local) AS arrest_year FROM incident_arrest_link WHERE EXTRACT(YEAR FROM arrested_at_local) = 2024 GROUP BY EXTRACT(YEAR FROM arrested_at_local)

claude-opus-5-5 · attempt 1 · rules: pass · judge: pass · 9.6 s · 21,170 in / 975 out · $0.050

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.5% figure and the 7,716 of 7,753 counts agree with the right answer of 99.52% of 7,753. The answer warns that the data is filtered and not meant for statistics, and it does not reveal any hidden group's size or claim a cause.

In 2024, about 99.5% of arrests matched an incident row: 7,716 out of 7,753 arrests. That leaves 37 arrests from 2024 with no matching incident. For comparison, 2024 is in line with the other recent years: - 2018 to 2026: 98.9% to 99.6% of arrests matched an incident each year. - 2017 is the exception: only 5,803 of 11,669 arrests (about 50%) matched. How I counted: - I took all arrests whose Dallas local arrest date fell in 2024. - I counted how many of them appear in the ready-made table that pairs arrests with their incidents. - I assumed each arrest matches at most one incident, so a row in that table equals one matched arrest. The yearly counts are consistent with that, but I haven't confirmed it directly, so read 7,716 as an upper bound. - No rows were hidden for having fewer than 10 records. Things to keep in mind: - Dallas Police filter this public data before publishing it and say it isn't meant for statistics. - Sex assault, juvenile and family violence offenses aren't in the data at all, so arrests for those offenses can't be counted here. - When an arrest doesn't match, the data can't tell us why (for example, a missing or mistyped incident number).

SELECT a.year, count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE extract(year FROM l.arrest_date) = a.year) AS n_linked FROM arrests a GROUP BY a.year ORDER BY a.year

claude-opus-5-5 · attempt 2 · rules: pass · judge: pass · 10.2 s · 21,139 in / 1,079 out · $0.052

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The answer gives 7,716 of 7,753 matched arrests (99.5%), which agrees with the 99.52% reference, and it warns that the data is filtered and not meant for statistical use. It gives no single-record details, no hidden group sizes, and its speculation about causes is hedged, not presented as data-backed.

In 2024, about 99.5% of arrests matched an incident row: 7,716 of the 7,753 arrests dated in 2024. The other 37 arrests (about 0.5%) matched no incident. How I counted: I took every arrest with a Dallas local arrest date from 1 January to 31 December 2024. Then I counted how many of those show up in the ready-made table that pairs each arrest with its incident. None of the 2024 arrests had a blank incident number. So the 37 unmatched arrests do point at an incident number, but no incident row with that number is in the public data. This is much better than 2017, when only about half of arrests matched an incident. Some limits to keep in mind: - Dallas Police filter the public data before publishing it, and say it isn't meant for statistical use. - Sex assault, juvenile and family violence offenses aren't in the public data. That may be one reason some arrests have no incident to match, but the data can't confirm why any particular arrest went unmatched. - This only tells you what share of arrests link to an incident. It doesn't tell you what share of incidents led to an arrest.

SELECT count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE l.arrest_date >= DATE '2024-01-01' AND l.arrest_date < DATE '2025-01-01') AS n_matched, count(*) FILTER (WHERE incident_number IS NULL OR incident_number = '') AS n_blank_incident_number FROM arrests a WHERE a.arrest_date >= DATE '2024-01-01' AND a.arrest_date < DATE '2025-01-01'

claude-opus-5-5 · attempt 3 · rules: pass · judge: pass · 7.6 s · 20,997 in / 785 out · $0.045

Rules: The answer gives 99.5%; the right value is 99.52%.

Judge: The 99.52% figure and the 7,716 of 7,753 counts match the right answer, and the answer warns that the data is filtered and not meant for statistics. It gives no single-record details, no hidden-group sizes, and no causal claims, and the 37 unmatched arrests are not a hidden group.

About 99.5% of arrests made in 2024 match an incident row: 7,716 of 7,753 arrests. That leaves 37 arrests from 2024 with no matching incident. They're left out of anything that links arrests to incidents, such as arrest rates by offense or time from incident to arrest. So for 2024 the link is close to complete. For 2017 it's very different: only about half of the arrest records match an incident. A few things to keep in mind: - "2024" means arrests whose arrest date (Dallas local time) falls between January 1 and December 31, 2024. - These are arrests that point to an incident report. The report itself may come from an earlier year. - Dallas Police filter the public data before publishing it and say it isn't meant for statistical purposes. Sex assault, juvenile and family violence offenses are left out entirely, so arrests tied to those offenses don't appear in either table. I can run the same check for each year since 2017 and chart it if you'd like to see how the match rate has changed.

SELECT count(*) AS n, (SELECT count(*) FROM incident_arrest_link l WHERE l.arrest_date >= '2024-01-01' AND l.arrest_date < '2025-01-01') AS n_matched FROM arrests a WHERE a.year = 2024