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Record W1970041415 · doi:10.1177/1098611111404179

Measuring the Impact of Police Discretion on Official Crime Statistics: A Research Note

2011· article· en· W1970041415 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolice Quarterly · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsUniversité de MontréalMontreal Police Service
Fundersnot available
KeywordsDiscretionCrime statisticsWorkloadVariation (astronomy)Service (business)Official statisticsCriminologyPolitical sciencePsychologyBusinessLawStatisticsEconomicsManagement

Abstract

fetched live from OpenAlex

This article examines the effect that collective bargaining had on official crime statistics compiled between 1998 and 2009 in Montreal, Canada. Police officers collectively decided to reduce their use of record-discretion on two occasions, to increase administrative workload and pressure their employers. Considerable increases of recorded assaults and mischief were observed, despite no apparent variation of reported infractions measured by calls for service. Recorded and reported car thefts and burglaries displayed no significant variation. Results suggest that observed variations can be explained in terms of temporary differential treatment of specific incidents rather than increases of reported criminality or proactive police activity. This research challenges the reliability of official statistics as measures of crime and demonstrates that external circumstances can influence police recording practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.242
GPT teacher head0.473
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it