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Record W2084026621 · doi:10.3138/cpp.39.4.559

The Crime Drop and the General Social Survey

2013· article· en· W2084026621 on OpenAlexaffvenueabout
Graham Farrell, P. Jeffrey Brantingham

Bibliographic record

VenueCanadian Public Policy · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
FundersEconomic and Social Research Council
KeywordsCriminologyGeneral Social SurveyDrop outSurvey researchEuropean Social SurveySurvey data collectionPolitical scienceDemographic economicsSociologySocial scienceEconomicsSocioeconomicsLawMathematicsStatistics

Abstract

fetched live from OpenAlex

Most indicators including Uniform Crime Reports and the International Crime Victims Survey suggest that Canada has experienced a dramatic “crime drop” similar to other advanced countries. Yet Canada’s General Social Survey (GSS), which ought to be the most methodologically sophisticated measure, suggests crime in this country has been stable or increasing. This study reviews the evidence. It concludes with the hypothesis that the GSS trends are misleading but that further research is needed to identify an explanation for this anomaly. Potential research and policy implications are discussed.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.016
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.063
GPT teacher head0.356
Teacher spread0.293 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2013
Admission routes3
Has abstractyes

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