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Record W2042392095 · doi:10.3138/cjccj.47.3.581

Inflammatory Rhetoric? Baseless Accusations? A Response to Gabor's Critique of Racial Profiling Research in Canada

2005· article· en· W2042392095 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRacial profilingRhetoricProfiling (computer programming)CriminologyCriminal justiceSociologyPsychologyPolitical scienceRace (biology)Gender studies

Abstract

fetched live from OpenAlex

Racial profiling has become one of the most controversial issues facing the Canadian criminal justice system. In a recent article, Thomas Gabor dismisses much of the evidence of racial profiling in Canada as "baseless" and "inflammatory." We address Gabor's critique by highlighting findings from a Toronto survey which suggest that black youth are much more likely to report being stopped and searched by the police than youth from other racial backgrounds. Logistic regression analysis reveals that the impact of race remains strongly significant after controlling for social class, self-reported criminal activity, gang membership, drug and alcohol use, and public leisure activities. The article concludes with a discussion of the impact that racial profiling has on minority communities and a brief review of the potential benefits - and consequences - of mandating the police to collect their own stop and search data.

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)0.008
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.195
GPT teacher head0.421
Teacher spread0.226 · 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