MétaCan
Menu
Back to cohort
Record W2148465095 · doi:10.3138/cjccj.2013.e05

Aboriginal People and Confidence in the Police

2014· article· en· W2148465095 on OpenAlexaffvenueabout
Liqun Cao

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsNeighbourhood (mathematics)Context (archaeology)PerceptionPsychologySocial psychologyConfidence intervalCriminologySociologyGeographyMedicine

Abstract

fetched live from OpenAlex

No nationally representative study has been conducted about differential confidence in the police between Aboriginal people and non-Aboriginal persons in Canada. Based on the 2009 General Social Survey of Canada, this article examines the influence of Aboriginal status on confidence in the police. Consistent with the theoretical prediction, results of multiple regression analyses show that Aboriginal people and visible minorities have a significantly lower level of confidence than other Canadians do, after the effects of both expressive and instrumental concerns are controlled for. The persistent effects of Aboriginal or visible minorities status raise questions about racial relationships in Canada. Other significant predictors of confidence in the police are expressive concerns, such as trust, and instrumental concerns, such as community context, crime experiences, perceptions of crime in one’s own neighbourhood, and police contact. Findings indicate that continued reform measures are needed for the police force to gain the confidence of Aboriginal people and visible minorities in Canada.

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)0.001
metaresearch head score (Gemma)0.008
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 score0.419
Threshold uncertainty score0.842

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.101
GPT teacher head0.372
Teacher spread0.272 · 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

Citations85
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicPolicing Practices and PerceptionsFrench-language works237,207