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Record W2146356715 · doi:10.3138/cjccj.2012.e17

Determinants of Police Strength in Canadian Cities: Assessing the Impact of Minority Threat

2015· article· en· W2146356715 on OpenAlexaffvenueabout
Rick Ruddell, Matthew O. Thomas

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsDemographic economicsLaw enforcementPer capitaUnemploymentPopulationCriminologyPolitical scienceDemographyEconomic growthSociologyLawEconomics

Abstract

fetched live from OpenAlex

The minority threat proposition posits that the size of minority populations is positively associated with levels of formal social control. Recent research in other nations has shown a clear and consistent relationship between the size of subordinate populations and the number of police as well as increased law enforcement spending. This study examined the relationships, in Canada’s largest cities, between six indicators of minority populations and both the ratio of police officers to residents and per capita policing expenditures. Inconsistent with the results of recent US, German, and Spanish studies, indicators of population heterogeneity were not significantly associated with police strength or spending. Levels of police-reported violent crime and population density, however, were strongly associated with both measures of police strength. Police strength was also positively associated with cities that had municipal police services, higher unemployment rates, and the percentage of conservative voters in provincial elections. Implications for the development of theories of formal social control 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 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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.190
GPT teacher head0.419
Teacher spread0.229 · 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 teacher head, not a consensus.

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

Citations17
Published2015
Admission routes3
Has abstractyes

Explore more

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