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Record W2047527280 · doi:10.3138/cjccj.2012.e25

Trends in the Seriousness of Youth Crime in Canada, 1984–2011

2013· article· en· W2047527280 on OpenAlexvenueaboutno aff
Peter J. Carrington

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSeriousnessPossession (linguistics)CriminologyProperty crimePsychologyDemographyPolitical scienceViolent crimeLawSociology

Abstract

fetched live from OpenAlex

Trends in the seriousness of youth crime in Canada from 1984 to 2011 are assessed by analysing changes over time in the mix of offences for which young people have been reported by police as chargeable. Four indicators of seriousness are used: Statistics Canada crime seriousness weights, the proportion of youth accused of an indictable offence, a fivefold classification of offences; and a selection of high volume offences. All four analyses clearly indicate a substantial downward trend over the period in the overall seriousness of police-reported youth crime. The decline in seriousness is mainly due to a very large decrease in the proportion of youth accused of the serious offence of break and enter and a correspondingly large increase in the proportion accused of the minor offences of common assault, cannabis possession, and offences against the administration of justice. The proportion of chargeable youth accused of major offences against the person has increased substantially relative to its level in 1984, but it remains low compared to property and other offenders. Thus, reported youth crime in Canada has become proportionally more violent but less serious overall.

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)0.003
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 score0.061
Threshold uncertainty score0.439

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.119
GPT teacher head0.324
Teacher spread0.205 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicCrime Patterns and InterventionsFrench-language works237,207