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Record W3196739120 · doi:10.11575/prism/32674

The Extent of Youth Victimization, Crime and Delinquency in Alberta, 1999

2000· article· en· W3196739120 on OpenAlexaboutno aff
J.T. Gomes, L.D. Bertrand, J.J. Paetsch, Joseph P. Hornick

Bibliographic record

VenueOpen MIND · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsJuvenile delinquencyCriminologyPsychology

Abstract

fetched live from OpenAlex

This report provides information about youth victimization, crime and delinquency in Alberta. In-school surveys of youth aged 12 to 18 years living in selected larger cities, smaller cities and towns and rural areas were conducted in 1999. The findings presented in this report describe students' perceptions of youth crime and personal safety, victimization experiences occurring while at school and outside of school over the past year, lifetime and past year involvement in delinquent behaviours, prevalence of weapon possession at school, and contact with the police and criminal justice system. The survey instrument was designed to collect data on variables related to major social and psychological environmental factors known to be associated with youth victimization and delinquency using a self-report method. Besides measures of prevalence of youth victimization and delinquency, additional information was gathered to describe the context of the experience for the most serious incidents that occurred over the past year. While findings in this report include all of the 2,001 respondents, two additional reports have been prepared in order to provide more in depth analyses of Calgary and of Edmonton students. These reports are titled: The Extent of Youth Victimization, Crime and Delinquency in Alberta, 1999: Summary of Calgary Findings; and The Extent of Youth Victimization, Crime and Delinquency in Alberta, 1999: Summary of Edmonton Findings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.054
GPT teacher head0.365
Teacher spread0.311 · 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 designOther design
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

Citations4
Published2000
Admission routes1
Has abstractyes

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