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Youth Gang Exit

2016· book-chapter· en· W2501231839 on OpenAlex
Laura Dunbar

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAdvances in psychology, mental health, and behavioral studies (APMHBS) book series · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsVariety (cybernetics)CriminologyArgument (complex analysis)Process (computing)Order (exchange)Psychological interventionSociologyPsychologyComputer scienceMedicineArtificial intelligenceBusiness

Abstract

fetched live from OpenAlex

Youth gangs and their members have been studied in a variety of contexts; however the issue of desistance has received less attention. This chapter seeks to address this gap. In order to situate the material to be covered, the chapter begins with an introduction to the topic of youth gangs. Next, an overview of the concept of desistance and how it is measured is provided. Following that is a review of some prominent criminological perspectives demonstrating that leaving the gang is a complex process involving the interaction of a combination of factors. The process of desistance and methods for leaving the gang are also briefly discussed. Several approaches have been developed to address youth gangs and their members. These approaches are reviewed and different interventions under these headings are discussed with Canadian examples provided. Finally, an argument for the development of a comprehensive strategy for youth gang exit is presented.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.147
GPT teacher head0.500
Teacher spread0.353 · 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