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Record W2069654648 · doi:10.1007/s10899-012-9321-1

Problem Gambling Inside and Out: The Assessment of Community and Institutional Problem Gambling in the Canadian Correctional System

2012· article· en· W2069654648 on OpenAlexafffundabout
Nigel E. Turner, Denise L. Preston, Steven McAvoy, Laura Gillam

Bibliographic record

VenueJournal of Gambling Studies · 2012
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersChina Scholarship CouncilUniversity of TorontoOntario Problem Gambling Research CentreCentre for Addiction and Mental Health
KeywordsPrisonPsychologyPsychiatrySample (material)Juvenile delinquencyIndex (typography)Criminology

Abstract

fetched live from OpenAlex

This paper reports on the results of a multi-site survey of gambling behaviour and gambling problems amongst offenders in correctional institutions in Ontario, Canada, conducted between 2008 and 2011. A total of 422 (completion rate 61.5 %) incarcerated offenders (381 male and 41 female) took part in the study including 301 federal offenders and 121 provincial offenders. Based on the Problem Gambling Severity Index of the Canadian Problem Gambling Index (CPGI/PGSI) the prevalence rate of severe problem gambling was 8.9 prior to incarceration and 4.4 % during incarceration. These numbers are substantially higher than rates found among the general public. Thirty-four percent of the sample reported gambling in prison. Half of those who suffered from gambling problems before incarceration continued to have gambling problems during incarceration. People with problems related to slot machines prior to incarceration reported fewer gambling problems during incarceration compared to other problem gamblers.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.219
GPT teacher head0.452
Teacher spread0.233 · 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.

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

Citations43
Published2012
Admission routes3
Has abstractyes

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