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Record W2079216766 · doi:10.1007/s10899-015-9540-3

Endorsement of Criminal Behavior Amongst Offenders: Implications for DSM-5 Gambling Disorder

2015· article· en· W2079216766 on OpenAlexafffundabout
Nigel E. Turner, Randy Stinchfield, John McCready, Steven McAvoy, Peter Ferentzy

Bibliographic record

VenueJournal of Gambling Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsPublic Health OntarioCentre for Addiction and Mental Health
FundersCentre for Addiction and Mental HealthUniversity of TorontoUniversity of Minnesota
KeywordsPsychologyDSM-5Gambling disorderPopulationConvergent validityCriminal behaviorPsychiatryIndex (typography)Clinical psychologyCriminologyPsychometricsDemographySociology

Abstract

fetched live from OpenAlex

The fifth edition of the diagnostic and statistical manual (DSM) has changed the scoring threshold for a gambling disorder (GD) from five criteria to four and eliminated the illegal acts criterion. The impact of these changes was examined with data from a correctional population (N = 676) in Ontario, Canada. The offenders completed a self-report survey that included the Canadian problem gambling index, the South Oaks Gambling Screen and the DSM-IV criteria. Changing the threshold from 5 to 4 improved the convergent validity for GD and resulted in an increase in the percentage of offenders diagnosed with a GD from 7.4 to 10.2 %. The results also indicate that the illegal acts criterion contributes to the convergent validity of GD. The evidence supports the change in the threshold from five to four, but also reinforces the importance of examining illegal acts when dealing with an offender population. The incorporation of illegal acts into the "lying to others" criteria appears to make up, to some extent, for the removal of the illegal acts criterion.

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)0.001
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 score0.104
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.383
GPT teacher head0.503
Teacher spread0.120 · 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

Citations16
Published2015
Admission routes3
Has abstractyes

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