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Record W1820076221 · doi:10.1080/10550887.2010.489447

Sociodemographic and Substance Use Correlates of Gambling Behavior in the Canadian General Population

2010· article· en· W1820076221 on OpenAlexaboutno aff
Sílvia S. Martins, Lilian Ghandour, Grace P. Lee, Carla L. Storr

Bibliographic record

VenueJournal of Addictive Diseases · 2010
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationSubstance usePsychiatryPsychologyAddictionMedicineClinical psychologyGerontologyDemographyEnvironmental health

Abstract

fetched live from OpenAlex

This study describes sociodemographic and substance use correlates of gambling behaviors, measured among 9,481 past-year gamblers from the Canadian general population. Compared to non-problem gamblers in this study (N=8,035), the 98 problem gamblers who scored 8 or more points on the Canadian Problem Gambling Research Index were more likely to report being "drunk or high" while gambling (adjusted odds ratio [AOR]: 8.92; 95% confidence interval [CI]: 5.46,14.55; p<.001), to admit to having an alcohol or drug problem (AOR: 3.80; 95% CI:2.21,6.52; p<.001), and to use electronic gambling devices (AOR: 4.85; 95% CI: 3.08-7.66; p<.001).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.982

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)0.0000.000

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 head0.063
GPT teacher head0.360
Teacher spread0.297 · 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
Published2010
Admission routes1
Has abstractyes

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