Portrait des joueurs au Québec: Prévalence, incidence et trajectoires sur 4 ans (Portrait of gamblers in Québec: Prevalence, incidence and projections over 4 years) 2012 [Canada]
Bibliographic record
Abstract
Data stem from a five-year project entitled Portrait du jeu au Québec: Prévalence, incidence et trajectoires sur quatre ans (ENHJEU-QUÉBEC Study) funded by the concerted actions program of the Fonds de recherche du Québec – Société et Culture (FRQ-SC). The study main objective was to generate prevalence data on gambling behaviours and associated problems among the adult population of Quebec. A survey was carried out in 2009, and a follow-up study with participants covered a period of three ( 3) years to better assess various gambling trajectories (2009, 2010, 2011). The study was conducted with a random sample, representative of the non-institutionalized population aged 18 and over, speaking French or English, and living in private households throughout the province (12 008 respondents in 2012). In this project, data collection took place in the summer of 2012, yielding an overall response rate of 43.2%. The results of the project are supporting the Quebec Ministry of Health and Social Services and its regional health agencies with planni ng prevention and treatment programs and ensure that services in all regions of Quebec adequately address the needs of gamblers seeking help.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".