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Record W2340030937 · doi:10.4309/jgi.2016.32.4

« La première fois que j’ai joué… » : l’expérience d’adolescents considérés comme ayant des difficultés avec les jeux de hasard et d’argent

2016· article· en· W2340030937 on OpenAlexvenueno aff
Annie-Claude Savard, Daniel Turcotte, Joël Tremblay

Bibliographic record

VenueJournal of Gambling Issues · 2016
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPleasureEmotivePsychologyContext (archaeology)HumanitiesSociologyArtPsychotherapistHistory

Abstract

fetched live from OpenAlex

This study describes the initial gambling experiences of teenagers who have developed problem gambling habits with regard to: a) the nature of the gambling activities, b) the significance of the first experience in terms of the benefits and attractive aspects of gambling, and c) the progression toward the development of problematic behaviours. The research design draws on secondary analysis of data from semi-structured interviews carried out with 31 adolescents with problem gambling behaviours in treatment for the consumption of psychoactive substances (PS). An analysis of the teenagers' responses reveals the existence of material, emotive and social benefits associated with their first gambling experience and the exacerbation of their behaviours. The results were analysed in light of the teenagers' social context: popularity of certain games, importance of performance, wealth and the pursuit of pleasure.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.241
Threshold uncertainty score0.807

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2410.059

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 head0.437
GPT teacher head0.485
Teacher spread0.049 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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