Savoir plus, miser moins : une maîtrise des principaux concepts en statistiques et probabilités distingue-t-elle les comportements de jeu?
Bibliographic record
Abstract
Prevention and treatment research for pathological gambling suggests that knowledge of statistics and probabilities (SP) improves decisions related to gambling. As such, it is expected that people who understand SP concepts will be more protected from excessive gambling. Laboratory studies nevertheless reveal longer gambling times and behaviours that defy a good understanding of SP in this population, similar to the behaviours of people without this knowledge. Are these behaviours reflected in the gambling habits of people with knowledge of SP when they choose to gamble in their personal lives? Seventy-four university students, divided into two groups based on their knowledge of SP, were questioned about their gambling behaviours and problems. The results show that the participants gamble very little and have few gambling problems, whether or not they have SP knowledge. The paper discusses the modest contribution of SP knowledge to gambling behaviour in the university population and the effect of other variables that could help discriminate between individuals in terms of their knowledge of SP and their gambling behaviours.RésuméLa recherche en prévention et en traitement du jeu d’argent pathologique suppose que la connaissance des statistiques et des probabilités (SP) améliore les prises de décision menant à la participation à des jeux de hasard et d’argent (JHA). Il est dès lors attendu que les gens maîtrisant les notions de SP soient davantage protégés des excès au jeu. Or, des études réalisées en laboratoire rapportent de plus longues durées de jeu et des comportements de jeu défiant une bonne compréhension des SP parmi cette population, similaires à ceux qui n’ont pas ces connaissances. Est-ce que ces comportements se reflètent dans les habitudes de jeu des personnes maitrisant les SP, lorsqu’elles choisissent de jouer dans leur vie personnelle? Soixante-quatorze universitaires répartis en deux groupes selon leur maîtrise des SP ont été sondés sur leurs comportements et problèmes de jeu. Les résultats montrent que les participants jouent peu et éprouvent peu de problèmes de jeu, qu’ils possèdent les connaissances en SP ou non. L’apport modéré de la connaissance des SP sur les comportements de jeu auprès d’une population universitaire déjà fortement scolarisée, ainsi que l’effet d’autres variables pouvant aider à discriminer les individus quant à leur maîtrise des SP et leurs comportements de jeu sont discutés dans cette étude.
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 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 | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".