Electronic Gambling Machines Outside Casinos: An Environmental Study of Risk Factors in Gambling Venues
Bibliographic record
Abstract
Electronic gambling machine (EGM) licenses are meant to be a complementary revenue source for liquor establishments. Considering this, retailers with more than one license to operate EGMs may benefit from promoting their gambling offer, which may in turn facilitate excessive gambling behaviours. This study compares establishments that possess a single license to operate EGMs with those that are multi-licensed regarding four environmental risk factors: advertisements, automated teller machines, isolated gambling area, and EGM operating hours. A field observation was carried out by seven pairs of observers in 166 establishments in Capitale-Nationale de Quebec (QC), Canada. In each establishment, observers had to complete an observational grid on an iPod touch to gather environmental data related to the identified variables. Results from the stepwise logistic regression show that being a multi-licensed establishment increases the chance of having longer operating hours and displaying non-regulated advertisements that promote gambling. Multi-licensed establishments tend to offer a more attractive gambling environment, which may increase the risk of excessive gambling. Reinforcement of regulations for responsible gambling is discussed.RésuméPour les établissements ayant un permis d’alcool, posséder une licence d’exploitation d’appareils de jeux électroniques (AJE) se traduit par un revenu complémentaire. De ce fait, les détaillants ayant plus d’une licence d’exploitation d’AJE peuvent tirer parti de la promotion de leur offre de jeu, ce qui, en retour, peut encourager des comportements de jeu excessifs. Cette étude compare les établissements qui détiennent une seule licence d’exploitation d’AJE avec ceux qui en détiennent plusieurs en tenant compte de quatre facteurs de risque environnementaux : la publicité, les guichets automatiques, la zone de jeu isolée et les heures d’exploitation des AJE. Une observation sur le terrain a été effectuée par sept paires d’observateurs dans 166 établissements de Capitale-Nationale de Québec (QC), Canada. Dans chaque établissement, ils ont recueilli des données environnementales liées aux variables identifiées qu’ils ont compilées dans une grille d’observation sur un iPod touch. Les résultats du modèle logistique utilisant la régression séquentielle montrent que le fait, pour un établissement, d’avoir plusieurs licences augmente la possibilité de prolonger les heures d’exploitation et d’afficher des publicités non réglementées qui font la promotion du jeu. Les établissements ayant plusieurs licences ont tendance à offrir un environnement de jeu plus attrayant, ce qui peut accroître le risque de jeu excessif. Un resserrement des règles pour une réglementation responsable du jeu est à l’étude.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".