On the Feasibility of In-Venue Observations of Electronic Gaming Machine Gamblers and Game Characteristics
Bibliographic record
Abstract
Detailed observational studies of undisturbed gambler behaviour in venues are rare, especially when the focus is on continuous gambling such as electronic gaming machines (EGMs). EGMs are the main source of harmful gambling in New Zealand and all EGMs in New Zealand now include a mandatory pop-up message feature. The present study reports on 48 hours of in situ observations of EGM gamblers in casino and non-casino (pub) venues in New Zealand. We sought to establish whether relatively detailed observations of EGM features and gambler behaviour in venues were possible. The EGM feature that we focused on were pop-up messages, given their harm-minimization potential and the relative ease with which they can be observed. However, other EGM features were also documented, along with descriptive accounts of associated gambler behaviour. The results establish that relatively detailed (quantitative or qualitative) observational data can be collected in venues by using smart phones. The data showed that pop-up messages were generally attended to, but had little observable effect on gambler behaviour in venues. Direct in situ observation of gamblers can provide ecologically valid information to complement more common experimental and survey-based approaches. Suggestions are made for developing the procedure.Les études d’observation détaillée in situ sur le comportement non perturbé de joueurs sont rares, surtout si on met l’accent sur le jeu continu, comme avec les appareils de jeux électroniques. En Nouvelle-Zélande, ces appareils sont la principale source de jeux compulsifs, et tous les appareils dans ce pays incluent dorénavant une fonctionnalité obligatoire de message contextuel. La présente étude fait état de 48 heures d’observation in situ de joueurs sur appareils dans des casinos ou d’autres lieux (bars) en Nouvelle-Zélande, et on a cherché à déterminer s’il était possible de faire des observations relativement détaillées des caractéristiques et du comportement de joueurs dans ces lieux. On a mis l’accent sur la fonctionnalité des messages contextuels pour analyser leur potentiel de diminuer des méfaits et leur relative facilité à les observer. On a aussi consigné d’autres fonctionnalités d’appareils de jeu, ainsi que des comptes-rendus descriptifs du comportement des joueurs associés. Les résultats montrent que l’on peut recueillir des données d’observation in situ relativement détaillées (quantitatives ou qualitatives) à l’aide de téléphones intelligents. Les données montrent que les messages contextuels ont généralement été pris en compte, mais qu’ils ont eu peu d’effet observable sur le comportement des joueurs. L’observation directe de joueurs peut fournir des informations écologiquement valables pour appuyer les approches expérimentales communes par sondage. On y fait aussi quelques suggestions pour mettre en œuvre une procédure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".