Reconciling Conflicting Demands in the EGM Industry: Government, Industry, Media and the Community
Bibliographic record
Abstract
Gambling has traditionally been a part of the national psyche in Australia. In more recent times, however, attitudes in much of the community are changing, with the result that governments are widely expected to develop increasingly restrictive public policies related to electronic gaming machines (EGMs). The purpose of this paper is to examine the relationships between government, business, and the broader community in the context of the gambling industry in New South Wales (NSW), Australia, and to explore the political and social policy implications of reconciling these competing stakeholder interests. The research draws on the results of 38 face-to-face interviews with key stakeholders in Nevada and NSW conducted during 2005 and 2006, with an additional two interviews in 2013 in NSW. Furthermore, 47 newspaper articles were analyzed to further identify key issues. Against a background of widespread community skepticism, we argue that governments have an important role in setting public policies and striking the appropriate balance between protecting those who have, or are susceptible to, gambling problems and the majority of people who play EGMs without any ensuing problems. However, businesses also have an important contribution to make by being proactively socially responsible, thereby increasing their legitimacy and negating the need for further government interventions.En Australie, les jeux de hasard sont traditionnellement ancrés dans les mœurs. Toutefois, depuis quelque temps, les attitudes d’une grande partie de la population sont en train de changer, de sorte que l’on s’attend généralement à ce que les gouvernements élaborent des politiques publiques de plus en plus restrictives à l’égard des appareils de jeux électroniques. Dans cet article, on examine les relations qui existent entre le gouvernement, les entreprises et l’ensemble de la population dans le contexte de l’industrie des jeux de hasard en Nouvelle-Galles du Sud, en Australie et on analyse les implications politiques et sociales d’une conciliation des intérêts complémentaires de ces intervenants. Ces travaux de recherche s’appuient sur les résultats de 38 entrevues en face à face avec les principaux intervenants au Nevada et en Nouvelle-Galles du Sud qui ont été réalisées au cours de 2005 et 2006, auxquelles s’ajoutent deux autres entrevues qui ont été effectuées en 2013 en Nouvelle-Galles du Sud. De plus, 47 articles de journaux ont été analysés pour définir davantage les principaux problèmes. Avec comme toile de fond un scepticisme généralisé dans la population, on soutient que les gouvernements ont un rôle important à jouer dans l’élaboration de politiques publiques et dans le maintien d’un juste équilibre lorsqu’il s’agit de protéger ceux qui ont des problèmes de jeu, ou ceux qui peuvent y succomber, et la majorité des gens qui utilisent des appareils de jeux électroniques sans que cela devienne problématique. Toutefois, les entreprises ont également un rôle important à jouer en prenant l’initiative d’agir de façon responsable sur le plan social, ce qui aura pour effet de renforcer leur légitimité et d’éliminer la nécessité d’avoir recours à d’autres interventions gouvernementales.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".