The Influence of Music on Estimates of At-risk Gambling Intentions: An Analysis by Casino Design
Bibliographic record
Abstract
This research examined the relationship between casino atmosphere and at-risk gambling intentions (likelihood of gambling beyond planned levels). Video simulations were developed to represent two models of casino design. The playground design is distinguished by spaciousness, pleasing décor elements, green space and moving water. The gaming design focuses entirely on the gambling machines and features low ceilings and crowded gaming areas. Two simulations of each casino design were created by including either ambient gambling sounds or by replacing those sounds with a music track. Measures of psychological reactions and at-risk gambling intentions for the four settings were collected from 101 (56 males) gamblers. Music increased perceived at-risk gambling intentions in the playground setting. At-risk intentions, however, decreased with music for the gaming design. This study suggests atmospheric variations within a casino should be tailored to the specific macro gaming environment.
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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 | 0.001 |
| 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".