The psychology of music in gambling environments: An observational research note
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Effects of the listening context on responses to music largely have been neglected despite the prevalence of music in our everyday lives. Furthermore, there has been no research on the role of music in gambling environments (e.g., casinos, amusement arcades) despite gambling's increased popularity as a leisure pursuit. An exploratory observational study in gambling arcades was carried out to investigate (i) how music is used as background music in amusement arcades, and (ii) how slot machines utilize music in their design. Results indicated that arcades often have music that caters for their customer demographics and that this may influence gambling behaviour. Furthermore, music from the slot machine itself appears to produce important impression formations about the machine (i.e., quality of the machine, familiarity, distinctiveness, and the sound of winning). It is suggested that music (whether it is in the gambling environment or in the activity itself) has the potential to be important in the acquisition, development, and maintenance of gambling behaviour. Some preliminary ideas and hypotheses to be tested are offered.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it