Gambling motives and symptoms of problem gambling in frequent slots players
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
Motives for gambling were examined among patrons of slots venues who reported playing electronic gaming machines at least weekly (N=849). According to scores on the Problem Gambling Severity Index (PGSI), there were 331 (39.0%) participants at low risk, 330 (38.9%) at moderate risk, and 188 (22.1%) at high risk of Pathological Gambling. Scores on the Coping and Enhancement scales of the Gambling Motives Questionnaire (GMQ) had independent effects on PGSI scores. Cluster analysis of Coping and Enhancement scores identified Low Emotion Regulation (LER; n=189), Primarily Enhancement (PE; n=338), and Coping and Enhancement (CE; n=322) subtypes. More CE gamblers (80.1%) had PGSI scores that suggested problem or Pathological Gambling than the PE (56.8%) or LE (36.0%) subtypes. Gamblers who frequently play slot machines are at elevated risk of Pathological Gambling if they play slots as a means of self-regulating their negative emotional states.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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