Comparing the Japanese Version of the Gambling Functional Assessment -Revised to an American Sample
Bibliographic record
Abstract
The Gambling Functional Assessment -Revised (GFA-R) was developed to determine the degree to which gambling behaviour was maintained by positive reinforcement or escape. For this study, the GFA-R was translated into Japanese and completed by 126 Japanese university students, who also completed the Japanese version of the South Oaks Gambling Screen (SOGS). Their results were compared to those from 133 American university students. All respondents endorsed gambling for positive reinforcement to a greater extent than as an escape. For both samples, the factor structure for the original GFA-R adequately fit the data, and internal consistency measures were very good. SOGS scores correlated more strongly with gambling as an escape than for positive reinforcement. The Japanese version of the GFA-R may be a useful research tool in a variety of ways, and may be helpful for practitioners in Japan interested in knowing the contingency maintaining their client's gambling behaviour.
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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".