The Sydney Laval Universities Gambling Screen: Preliminary data
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
Current instruments used in epidemiological studies suffer serious methodological problems, one being the failure to properly conceptualize the constructs of problem and pathological gambling. The purpose of this study is to develop a brief single purpose survey instrument to identify prevalence rates and estimates for treatment services. The South Oaks Gambling Screen (SOGS) and Sydney Laval Universities Gambling Screen (SLUGS) were administered to a sample of 2069 college and university students in Scotland. Results showed that 4% of respondents met criteria for probable pathological gambling. SOGS scores correlated significantly with rated level of problems but less than half (44%) of those meeting SOGS criteria indicated a need for treatment. Responses on the SLUGS indicated that impaired control and spending more time and money is a feature commonly reported among non-problem gamblers. The SLUGS may represent a useful brief single purpose screen for problem gambling and self-reported need for treatment.
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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 | 0.002 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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