Public Stigma of Disordered Gambling: Social Distance, Dangerousness, and Familiarity
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
Disordered gambling stigma was examined. University students (117 male, 132 female) rated vignettes describing males with five health conditions (schizophrenia, alcohol dependence, disordered gambling, cancer, and a no diagnosis control with subclinical problems) on a measure of attitudinal social distance. A mixed ANOVA revealed that, in keeping with hypotheses, disordered gambling was more stigmatized than the cancer and control conditions. Interactions suggested that stigma may be influenced by context (i.e., order of vignette appearance) and participant characteristics (i.e., sex and ethnicity), although follow–up analyses revealed this was not the case for disordered gambling. Perceived dangerousness attributions and familiarity (previous experience with a disordered gambler) were also examined. As predicted, perceived dangerousness was positively correlated with social distance scores. Familiarity ratings were unrelated to social distance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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