Has there been a "feminization" of gambling and problem gambling in the United States?
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
This paper examines the question of whether there has been a "feminization" of gambling and problem gambling in the United States. Feminization refers to the idea that more women are gambling, developing problems and seeking help for problems related to gambling than in the past. Data from a theoretically derived sample of four states are examined to identify patterns in the distribution of gambling participation and the prevalence of problem gambling in the general population. Despite widespread acceptance of the notion of the feminization of gambling and problem gambling, men remain significantly more likely than women to participate regularly in most types of gambling. Most gambling activities remain highly gendered; however, in the United States, the widespread introduction of gaming machines is associated with increases in gambling and problem gambling among women. The present analysis highlights the importance of taking socio-demographic characteristics besides gender into account when considering the distribution of gambling and problem gambling in the general population.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it