A National Study on Gambling Among US College Student-Athletes
Bibliographic record
Abstract
OBJECTIVE: The authors examined the national prevalence of gambling problems and sports wagering among US college student-athletes. PARTICIPANTS: A national sample of 20,739 student-athletes participated in the study. METHODS: The authors used data from the first national survey of gambling among college athletes, conducted by the National Collegiate Athletic Association. RESULTS: Men (62.4%) consistently had higher past-year prevalence of gambling than did women (42.8%). The authors identified 4.3% of men and 0.4% of women as problem or pathological gamblers. Among the most popular forms of gambling were playing cards, lotteries, and games of skill, with male-to-female prevalence ratio ranging 1.3-5.6 across various gambling activities. Athletes in golf and lacrosse were more likely to report sports wagering than were other athletes. Athletes in gender-specific sports wagered more prevalently than did athletes in unisex sports. CONCLUSION: Gambling prevalence may be underestimated in this population because respondents' athletics eligibility is at stake. This study provides important baseline data for future cohorts of athletes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".