Correlates of gambling among youth in an inner-city emergency department.
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
Correlates of past year gambling were examined in a diverse sample of 1128 youth ages 14 to 18 (54.1% female, 58.0% African American) presenting to an inner-city emergency department (ED). Overall, 22.5% of the sample reported past-year gambling. Male youth were more likely to gamble than female youth, and African American youth reported higher rates of past-year gambling than non-African American youth. Significant bivariate correlates of gambling included lower academic achievement, being out of school, working more than 20 hours per week, alcohol, cigarette, and marijuana use, alcohol problems, severe dating violence, moderate and severe general violence, and carrying a weapon. When examined simultaneously, being male, African American, out of school, working for pay, alcohol and marijuana use, severe general violence, and carrying a weapon all emerged as significant correlates of past-year gambling, largest amount of money gambled, and gambling frequency. In addition, involvement in severe dating violence was associated with frequency and largest amount gambled. The results suggest that gambling is common among youth in the inner city and is associated with several risk behaviors. The inner-city ED may provide a context for screening and intervention to address multiple risk behaviors. (PsycINFO Database Record (c) 2009 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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 it