A Losing Hand: Gambling Among Youth in Custody for Criminal Offenses
Bibliographic record
Abstract
Abstract: It is well documented that incarcerated adults have rates of gambling problems that are among the highest found in any population. Less well studied are rates of problem gambling, gambling related incarcerations, and gambling related incidents among youth housed in secure facilities for criminal behavior. This presentation will describe a study that assessed gambling behaviors and related consequences of 166 youth housed at Oregon Youth Authority facilities. Findings indicated that nearly 45% of these youth scored within the High Severity range as measured by the Gambling Problem Severity Subscale of the Canadian Adolescent Gambling Index (CAGI/GPSS) when asked about their gambling behavior in the 3-months prior to their current commitment. When comparing pre-commitment gambling to gambling while incarcerated, 24% had a reduced problem gambling severity score and 12% has an increased score. Survey data suggested that youth gambling behaviors were linked to 1 out of every 8 male juvenile commitments and about 1 in every 4 female commitments. Further, gambling was identified as a significant contributor to altercations between youth housed within secure facilities. These results present a distinct need for youth to be screened for gambling problems upon entering and exiting the Juvenile Justice System, and for prevention and intervention services to be offered within juvenile corrections settings. Implications Statement: Very few studies have investigated rates of problem gambling, gambling related incarcerations, and gambling related incidents among youth housed in secure facilities for criminal behavior. The results of study to be presented has important implications for gambling harm reduction and the Juvenile Justice System.
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.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".