Early Detection of Gambling Among At-Risk Adolescents. Validation of EDGAR-A Scale
Bibliographic record
Abstract
Despite the fact that minors have prohibited access to commercial gambling, and legislation trying to constrain gambling, an important proportion declares that they have bet either online, or by illegally entering gambling venues. This situation highlights the need to implement selective prevention programs that requires assessment tools to identify vulnerable groups. This paper aims to design and validate a scale of evaluation for the psycho-social characteristics that predict onset and maintenance of gambling behavior among adolescents. 2,716 students of Secondary Education, 15.12 years (± 1.03) answered a frequency, intensity and problematic gambling questionnaire and a scale to evaluate risk profiles. The resulting scale is compounded by 26 items classified in 4 sub-scales: Accessibility, Risk Perception, Normative Perception and Parental Attitudes. Internal consistency coefficients were: 0.668, 0.728, 0.746 and 0.818 respectively, and 0.811 for the total scale. Results offer a robust support on the structural validity and internal consistency of the Early Detection of Gambling among At-Risk Adolescents (EDGAR-A) Scale, a useful tool for the design and assessment of effective preventive interventions.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".