Evaluating the role of strengths and protective factors for youth with FASD and criminal legal system involvement: a scoping review
Bibliographic record
Abstract
Youth with fetal alcohol spectrum disorder (FASD) are overrepresented in the criminal legal system (CLS). There is greater recognition among scholars, policymakers, and professionals of the importance of strengths-based approaches for this population. The current scoping review (preregistered on the Center for Open Science; DOI: 10.17605/OSF.IO/6WAZE) aimed to determine what strengths and protective factors have been investigated for youth with FASD in the CLS, and how these have been identified, defined, and measured. Results identified an emerging body of literature of 16 peer reviewed articles. Strengths were often nested within deficit-based conversations and included individual (e.g. kindness), relational (e.g. caregiver support), and broader contextual level strengths (e.g. early diagnosis). To foster consistency, understanding, and better support this group, future research should purposefully incorporate strengths and protective factors into research and intervention frameworks and improve conceptual clarity when describing strengths and protective factors in this population.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".