Understanding the needs of justice‐involved adults with fetal alcohol spectrum disorder in an Indigenous community
Bibliographic record
Abstract
Individuals with fetal alcohol spectrum disorder (FASD) experience a range of neurodevelopmental challenges, often compounded by social and environmental adversity. One of the most concerning outcomes that can be associated with FASD is involvement in the justice system, where individuals with FASD are vastly over-represented. Individuals with FASD who are both justice-involved and Indigenous experience added layers of marginalization. In this community-based study, we explored the needs of 16 adults who participated in an FASD-informed restorative justice program in an Indigenous community in Alberta, Canada. Clinical record reviews and client interviews were used to gather information. Diverse needs were identified, including pervasive neurodevelopmental difficulties, notable physical and mental health challenges, complex experiences of psychosocial trauma, and varied criminogenic needs. This study increases our understanding of the unique and complex biopsychosocial and criminogenic needs of Indigenous justice-involved adults with FASD. Such an understanding is a first step in developing tailored interventions for individuals with FASD and has important practice and policy implications for supporting positive outcomes. For Indigenous individuals with FASD, intervention efforts should be integrated within the community context to promote collective healing.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".