An updated systematic review of the literature on fetal alcohol spectrum disorder and the criminal legal system
Bibliographic record
Abstract
People with fetal alcohol spectrum disorder (FASD) can experience a range of individual, social, and systemic challenges that may increase the likelihood of life adversity, including contact with the criminal legal system (CLS). The purpose of this article was to update a 2018 systematic review of literature on this intersection of FASD and the CLS. We searched ten academic databases for studies with people with FASD involved in the CLS, as well as caregivers and service providers who support them. A total of 54 studies were identified, published between April 2017 and March 2024, which is more than double what was present in 2018. Most of this research was conducted in Canada and Australia with individuals with FASD across the lifespan. These studies indicate growth in the literature on FASD prevalence in CLS settings (n = 3), CLS-related trajectories for people with FASD (n = 15), the needs and strengths of people with FASD involved in the CLS (n = 9), FASD-informed CLS responses (n = 17), and CLS professional knowledge, attitudes, and practices related to FASD (n = 10). Despite these advancements, there remain limitations in the evidence base such as a lack of specific and rigorous intervention studies; longitudinal research on outcomes and trajectories; generalizable prevalence estimates; the unique ways in which needs, risk, and protective factors may be experienced by people with FASD; how socio-cultural factors impact people with FASD and the research conducted in this area; as well as training opportunities for professionals supporting those with FASD in the CLS. These findings are integrated with results reported in the 2018 review to identify priority areas for future research.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".