Experiences in the Canadian Criminal Justice System for Individuals with Fetal Alcohol Spectrum Disorders: Double Jeopardy?
Bibliographic record
Abstract
The study explored the experiences of individuals in the criminal justice system with a Fetal alcohol spectrum disorder (FASD) in order to identify possible ways to reduce the likelihood of re-entry into the criminal justice system. Semi-structured interviews were conducted to capture the voices of two participant groups: (1) individuals with an FASD, and (2) professionals who work with clients with an FASD. Qualitative research methods were used to analyse the data. Analysis of 20 interviews (n = 21) yielded three major themes: (1) primed to enter the system, (2) hindered within the system, and (3) strengthened to move beyond the system. Participants identified biological (e.g., poor decision-making abilities and inability to self-advocate), psychological (e.g., mental health issues and victimization), and social factors (e.g., limited social support) that increased risk of re-entry into the criminal justice system. Participants also identified strengths (e.g., hope, willingness to change, and resilience) that could assist with more positive outcomes. The study provides insight into the unique experiences of individuals in the criminal justice system with an FASD – with reference to both risk factors and relevant personal strengths. Implications for practice are discussed, including suggestions for increasing support, awareness, and a focus on strengths.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.048 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".