Carceral abolition as disability justice for incarcerated people with fetal alcohol spectrum disorder (FASD)
Bibliographic record
Abstract
People with fetal alcohol spectrum disorder (FASD) are overrepresented in the Canadian carceral system (Flannigan et al., 2018a; Flannigan et al., 2018b; MacPherson et al., 2011; McLachlan, 2017). Reports indicate that their experiences in custody tend to be marked by higher rates of trauma, violence, and institutional struggles, contributing to continued contact with the carceral system over their lifetimes (Baldry, 2018; Standing Senate Committee on Human Rights, 2020). Despite this adversity, a review of the existing literature indicates that research about FASD and contact with the carceral system has not adequately critiqued the legitimacy of the carceral system itself. Exploration of possible alternatives to imprisonment for people with FASD has been limited. The experiences of people with FASD in the carceral system underscore the need for prison abolition and the development of robust alternatives to incarceration. Research demonstrates that community-based alternatives, such as restorative justice, can be successfully adapted to meet the needs of people with FASD (Blagg et al., 2019; Evans & Bourgon, 2020; Flannigan et al., 2022). Furthermore, these alternative justice strategies are a meaningful step toward achieving both prison abolition and disability justice.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".