A Class Action on Behalf of Federally-Sentenced Women with Mental Health Issues
Bibliographic record
Abstract
The inquiry into Ashley Smith's in-custody death is playing a crucial role in opening up the typically inscrutable prison system and forcing the Correctional Service of Canada (CSC) to defend its policies and practices under intense public scrutiny.Yet there is a risk that Smith will be understood as an extreme outlier, rather than an indicator of a deeper problem.There remains a broader need for concrete and systemic reform of the prison system as it treats Federally-Sentenced Women (FSW) with mental health issues.In this analysis I will consider how civil litigation might be used in creative ways to seek remedies for this segment of the prison populations.Specifically, I will explore the viability of a class action lawsuit against CSC on behalf of FSW with mental health issues, with a sub-class of Aboriginal female prisoners.While there are admittedly a number of practical obstacles to bringing this type of lawsuit, a class action against the Crown offers an interesting combination of private and public law advantages as well as the potential for both individual recourse and systemic change.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.033 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".