Involuntary Treatment Legislation in Canada: Implications for Pregnant People and Parents
Bibliographic record
Abstract
Since 2023, three Canadian provincial governments have announced plans to establish involuntary treatment laws that would apply to people who use criminalized substances, with one province passing such legislation in 2025. In this commentary, the authors attend to the implications of this approach for pregnant people and parents and identify two key concerns. First, involuntary treatment punishes parents, likely contributing to the apprehension of their children—present and future—and undermining their access to health services. Second, involuntary treatment legislation will likely be applied in ways that bolster fetal rights and fetal protection discourse, enabling the confinement of pregnant people.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.037 | 0.020 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.018 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 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".