Experiences of pregnancy in prison: understanding access to prenatal care in Canadian federal prisons
Bibliographic record
Abstract
Criminalized women represent an acutely marginalized portion of the population with specific healthcare needs that have been overlooked within the Canadian carceral landscape. This thesis aims to focus on the unique experiences and needs of pregnant and incarcerated women in Canadian Federal Prisons with a focus on the prenatal and post-natal care that they receive while incarcerated. This thesis presents an analysis of three qualitative interviews with individuals involved in healthcare and advocacy for pregnant women in prison, by interpreting them in light of the current academic and grey literature. The dominant themes that emerged throughout this thesis include an emphasis on standard of care, community-based programming and supporting mothers and babies as a unit, in order to have the best possible outcome. This project draws on insights from medical anthropology, Foucauldian theory and feminist criminology to frame the discussion of the needs of incarcerated women in Canada. Specifically, it argues that women in Canadian federal prisons should: 1) have access to the same level of care as non-incarcerated women; 2) be empowered to be mothers (should they so desire); and 3) be supported in their return to the community. Through analyzing the interviews, literature, and publicly available grey literature, the thesis focuses heavily on the complex challenges faced by marginalized and incarcerated women, the extent of institutional power to make a difference, and the challenges of early motherhood.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.032 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".