Reproductive healthcare in prison: A qualitative study of women’s experiences and perspectives in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: To explore women's experiences and perspectives of reproductive healthcare in prison. METHODS: We conducted a qualitative study using semi-structured focus groups in 2018 with women in a provincial prison in Ontario, Canada. We asked participants about their experiences and perspectives of pregnancy and contraception related to healthcare in prison. We used a combination of deductive and inductive content analysis to categorize data. A concept map was generated using a reproductive justice framework. RESULTS: The data reflected three components of a reproductive justice framework: 1) women have limited access to healthcare in prison, 2) reproductive safety and dignity influence attitudes toward pregnancy and contraception, and 3) women in prison want better reproductive healthcare. Discrimination and stigma were commonly invoked throughout women's experiences in seeking reproductive healthcare. CONCLUSIONS: Improving reproductive healthcare for women in prison is crucial to promoting reproductive justice in this population. Efforts to increase access to comprehensive, responsive, and timely reproductive healthcare should be informed by the needs and desires of women in prison and should actively seek to reduce their experience of discrimination and stigma in this context.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.008 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".