Invisible women: correctional facilities for women across Canada and proximity to maternity services
Bibliographic record
Abstract
Purpose This paper aims to describe the process to create an inventory of the facilities in Canada designated to incarcerate women and girls, health service responsibility by facility, facility proximity to hospitals with maternity services and residential programmes for mothers and children to stay together. This paper creates the inventory to support health researchers, prison rights advocates and policymakers to identify, analyse and respond to sex and gender differences in health and access to health services in prisons. Design/methodology/approach In spring 2019, this study conducted an environmental scan to create an inventory of every facility in Canada designated for the incarceration of girls and women, including remand/pretrial custody, immigration detention, youth facilities and for provincial and federal sentences. Findings There are 72 facilities in the inventory. In most, women are co-located with men. Responsibility for health varies by jurisdiction. Few sites have mother-child programmes. Distance to maternity services varies from 1 to 132 km. Research limitations/implications This paper did not include police lock-up, courthouse cells or involuntary psychiatric units in the inventory. Information is unavailable regarding trans and non-binary persons, a priority for future work. Access to maternity hospital services is but one critical question regarding reproductive care. Maintenance of the database is challenging. Originality/value Incarcerated women are an invisible population. The inventory is the first of its kind and is a useful tool to support sex and gender and health research across jurisdictions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".