Exploring the impact of mainstream and culturally specific programs for Indigenous women’s healing in a Quebec women’s provincial prison
Bibliographic record
Abstract
Indigenous women are the fastest growing offender population in Canada. The largest increase in Indigenous women’s admissions to provincial/territorial custody between 2007 and 2018 occurred in Quebec, with a 219% increase (Statistics Canada, 2019). These statistics, coupled with a lack of localized (e.g., province-specific) knowledge regarding circumstances of Indigenous women, highlight an urgent need for identification and understanding of services needed to support Indigenous women in prison. \n \nThe purpose of this study was to explore Indigenous women’s perspectives on their participation in culturally specific and mainstream programs in a Quebec provincial women’s prison: Établissement de détention Leclerc de Laval. The study’s approach blended Indigenous and Western approaches to data collection and employed a relational ethics process for collaboratively building the study with women who participated. As a part of the study researchers and Indigenous women participated in three-day medicine bag workshops facilitated by Indigenous Elders and healers. Arts-based methods including storytelling, creation of medicine bags, sharing circles, and Sketchnotes (arts-based note taking; Rhodes, 2013) were used to collect data during workshops. The women also took part in optional interviews following workshops to share individualized insights regarding the impacts of the workshop and other correctional programs on their lives. \n \nThis thesis presents findings from five workshops and 31 interviews regarding the role of culturally specific and mainstream prison programs in supporting Indigenous women’s healing from the women’s perspectives. It further presents assets and limitations of available programs from the women’s perspectives. Program and policy implications of the findings are also presented.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".