Programs supporting incarcerated and previously incarcerated indigenous peoples: a scoping review protocol
Bibliographic record
Abstract
The overincarceration of Indigenous peoples and its impacts on individual and community health is a growing concern across Canada and the United States. Federally run Healing Lodges in Canada are an example of support services for incarcerated and previously incarcerated Indigenous peoples to reintegrate into community and support their healing journey. However, there is a need to synthesise research which investigates these programmes. We report a protocol for a scoping review that is guided by the following research question: What is known about culturally informed programmes and services available to incarcerated and previously incarcerated Indigenous peoples in Canada and the US? This scoping review will follow guidelines published by the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. This review will only identify programmes that are guided by Indigenous ways of being and knowing in order to best serve Indigenous communities and our community partners. The results of this review will support the development of programmes that are necessary for understanding and addressing the diverse needs of incarcerated and previously incarcerated Indigenous peoples.
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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 | 0.119 | 0.100 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.082 | 0.017 |
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".