Aboriginal healing lodges in Canada: still going strong? Still worth implementing in the USA?
Bibliographic record
Abstract
Aboriginal healing lodges are a means of accommodating Aboriginal customary law in the Canadian correctional system by providing holistic culturally appropriate services to Aboriginal offenders. They combine Aboriginal healing practices with non-Aboriginal correctional practices as determined by Canadian law and Correctional Service Canada policy. Some are operated by Aboriginal Nations/organizations and some by the Correctional Service Canada. The co-optation of healing lodges through federal correctional policy is contrary to the intent of Canadian law. This combination of state disregard for the law and cultural appropriation provides lessons for Indigenous American groups contemplating more involvement in correctional services. In the USA, the Tribal Law and Order Act of 2010 and policies regarding private prisons may help or threaten the implementation of healing lodges. In both countries, state laws and policies seem to be subverting Indigenous sovereignty but this makes healing lodges even more valuable. Just as healing lodges could enhance community capacity building in Canada, Indigenous American healing lodges could assist with community capacity-building, as well as reducing recidivism rates. Healing lodges thereby have the potential to increase indigenous sovereignty in both countries, political climate permitting.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".