Sweating it Out: Facilitating Corrections and Parole in Canada Through Aboriginal Spiritual Healing
Bibliographic record
Abstract
Aboriginal peoples continue to be subjected to drastic over-incarceration. Much of the existing literature explores contemporary adaptations of Aboriginal justice traditions that resemble restorative justice as a solution. There is by comparison a lack of literature that considers searching for solutions during the correctional phase of the justice system, after Aboriginal persons have already been convicted and imprisoned. The objective of this paper is to explore a number of reforms in order to better facilitate rehabilitation, reintegration, and parole for Aboriginal inmates. One is to invest greater resources into culturally sensitive programming that emphasizes spiritual healing for Aboriginal inmates. This is premised on the theme of “spend now, save later” with the idea that increasing the chances for Aboriginal re-integration may represent the better long term investment than simply warehousing large numbers of Aboriginal inmates year after year. Another problem is that many Aboriginal inmates are classified as higher security risks, which results in them being cut off from needed programming. The suggestion here is that criminal history as a static factor for determining security classifications may have little predictive value for the actual security risk posed by Aboriginal inmates, and therefore should be de-emphasized. Correctional Services of Canada should seriously consider developing an Aboriginal-specific classification scale that de-emphasizes criminal history, and emphasizes instead offender participation in culturally appropriate programs and spiritual healing, and behavioural progress while in prison. Risk assessment to re-offend for purposes of granting parole may also represent a form of systemic discrimination since criminal history represents a static factor that encumbers parole for many Aboriginal inmates. Risk assessment should instead emphasize dynamic risk factors by assessing Aboriginal participation in culturally appropriate programming, and attendant behaviourial progress while in prison. The difficult issue of Aboriginal gang activity can perhaps be dealt with through a more flexible system of risk assessment that gauges a willingness to reform and dissociate from the gang lifestyle rather than require Aboriginal inmates to endure nearly permanent penalties for past involvement. Finally, the paper will suggest that it is possible to overcome the political obstacles to implementing these reforms and obtain a political mandate to pursue them after the public is made aware of the benefits they offer.
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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 | 0.002 | 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 | 0.025 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".