Culture, cultural identity, and the role of culture in the rehabilitation of aboriginal offenders
Bibliographic record
Abstract
Aboriginal people are vastly over-represented in the Canadian Criminal Justice system and it is widely accepted that this is the result of colonization, assimilation, and continued marginalization of Aboriginal people (see Aboriginal Justice Inquiry, 1991; Perreault, 2009; Roach and Rudin, 2000). As part of the process of colonization and assimilation, colonizing agents purposely destroyed Aboriginal culture and traditional knowledge (Corrado et al, 2008; LaPrairie, 1998). However, many Aboriginal people are now attempting to recapture their traditional knowledge of healing in an effort to revitalize their communities. Traditional healing programs are being established in correctional facilities and offered as alternatives to Western-based rehabilitation programs. This paper, therefore, draws on the connection between traditional Aboriginal healing systems and cultural identity and rehabilitation. The question of how and why culture is important to identity and rehabilitation is explored by highlighting how culture can benefit the Aboriginal offender; particularly in the teaching and encouragement of traditional cultural values, beliefs and traditions, and in the establishment of self and cultural identity. Knowledge and understanding of Aboriginal culture and traditional healing may enhance rehabilitation by anchoring offenders to a history, culture, and identity that they have been deprived of. As a result, this major paper provides a critical review of the current literature and research about the state of culture-based rehabilitation programs for Aboriginal offenders in Canada.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".