Transitional Justice in Non-Transitional Societies: Canada and the Legacy of the Indian Residential School System
Bibliographic record
Abstract
The framework of transitional justice, originally devised to facilitate reconciliation in countries undergoing transitions from authoritarianism to democracy, is used with increasing frequency to respond to certain types of human rights violations against indigenous peoples. In some cases, transitional justice measures are employed in societies not undergoing regime transition. Transitional justice measures offer opportunities for re-inscribing the responsibility of states toward their indigenous populations, empowering indigenous communities, responding to indigenous demands to be heard, and rewriting history. Nevertheless, treating indigenous demands for justice as a matter of “human rights” is an ethically loaded project that may reinforce liberal (and neo-liberal) paradigms that indigenous peoples often reject. Whether transitional justice measures will serve primarily to legitimate the status quo between post-colonial states, settler societies, and Aboriginal peoples, or whether they will have transformational capacity, will depend in part on the political context in which they take place. The impact of such transitional justice measures as apologies, truth commissions, and reparations will be limited, or extended, by the wider policy environment in which they occur.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.046 | 0.016 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".