Redress through constitutional change: reimagining the Canada Round for its reparative potential
Bibliographic record
Abstract
The Canada Round was a period of megaconstitutional politics where many of the perennial topics of Canadian politics were viewed through a constitutional lens. This research analyzes the Canada Round of negotiations for its potential to act as a project in historical justice to address the state’s mistreatment of Indigenous peoples. By viewing constitutional change as a means of engaging in political redress, this research offers a corrective to understanding the dynamics of the Canada Round and provides an expanded understanding of redress to compensate for its limited and non-transformative nature in settler-colonial contexts by introducing the idea of redress constitutionalism. Through an analysis of the primary documents from the Canada Round, this research demonstrates that national Indigenous organizations—the Assembly of First Nations, the Métis National Council, the Inuit Tapirisat of Canada, and the Native Council of Canada—sought to employ constitutional change for its reparative potential to address long-standing injustices against Indigenous peoples in Canada caused or worsened by the constitution. Therefore, the failure to significantly renew the constitution was also a failure to significantly engage in redress, remedy their historical exclusion from decision making, and respond to the suppression of their self-determination.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.053 |
| Scholarly communication | 0.018 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".