“An equitable right to be compensated”: The Dispossession of the Aboriginal Peoples of Quebec and the Emergence of a New Legal Rationale (1760–1860)
Bibliographic record
Abstract
Abstract: At the conquest of New France, the British had already built a long tradition of purchasing Aboriginal land. This policy, made official in the Royal Proclamation of 1763, was implemented in an extensive portion of the Canadian territory, but not in the Saint Lawrence Valley, heart of the former French empire in America, and what is now the province of Quebec. The British, followed by the Canadian government, adopted a policy of unilateral land appropriation in that area, dispossessing the Aboriginals without reliance on a treaty system. This particularity of the Indian land policy in Quebec has given rise to divergent interpretations that rest on the same implicit premise that a structuring legal framework existed, which, when reconstituted, gives meaning to history, either by legitimizing the unilateral dispossession process or by stigmatizing it. This article attempts to locate the process of dispossessing Aboriginal land outside the normative framework imposed by the law. The objective is not to identify a standard to explain why the British did not conclude treaties, but rather to follow a process of legal standardization, in which colonial practice is inscribed, through trial and error, detours, shifts in meaning, and improvisations into a legitimizing framework.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".