Is the Sky the Limit? Following the Trajectory of Aboriginal Legal Rights in Resource Development
Bibliographic record
Abstract
There has been a tremendous debate in recent years about the impact of a string of court decisions recognizing Aboriginal rights in Canada. What do they mean for Aboriginal prosperity? What do they mean for the natural resource sector? Are Aboriginal communities in effect gaining a veto over development? And will this apparent string of legal victories continue indefinitely?The legal developments of recent years have been welcome, in that they constitute long-overdue recognition of Aboriginal rights in the courts, and hard-won victories in cases that spanned many years. Indeed, one thing is perfectly clear, Aboriginal peoples are vital partners in development projects that affect their communities and traditional lands, and no one can deny they have a seat at the table with government and industry. But a lack of clarity about the meaning of key decisions in contexts like Aboriginal title and the duty to consult will cause uncertainty for project proponents, could create conflict with Aboriginal communities, and might in fact deny Aboriginal communities some of the economic benefits they stand to gain.This paper analyzes the recent history of Canadian court decisions on Aboriginal rights, particularly focusing on the last five years, examining some of these themes and the uncertain prospects for further gains for Aboriginal communities through litigation.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.032 | 0.074 |
| Scholarly communication | 0.022 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.011 |
| 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".