Bibliographic record
Abstract
These remedies involve the challenges of responding to the harms of colonialism and avoiding new neo-colonial harms. Part I stresses the importance of interim remedies to prevent irreparable harm to Indigenous rights. Courts should stop their tendency to discount pecuniary losses even while trying to off-set this with a more generous approach to non-pecuniary harms. Part II examines the duty to consult. It, like the South African practice of engagement, can result in consensual agreements but also authorize limits on rights, especially if no attempt is made to address inequality of bargaining power and respect Indigenous law. Part III argues that proportionality principles can be used to avoid allowing majoritarian and economic interests to weaken remedies. Following Article 40 of the United Nations Declaration on the Rights of Indigenous Peoples, the overall balance stage should be applied bi-jurally to respect both rights and Indigenous law including with respect to the environment. Part IV suggests that domestic and supra-national courts should focus on providing first-track remedies to prevent irreparable harm and compensate for past harm. They should employ a lighter and respectful touch that encourages bi-jural treaties as systemic remedies. Effective first-track remedies may make such agreements more likely.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".