The disappointing remedy? Damages as a remedy for violations of human rights
Bibliographic record
Abstract
After initial optimism, damages have become a disappointing remedy for human rights violations in Canada, New Zealand, South Africa, the United Kingdom, and the United States. Part I of this article relates this disappointment to the modest nature of most awards and the continued impact of qualified and absolute immunities. Part II argues that the answer is not, as some have suggested, to return to tort principles but, rather, to look to public law principles, including international law principles of state responsibility. This allows damages to be placed in the perspective of the state’s obligations to comply with human rights and the availability of alternative and sometimes stronger remedies. A public law approach also allows principles of proportionality to discipline and structure the exercise of remedial discretion. Part III situates damages within a two-track approach to remedies in both domestic and supranational law. Under this approach, courts will play the dominant role in providing remedies including damages to recognize past violations but play a more dialogic role with respect to encouraging states to prevent similar violations in the future.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".