Can Reconciliation Be Compelled? Transnational Advocacy and the Indigenous–Canada Relationship
Bibliographic record
Abstract
Through an examination of transnational advocacy and the Indigenous–Canada relationship, this article advances a compliance model of reconciliation to suggest that reconciliation might be compelled through pressure upon states to comply with their human rights obligations. Drawing upon constructivism, conflict resolution theory, and social psychology, the article proposes that compliance and reconciliation converge as a result of behavioral adjustment and the internalization of values through enforced performance. The article uses four examples for illustration: (1) challenges at the UN Human Rights Committee against gender discrimination in the Indian Act, (2) Canada's belated endorsement in 2010 of the United Nations Declaration of the Rights of Indigenous Peoples, (3) insider–outsider pressure that Canada comply with its human rights obligations with respect to its missing and murdered indigenous women and girls, and (4) the Hul'qumi'num Treaty Group's land claim petition before the Inter‐American Commission for Human Rights. The article concludes that transnational advocacy in the Indigenous–Canada context has had slight to moderate effect in making reconciliation happen.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.026 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".