Engaging a Human Rights Based Approach to the Murdered and Missing Indigenous Women and Girls Inquiry
Bibliographic record
Abstract
This article argues that the National Inquiry into Missing and Murdered Indigenous Women and Girls should engage a human rights based approach when analyzing the systemic causes of violence and making recommendations. Such an approach includes using international human rights norms to evaluate and recommend changes to the laws that failed to protect, and in some cases contributed to, murdered and missing Indigenous women and girls. Such an approach would also include international human rights principles such as Canada’s duty of due diligence to prevent, investigate, prosecute, punish, and compensate for murdered and missing Indigenous women and girls. A human rights based approach keeps Indigenous women’s needs at the center of the Inquiry. This article focusses on three instruments that have particular relevance to murdered and missing Indigenous women and girls: the Convention against Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment , the International Convention on the Rights of the Child , and the International Convention for the Protection of All Persons from Enforced Disappearance . The goal is to highlight the broad range of human rights protections that should inform a human rights based approach to the Inquiry.
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 | 0.023 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.075 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".