Indigenous Women in a Colonial Legal Framework: An Intersectional Analysis of the British Columbia Human Rights Tribunal
Bibliographic record
Abstract
The British Columbia Human Rights Tribunal is a space to heal and assign reparations for discriminatory action. But before the reparations can occur, the harm must be verified. To do this, the onus is on the potential victim of discrimination, the complainant, to prove a correlation between their ‘characteristics’ and the occurrence of discrimination. The format of the British Columbia Human Rights Tribunal (BC HRT), which operates on specific lines of discrimination and tackles instances of discrimination based on parcelled out categories, does not have a framework that allows for an intersectional analysis. As a result of this framework, the BC HRT cannot look at the whole picture and must instead fit narratives into the framework of colonial law, in which the whole experience is parcelled and judged. Looking at 21 cases brought to the BC HRT by Indigenous women complainants since 2015, I examine how intersecting lines of oppression are managed and approached by the BC HRT. I find that the format of the BC HRT is not conceptualizing discrimination as experienced by people with complex intersectional identities. Instead the HRT is forcing the complainants to parcel their experience into clear lines which serves to destabilize and make illegitimate the argument brought by the complainant.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.035 | 0.035 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".