The Complainant: The Canadian Human Rights Case on First Nations Child Welfare
Bibliographic record
Abstract
In February 2007, the First Nations Child and Family Caring Society of Canada and the Assembly of First Nations filed a complaint under the Canadian Human Rights Act alleging that the Government of Canada’s inequitable provision of child welfare services to 163,000 First Nations children, along with its flawed implementation of Jordan’s Principle, was discriminatory on the prohibited grounds of race and national ethnic origin. The case was highly contested. By the time the final arguments were heard in 2014, the Government of Canada had made eight unsuccessful attempts to get the case dismissed on technical grounds and breached the law on three occasions. On 26 January 2016, the Canadian Human Rights Tribunal substantiated the complaint and ordered the Canadian Government to cease its discriminatory conduct. This article describes this historic case from the perspective of the executive director of the complainant, the First Nations Child and Family Caring Society of Canada, highlighting access to justice issues for equality-seeking Indigenous groups, children, and civil society. Recommendations for reform are discussed.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Not applicable | low |
| gpt | Science and technology studies Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: yes | Theoretical or conceptual | low |
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.069 | 0.023 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".