The Indigenous Child Removal System in Canada: An Examination of Legal Decision-making and Racial Bias
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This Indigenous child removal system in Canada has been in operation since the 1950s and has created unprecedented Indigenous child overrepresentation in the child welfare system. While five generations of residential schools and disastrous socio-economic conditions often warrant child welfare involvement, the statistics for Indigenous children in care are so disproportionate that we are called to examine key factors that have created and sustain the system. While history provides a contextual frame for these statistics, examining legislation and legal decision-making in Indigenous child welfare cases sheds light on how legal and racial factors contribute to ongoing Indigenous child removals from families and culture. This article is a call for the Indigenous child removal system to be overhauled and suggests that the recommendations of the Truth and Reconciliation Commission final report can guide us in how that can be achieved.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it