IMMEDIATE RESPONSE: ADDRESSING ANTI-NATIVE AND ANTI-BLACK RACISM IN CHILD WELFARE
Bibliographic record
Abstract
<p>Anti-oppression emerged in the 1990s as a perspective for challenging inequalities and accommodating diversity within the field of social work, including child welfare in Canada. Using the concepts of white supremacy, anti-Black, and anti-Native racism in conjunction with the notion of the exalted national subject (Thobani, 2007), we contend that any understanding of the overrepresentation of Aboriginal and Black children in the care of child welfare services must be located within the wider narrative of white supremacy that has underpinned the formation of the post-war welfare state. This overrepresentation highlights the need to shift from anti-oppression to critical race feminism and anti-colonialism perspectives in order to address more effectively anti-Black and anti-Native racism and the economy of child welfare.</p>
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.050 | 0.045 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".