An Anti-Oppression (AO) Framework for Child Welfare in Ontario, Canada: Possibilities for Systemic Change
Bibliographic record
Abstract
This article presents the development and potential use of a method of bringing systemic change to a mandated institution such as the Children's Aid Society in Ontario, Canada, while taking into account the many challenges to realising progressive change in child welfare practice. The authors explore whether systemic change is possible given contemporary child welfare's manifold standardised procedures, including risk and safety assessment and legal reporting requirements. The second author discusses his viewpoint and experiences as a member of the Anti-Oppression Roundtable, and outlines its work as a catalyst for critical review of practices and processes. The authors describe the genesis and development of the Anti-Oppression Framework for Child Welfare in Ontario and provide an example to show how it can be used as an important strategic tool to try to bring systemic change to the child welfare system. The article concludes by reviewing some of the challenges in choosing to take this path of implementing an AO framework in the face of increasing criticism directed to child welfare agencies.
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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 | 0.016 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.037 | 0.070 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".