Highlighting two black families experience with Ontario's Child Welfare System
Bibliographic record
Abstract
Black children are entering child welfare system at a rate five times higher than that of the average Canadian population (Polanyi et al., 2014). There are approximately 539, 205 (8% of the population) Black individuals living in Ontario, yet Black children make up 41% of the children in the care of Children’s Aid Society (Polanyi et al., 2014). The disproportionate apprehension of marginalized children is not a new issue; it is only recently that child welfare organizations have acknowledged that this is an issue. This prompted some agencies to release disaggregated race-based data outlining racial disparities. This phenomenological qualitative research study intends to highlight the stories of two Black parents who have had an ongoing relationship with Ontario’s child welfare system. This research hopes to outline their similarities, differences and the intricate experiences. Their experiences will be examined through a critical lens guided by anti-black racism and critical race theory.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.042 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".