Indigenous child welfare in British Columbia : training and practice shifts in child protection
Bibliographic record
Abstract
In the Province of British Columbia there is an alarming over-representation of\nIndigenous children in the foster care system. An extensive literature review revealed there are\npolicy and practice changes designed to address this problem. There are currently 24 Delegated\nAboriginal Agencies throughout the province, each with varying levels of delegated authority. As\nwell there are frameworks of practice, such as the Aboriginal Policy and Practice Framework\ncreated by the Ministry of Children and Family Development, the Nlaka’pamux Framework of\nPractice created by Scw’exmx Child and Family Services Society and the Syilx Child and\nFamily Plan created by Okanagan Nation Alliance. These frameworks encourage child welfare\npractices that are more aligned with and culturally sensitive to Indigenous community(s) being\nserved. There are also legislative changes such as Bill C-92 which was passed in June 2019; this\nis a Federal Act with the respect to First Nations, Inuit and Metis children, youth and family that\nencourages increased Indigenous jurisdiction over child welfare for Indigenous communities.\nThe findings are that although there have been policy and practice changes made there remains\nto be an over-representation of Indigenous children in Foster Care and in fact in some cases the\nnumber of Indigenous children has risen.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".