In what ways can Indigenous care providers, both relational and non-relational be adequately supported when caring for children in the British Columbia child welfare system?
Bibliographic record
Abstract
It is challenging in British Columbia to recruit and retain Indigenous caregivers and foster parents. The over representation of Indigenous children in care is overwhelming, as is the under representation of Indigenous caregivers. Issues associated with recruiting and retaining Indigenous caregivers are numerous. In part due to historical trauma of colonization, along with other multiple systemic issues, such as oppressive legislation and polices that resulted in poverty, homelessness and lack of professional support. This paper will explore how social services can acquire and retain more Indigenous caregivers. An analysis of the literature will be used to evaluate information and reflect an in-depth review, which will be explored with both feminist and Indigenous theories. An anti-oppressive and culturally competent framework was valuable for assessing social issues and systemic inequities of potential Indigenous caregivers. This in turn provides professionals with a better understanding as how to recruit and retain Indigenous caregivers and foster parents, by enhancing understanding of the complexities that are impactful to Indigenous peoples.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".