Supporting Indigenous Kinship Caregivers
Bibliographic record
Abstract
This article reports on data shared by Indigenous kinship caregivers in a larger study on kinship care conducted in British Columbia (BC), Canada. There is a significant amount of research on kinship caregivers, but little of it focuses specifically on Indigenous carers. The findings presented here add to that small but growing body of literature. The larger study was done in partnership between Parent Support Services of BC (PSS), a charitable non-profit organization that supports kinship caregivers in BC, and the University of Northern BC (UNBC) (Burke et al. Citation2022). Data for this secondary analysis arose from surveys that focused on the experiences and needs of kinship caregivers. The findings suggest that supports should be delivered in ways that acknowledge the heterogeneity of Indigenous peoples and respond to individual needs, that programs should be designed in ways that support caregivers’ efforts to heal from the impacts of colonialism, and that policies designed for Indigenous kinship carers should be evaluated to ensure their efficacy. Suggestions regarding future research include research that focusses on the optimism that exists among kinship caregivers despite the challenges they face, research on non-grandparent caregivers, and research that is designed to be culturally sensitive 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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".