Community‐based social care models for indigenous people with disability: A scoping review of scholarly and policy literature
Bibliographic record
Abstract
Disability is experienced and understood by Indigenous people internationally in distinct ways from other populations, requiring different approaches in disability services. Furthermore, Indigenous populations access disability services at low rates. In response, policymakers, service providers and Indigenous organisations have developed specific models of care for Indigenous people with disability. Social care services, comprising personal care, transport and social activities, can support Indigenous people with disability to live with their families and in their communities. However, little is known about the range of social care models for Indigenous people with disability. To inform policy and practice, we conducted a scoping review of community-based models of social care designed to meet the needs of Indigenous peoples in Australia, Aotearoa New Zealand, Canada and the United States. Our methods were informed by best practice scoping review principles and a collaborative approach that centred Indigenous voices within research appraisal and project governance processes. Literature searches (conducted March-April 2021) yielded 25 results reporting on 10 models of care. We identified two over-arching themes (funding and governance arrangements; service delivery design) that encompass nine key characteristics of the included models. Our analysis shows promising practice in contextually relevant place-based social activity programs, support and remuneration for family carers and workforce strategies that integrate Indigenous staff roles with kinship relationships and social roles. While more research and evaluation are needed, disability funding bodies and service systems that facilitate these areas of promising practice may improve the accessibility of social care for 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 | 0.034 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.018 | 0.022 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".