Capacity building of the Australian Aboriginal and Torres Strait Islander health researcher workforce: a narrative review
Bibliographic record
Abstract
BACKGROUND: This paper provides a narrative review that scopes and integrates the literature on the development and strengthening of the Australian Aboriginal and Torres Strait Islander health researcher workforce. The health researcher workforce is a critical, and oft overlooked, element in the health workforce, where the focus is usually on the clinical occupations and capabilities. Support and development of the Australian Aboriginal and Torres Strait Islander health researcher workforce is necessary to realise more effective health policies, a more robust wider health workforce, and evidence-led clinical care. This holds true internationally. It is critical to identify what approaches have resulted in increased numbers of Aboriginal and Torres Strait Islander people in health research, stronger local community partnerships with universities and industry, and research excellence and have contributed to evidence-led health workforce development strategies. METHODS: The search was for peer-reviewed journal articles between 2000 and early 2018 on capacity building of the Aboriginal and Torres Strait Islander health researcher workforce. Databases searched were CINAHL (EBSCO), PubMed, PsychINFO, LIt.search, and Google Scholar, combined with manual searches of select journals and citations in the grey literature. A coding scheme was developed to scan research coverage of various dimensions of health research capacity building. RESULTS: Twenty-four articles were identified. Eight focused on strengthening research capabilities of community members. A recurrent finding was the high research productivity of Aboriginal and Torres Strait Islander health researchers and strong interest in furthering research that makes a substantive contribution to community well-being. Action-based principles were derived from synthesis of the findings. Generally, research capacity building led to numerous gains in workforce development and improving health systems. CONCLUSIONS: There is a shortage of literature on health researcher workforce capacity building. National-level research on capacity building strategies is needed to support the continued success and sustainability of the Australian Aboriginal and Torres Strait Islander health researcher workforce. This research needs to build on the strengths of Aboriginal and Torres Strait Islander researchers. It also needs to identify clear and robust pathways to careers and stable employment in the health workforce, and health researcher workforce more specifically. This need is evident in all settler colonial nations (e.g. Canada, United States of America, New Zealand), and principles can be applied more broadly to other minoritised populations.
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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 | 0.021 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 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".