Addressing Institutional Racism Against Aboriginal and Torres Strait Islanders of Australia in Mainstream Health Services: Insights From Aboriginal Community Controlled Health Services
Bibliographic record
Abstract
With long colonial histories, Aboriginal and Torres Strait Islander Peoples in Australia experience lower life expectancy and a higher burden of illness. To this day, Indigenous Peoples experience interpersonal, systemic, and institutional racism in the mainstream public health system of Australia, leading to the under- use of mainstream health services and resulting in many Indigenous Australians living in a state of persistent crisis. Extreme and unacceptable levels of institutional racism have been identified in the hospitals and health services of Queensland, Australia, using the Marrie Institutional Racism Matrix (MIRM), an evidence-based assessment tool for identifying, measuring, and monitoring racism in institutional settings. This paper aims to identify ways to address institutional racism against Indigenous Peoples in the health care sector. Specifically, using publicly available documents, a case study analysis of the Institute for Urban Indigenous Health (IUIH), a network of Aboriginal Community Controlled Health Services, is conducted using the MIRM as a guide. The conclusion is that the IUIH actively works to address institutional racism by (a) including Indigenous people in key decision-making processes and structures; (b) undertaking numerous community engagement strategies; (c) building partnerships within and outside the health sector to address the social determinants of health; and (d) working in ways that align with Indigenous ways of being and doing. It is argued that mainstream health services need to be aware of institutional racism and learn from the approaches of Indigenous-led organizations to create institutions that are inclusive of Indigenous members of society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".