The commercial determinants of Indigenous health and well-being: a systematic scoping review
Bibliographic record
Abstract
INTRODUCTION: Health inequity within Indigenous populations is widespread and underpinned by colonialism, dispossession and oppression. Social and cultural determinants of Indigenous health and well-being are well described. Despite emerging literature on the commercial determinants of health, the health and well-being impacts of commercial activities for Indigenous populations is not well understood. We aimed to identify, map and synthesise the available evidence on the commercial determinants of Indigenous health and well-being. METHODS: Five academic databases (MEDLINE Complete, Global Health APAPsycInfo, Environment Complete and Business Source Complete) and grey literature (Australian Indigenous HealthInfoNet, Google Scholar, Google) were systematically searched for articles describing commercial industry activities that may influence health and well-being for Indigenous peoples in high-income countries. Data were extracted by Indigenous and non-Indigenous researchers and narratively synthesised. RESULTS: 56 articles from the USA, Canada, Australia, New Zealand, Norway and Sweden were included, 11 of which were editorials/commentaries. The activities of the extractive (mining), tobacco, food and beverage, pharmaceutical, alcohol and gambling industries were reported to impact Indigenous populations. Forty-six articles reported health-harming commercial practices, including exploitation of Indigenous land, marketing, lobbying and corporate social responsibility activities. Eight articles reported positive commercial industry activities that may reinforce cultural expression, cultural continuity and Indigenous self-determination. Few articles reported Indigenous involvement across the study design and implementation. CONCLUSION: Commercial industry activities contribute to health and well-being outcomes of Indigenous populations. Actions to reduce the harmful impacts of commercial activities on Indigenous health and well-being and future empirical research on the commercial determinants of Indigenous health, should be Indigenous led or designed in collaboration with 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 | 0.012 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".