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Record W4392922444 · doi:10.32799/ijih.v19i1.41293

Could Adequate and More Appropriate Housing for Aboriginal and Torres Strait Islander People in New South Wales, Australia, Reduce the Risk of Poorer Health Outcomes?

2024· article· en· W4392922444 on OpenAlexvenueno aff
Michael Doyle, Lisa Jackson Pulver, Samuel Harley, Ian Ring, Emma S. McBryde

Bibliographic record

VenueInternational Journal of Indigenous Health · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersMedical Research Council
KeywordsGeographyEnvironmental planningFisheryEnvironmental protectionEnvironmental healthPolitical scienceMedicineBiology

Abstract

fetched live from OpenAlex

Objective: Indigenous Australians are estimated to be 3.7 times more likely to be living in overcrowded conditions and are more likely to have poorer health outcomes. To investigate correlations between housing, health and age of death, we used data from the Public Health Information Development Unit (PHIDU) on the 105 Indigenous Areas (IAREs) within New South Wales (NSW). Methods: Univariant and multivariant linear regression analysis of the Public Health Information Development Unit (PHIDU) database. Results: Our results indicate that for every 1% increase in crowded households in an IARE, avoidable hospital admissions increased by 130 cases per 100,000. Conclusion: We conclude that this finding is consistent with the view that decreased overcrowding could improve the health of Aboriginal people in NSW. Implications for public health: Increased housing availability could reduce the demand for health services, including public hospitals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.042
GPT teacher head0.426
Teacher spread0.385 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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