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Record W4306294652 · doi:10.18584/iipj.2022.13.2.14012

Why are Indigenous Affairs Policies Framed in ways that Undermine Indigenous Health and Equity?

2022· article· en· W4306294652 on OpenAlexvenueaboutno aff
Toby Freeman, Belinda Townsend, Tamara Mackean, Connie Musolino, Sharon Friel, Dennis McDermott, Fran Baum

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsIndigenousGovernment (linguistics)Equity (law)Health equityMetisSovereigntyPublic administrationPolitical scienceUnderpinningHealth policyColonialismEconomic growthSociologyHealth careLawPoliticsEconomics

Abstract

fetched live from OpenAlex

The 2007 Australian Northern Territory Emergency Response policy was harmful to the health of Aboriginal and Torres Strait Islander people. We thematically analysed 72 speech acts and reports from the three prominent perspectives: a Northern Territory government inquiry report, the Federal government, and an Aboriginal civil society coalition to examine how framings during the policy agenda setting phase constrained or supported scope for equitable health outcomes. The report authors and the coalition emphasised colonisation and other social determinants of Indigenous health. The Federal government used a discourse of pathology and white sovereignty. Our findings highlighted the need for Indigenous voice in policy making, and the need to address colonial assumptions underpinning policy framings to achieve Indigenous health equity.

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)0.036
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.037
Scholarly communication0.0160.011
Open science0.0020.008
Research integrity0.0040.006
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 head0.055
GPT teacher head0.379
Teacher spread0.324 · 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 designTheoretical or conceptual
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

Citations3
Published2022
Admission routes2
Has abstractyes

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