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Record W4382918323 · doi:10.1002/hpja.775

Celebrating Aboriginal and Torres Strait Islander voices in Australian health promotion

2023· editorial· en· W4382918323 on OpenAlexaboutno aff
James A. Smith, Courtney Ryder, Bep Uink, Jenni Judd, Michelle Dickson, Gemma Crawford, Le Smith, Vicki Wade

Bibliographic record

VenueHealth Promotion Journal of Australia · 2023
Typeeditorial
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsPopulation healthHealth economicsHealth promotionPublic healthCommunity healthPromotion (chess)MedicinePublishingProject commissioningEconomic growthPolitical scienceMedia studiesNursingSociologyLawEconomics

Abstract

fetched live from OpenAlex

In this editorial, in parallel with NAIDOC Week 2023, we celebrate Aboriginal and Torres Strait Islander voices in Australian health promotion efforts.We focus on tangible actions of the Australian Health Promotion Association (AHPA ® ) and Health Promotion Journal of Australia (HPJA) that have enabled this vision.But first, it is helpful to understand why this is important.

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)0.011
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0100.004
Open science0.0020.004
Research integrity0.0060.013
Insufficient payload (model declined to judge)0.0070.002

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 head0.056
GPT teacher head0.437
Teacher spread0.380 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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