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The 2022 restructure of Aotearoa New Zealand's health system: Will it succeed in advancing equity where others have failed?

2023· article· en· W4378832535 on OpenAlex
Tim Tenbensel, Jacqueline Cumming, Esther Willing

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Policy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsInstitute of Health Services and Policy Research
FundersEuropean Observatory on Health Systems and Policies
KeywordsAotearoaTreaty of WaitangiEconomic growthWorkforceHealth policyPopulation healthHealth equityPopulationGovernment (linguistics)Equity (law)BusinessSocial determinants of healthContext (archaeology)IndigenousPolitical scienceHealth carePublic relationsMedicineEnvironmental healthGeographyEconomics

Abstract

fetched live from OpenAlex

Aotearoa New Zealand has restructured its health system with the objective of addressing inequitable access to health services and inequitable health outcomes, particularly those affecting the indigenous Māori population. In July 2022, two new organisations were created to centralise planning, funding and provision responsibilities for publicly funded health services in Aotearoa New Zealand. Health New Zealand and the Māori Health Authority have been created to drive transformational change within the national health system and monitor and improve the health and wellbeing of Māori. At the local level, new Localities are to be formed with the aim of integrating services between government and non-government health and social services providers, while incorporating local Māori and local communities in co-design of services. These changes will be of interest to those in many other countries who are grappling with their own colonial histories and struggling to provide health services in ways that are equitable and contribute to positive health outcomes for their whole population. Although key aspects of the reforms are well supported within the health sector, the ambitious scope and timing of their introduction in the context of the COVID-19 pandemic and health workforce shortages can be expected to generate significant implementation challenges.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.477
Teacher spread0.429 · 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