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Comprehensive primary health care under neo-liberalism in Australia

2016· article· en· W2518777552 on OpenAlexaff
Fran Baum, Toby Freeman, David Sanders, Ronald Labonté, Angela Lawless, Sara Javanparast

Bibliographic record

VenueSocial Science & Medicine · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of OttawaInstitute of Population and Public Health
FundersNational Health and Medical Research Council
KeywordsGovernment (linguistics)Health careEconomic growthHealth policyHealth care reformHealth promotionPopulationPublic relationsPublic administrationProcurementPolitical scienceMedicineBusinessEconomicsEnvironmental healthMarketing

Abstract

fetched live from OpenAlex

This paper applies a critical analysis of the impact of neo-liberal driven management reform to examine changes in Australian primary health care (PHC) services over five years. The implementation of comprehensive approaches to primary health care (PHC) in seven services: five state-managed and two non-government organisations (NGOs) was tracked from 2009 to 2014. Two questions are addressed: 1) How did the ability of Australian PHC services to implement comprehensive PHC change over the period 2009-2014? 2) To what extent is the ability of the PHC services to implement comprehensive PHC shaped by neo-liberal health sector reform processes? The study reports on detailed tracking and observations of the changes and in-depth interviews with 63 health service managers and practitioners, and regional and central health executives. The documented changes were: in the state-managed services (although not the NGOs) less comprehensive service coverage and more focus on clinical services and integration with hospitals and much less development activity including community development, advocacy, intersectoral collaboration and attention to the social determinants. These changes were found to be associated with practices typical of neo-liberal health sector reform: considerable uncertainty, more directive managerial control, budget reductions and competitive tendering and an emphasis on outputs rather than health outcomes. We conclude that a focus on clinical service provision, while highly compatible with neo-liberal reforms, will not on its own produce the shifts in population disease patterns that would be required to reduce demand for health services and promote health. Comprehensive PHC is much better suited to that task.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.114
GPT teacher head0.493
Teacher spread0.379 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations95
Published2016
Admission routes1
Has abstractyes

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