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Record W4399717248 · doi:10.1080/01559982.2024.2364955

Patient empowerment in public healthcare funding system reform: a power network perspective

2024· article· en· W4399717248 on OpenAlexaff
Aziza Laguecir, Christopher S. Chapman, Florian Gebreiter, Célia Lemaire

Bibliographic record

VenueAccounting Forum · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDisadvantagedHealth careEmpowermentPosition (finance)Power (physics)Health care reformBusinessPublic relationsPerspective (graphical)SociologyEconomic growthPolitical scienceEconomicsHealth policyFinance

Abstract

fetched live from OpenAlex

This paper examines a reform of the French healthcare system that aimed to empower patients and improve their access to care but led to various adverse consequences for patients. Specifically, already socio-economically disadvantaged groups of patients found their positions becoming even more precarious. Conceptually, we draw upon Emerson’s power dependence theory and find that, rather than empowering patients, the reform resulted in private health insurance providers emerging as critical actors and primary beneficiaries of power network changes. This healthcare system-level analysis highlights the need for patients to be the direct focus of healthcare system reform and the importance of considering their position within the power network for understanding reform outcomes. This attention to the power network adds to the extant theorisation on the effects of funding mechanism reform on the nature of patient empowerment and access to healthcare.

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)0.010
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.016
Scholarly communication0.0060.010
Open science0.0010.005
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.037
GPT teacher head0.274
Teacher spread0.237 · 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 designQualitative
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

Citations7
Published2024
Admission routes1
Has abstractyes

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