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Record W2166227902 · doi:10.1215/03616878-1597448

Reform and the Politics of Hybridization in Mature Health Care States

2012· article· en· W2166227902 on OpenAlexaffabout
Carolyn Hughes Tuohy

Bibliographic record

VenueJournal of Health Politics Policy and Law · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRetrenchmentPoliticsPublic administrationHealth care reformAccountabilityMonopolyHealth carePolitical scienceHealth policyPolitical economySociologyEconomic growthEconomicsMarket economyLaw

Abstract

fetched live from OpenAlex

This article examines the cases of three health care states -- two of which (Britain and the Netherlands) have undergone major policy reform and one of which (Canada) has experienced only marginal adjustments. The British and Dutch reforms have variously altered the balance of power, the mix of instruments of control, and the organizing principles. As a result, mature systems representing the ideal-typical health care state categories of national health systems and social insurance (Britain and the Netherlands, respectively) were transformed into distinctive national hybrids. These processes have involved a politics of redesign that differs from the politics of earlier phases of establishment and retrenchment. In particular, the redesign phase is marked by the activity of institutional entrepreneurs who exploit specific opportunities afforded by public programs to combine public and private resources in innovative organizational arrangements. Canada stands as a counterpoint: no window of opportunity for major change occurred, and the bilateral monopoly created by its prototypical single-payer model provided few footholds for entrepreneurial activity. The increased significance of institutional entrepreneurs gives greater urgency to one of the central projects of health policy: the design of accountability frameworks to allow for an assessment of performance against objectives.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.707
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.036
GPT teacher head0.325
Teacher spread0.289 · 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.

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

Citations42
Published2012
Admission routes2
Has abstractyes

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