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Record W3118808661 · doi:10.1093/heapol/czaa080

Self-undermining policy feedback and the creation of National Health Insurance in Ghana

2020· article· en· W3118808661 on OpenAlexaff
Ishmael Wireko, Daniel Béland, Michael Kpessa-Whyte

Bibliographic record

VenueHealth Policy and Planning · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsMcGill UniversityGovernment of Saskatchewan
Fundersnot available
KeywordsScholarshipTransformative learningContext (archaeology)Health policyPublic policyHealth careUnintended consequencesPublic economicsEconomicsPublic administrationPolitical scienceEconomic growthSociologyLaw

Abstract

fetched live from OpenAlex

Contributing to the ongoing debate about policy feedback in comparative public policy research, this article examines the evolution of healthcare financing policy in Ghana. More specifically, this article investigates the shift in healthcare financing from full cost recovery, known as 'cash-and-carry', to a nation-wide public health insurance policy called the National Health Insurance Scheme (NHIS). It argues that unintended, self-undermining feedback effects from the existing health policy constrained the menu of options available to reformers, while simultaneously opening a window of opportunity for transformative policy change. The study advances the current public policy scholarship by showing how the interaction between policy feedbacks and other factors-particularly ideas and electoral pressures-can bring about path-departing policy change. Given the dearth of scholarship on self-undermining policy feedback effects in the Global South, this contribution's originality lies in its application of the novel theory to the sub-Saharan African context.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.777
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.086
GPT teacher head0.435
Teacher spread0.348 · 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 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

Citations5
Published2020
Admission routes1
Has abstractyes

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