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Record W2808823227 · doi:10.1177/0020731418779508

Performance-based Financing in Africa: Time to Test Measures for Equity

2018· article· en· W2808823227 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal of Health Services · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversité de Montréal
FundersInstitute of Population and Public HealthCanadian Institutes of Health Research
KeywordsEquity (law)Psychological interventionHealth care financingEconomicsFinancePurchasingHealth carePublic economicsHealth equityBusinessDeveloping countryDevelopment economicsEconomic growthPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Over the past 15 years, hundreds of millions of dollars have been invested in reforms founded on performance-based financing (PBF) in low- and middle-income countries. While evidence on its effectiveness and efficiency is still controversial, there appears to be an emerging consensus that equity has not been adequately considered. In this article, we show how PBF-type interventions in Africa have not sufficiently taken into account equity of access to care for the worst-off and their financial protection. In reviewing the history of health reforms in Africa, we show that this omission is nothing new. We suggest that strategic purchasing and PBF-type actions would benefit from being implemented in ways that promote equity and the financial protection of populations in Africa. Without such a reorientation of reforms, it will be impossible to achieve universal health coverage by 2030.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.080
GPT teacher head0.330
Teacher spread0.251 · 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