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Record W4379882442 · doi:10.1111/issr.12323

The role of mutuals and community‐based insurance in social health protection systems: International experience on delegated functions

2023· article· en· W4379882442 on OpenAlexaff
Mariétou Niang, Émilie Gélinas, Oumar Mallé Samb, Lou Tessier, Mathilde Mailfert, Aurore Iradukunda, Olivier Guérin, Valéry Ridde

Bibliographic record

VenueInternational Social Security Review · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec à Rimouski
Fundersnot available
KeywordsDelegationSocial protectionContext (archaeology)Social securityPoliticsAuthorizationPolitical scienceBusinessPublic administrationEconomic growthEconomicsComputer securityGeographyLaw

Abstract

fetched live from OpenAlex

Abstract The institutional architecture for the provision of social health protection varies across countries, as do the actors and organizations involved. In some countries, mutual benefit societies and community‐based health insurance organizations (CBHI) play a role in this area. In the 1990s, these were promoted particularly as a means of extending social security coverage, especially in sub‐Saharan Africa. In the current context, the adoption of the 2030 Agenda for sustainable development, as well as renewed political will to realize universal coverage, has led to a questioning of the role of mutuals/CBHI. However, the literature on the roles they play in national social security systems remains limited. For this scoping review, 49 documents were analysed, covering 18 countries worldwide, focused on the delegation of functions to mutuals/CBHI in national social health protection systems. The results reveal the dynamics of the delegation of functions within social protection systems over time and their implementation processes. These provide areas for reflection that can inform policy processes.

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)0.032
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.014
Scholarly communication0.0070.006
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.081
GPT teacher head0.335
Teacher spread0.254 · 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 designObservational
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

Citations2
Published2023
Admission routes1
Has abstractyes

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