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Record W3024585045 · doi:10.21149/10938

Sistema de salud de Haití

2020· article· es· W3024585045 on OpenAlexaff
Fato Fene, Octavio Gómez‐Dantés, James Lachaud

Bibliographic record

VenueSalud Pública de México · 2020
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

El sistema de salud haitiano se conforma por un sector público y un sector privado. El primero está compuesto por el Ministerio de Salud Pública y Población (MSPP) y la Caja de Seguro de Accidentes de Trabajo, Enfermedades y Maternidad (Ofatma). El sector privado incluye a los seguros y prestadores de servicios de salud privados. El MSPP ofrece servicios básicos a la población no asalariada (95% de la población total), mientras que la Ofatma ofrece seguros contra accidentes de trabajo, enfermedades y maternidad a los trabajadores del sector formal privado y público. El gasto total en salud en Haití representó 5.4% del producto interno bruto en 2016 y el gasto en salud per cápita fue de 38 dólares estadunidenses. Hay una enorme dependencia de los recursos externos. El MSPP es el responsable de la mayor parte de las actividades de rectoría. El mayor reto que enfrenta el sistema de salud de Haití es ofrecer servicios integrales de salud con protección financiera a toda la población. Esta meta no podrá alcanzarse sin mayores recursos financieros, sobre todo públicos, y sin un importante esfuerzo de fortalecimiento institucional.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0390.010

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 head0.048
GPT teacher head0.260
Teacher spread0.212 · 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 designNot applicable
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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