MétaCan
Menu
Back to cohort

Cross country lessons sharing on practices, challenges and innovation in PHC revitalization and UHC implementation among 18 countries in the WHO African Region

2022· article· en· W4213282676 on OpenAlexaff
Humphrey Karamagi, Regina Titi-Ofei, Michelle Amri, Sosthene Zombre, Hillary Kipruto, Aminata Binetou-Wahebine Seydi, Gertrude Avortri, Juliet Nabyonga, Prosper Tumusiime

Bibliographic record

VenuePan African Medical Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsPublic Health Ontario
FundersWorld Health Organization
KeywordsMedicineWork (physics)Economic growthHealth servicesHealth careResilience (materials science)Health sectorPandemicDeveloping countryHealth policyPublic relationsCoronavirus disease 2019 (COVID-19)NursingPublic healthEnvironmental healthPopulationPolitical science

Abstract

fetched live from OpenAlex

The fifth health sector directors´ policy and planning meeting for the World Health Organization (WHO) regional office for Africa convened to focus on building health system resilience during the COVID-19 pandemic to ensure continuity of essential health services, primary health care (PHC) revitalization, and health system strengthening towards achieving universal health coverage (UHC). In this paper, we present short summaries and experiences shared by 18 countries, for which their practices and outcomes have been documented in this manuscript. These actions are aligned with six key themes: (i) defining and making more essential health services available, (ii) increasing service coverage targeting hard to reach populations, (iii) financial risk protection, (iv) improving user satisfaction with services, (v) improving health security, and (vi) improving coverage with health-related sector services. It is through these shared country experiences that lessons are learned that can influence the region´s work and advancement to achieve UHC through a PHC approach.

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)0.025
metaresearch head score (Gemma)0.025
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 score0.025
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0080.009
Scholarly communication0.0080.009
Open science0.0020.013
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.393
Teacher spread0.327 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

Explore more

Same venuePan African Medical JournalSame topicGlobal Maternal and Child HealthFrench-language works237,207