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Record W4226094823 · doi:10.5216/ree.v23.61603

Institutional support to community health workers using integrated management of childhood illness program in Rwanda

2021· article· en· W4226094823 on OpenAlexaff
Joyce Kamanzi, Solina Richter

Bibliographic record

VenueRevista Eletrônica de Enfermagem · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Alberta
FundersInyuvesi Yakwazulu-Natali
KeywordsIntegrated Management of Childhood IllnessNursingExploratory researchDescriptive statisticsSample (material)Economic shortageSocial supportCommunity healthMedicinePsychologyEnvironmental healthHealth servicesGovernment (linguistics)Sociology

Abstract

fetched live from OpenAlex

The objective was to explore the support given to community health workers who use the integrated management of childhood illness (IMCI) approach and describe the supervision given to them. A non-experimental, exploratory, descriptive, quantitative design was used for this study. Data were collected using a structured questionnaire; 305 were interviewed (30% sample). The data were double entered, cleaned, and analyzed using Statistics Package of Social Sciences (SPSS) 19. Support and supervision in Rwanda are provided by the base institution and by supervisors. CHWs often had a shortage of drugs and equipment (63.3%) and 87.5% have experienced run out of equipment, medicines, and consumables. This created barriers to caring for sick children. To improve institutional support for community health workers, regular and continuous supportive supervision and supplies are essential.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.367
Teacher spread0.328 · 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
Published2021
Admission routes1
Has abstractyes

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