MétaCan
Menu
Back to cohort
Record W2135446629 · doi:10.7189/jogh.04.020303

The way forward for integrated community case management programmes: A summary of lessons learned to date and future priorities

2014· review· en· W2135446629 on OpenAlexfundno aff
Mark Young, Alyssa Sharkey, Samira Aboubaker, Dyness Kasungami, Eric Swedberg, Kerry Ross

Bibliographic record

VenueJournal of Global Health · 2014
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersDepartment of Foreign Affairs and Trade, Australian GovernmentGovernment of CanadaWorld Health OrganizationGlobal Fund to Fight AIDS, Tuberculosis and Malaria
KeywordsPsychological interventionGovernment (linguistics)Software deploymentProgram evaluationDeveloping countryBusinessMedicineEconomic growthEnvironmental healthPolitical scienceNursingComputer sciencePublic administrationEconomics

Abstract

fetched live from OpenAlex

Integrated community case management (iCCM) programming is an important and increasingly common strategy used to deliver essential health and nutrition interventions to families in sub-Saharan Africa [1-3]. Between 3 and 5 March 2014, over 400 individuals from 35 countries in sub-Saharan Africa and 59 international partner organisations gathered in Accra, Ghana for an iCCM Evidence Review Symposium. The objective of the Symposium was twofold: first, to review the current state of the art of iCCM implementation by bringing together researchers, donors, government, implementers and partners to review the map of the current landscape and status of evidence in key iCCM programme areas, in order to draw out priorities, lessons and gaps for improving child and maternal-newborn health and nutrition. Second, to assist African countries to integrate and take action on key frontline iCCM findings presented during the evidence Symposium around eight thematic areas: 1) Coordination, Policy Setting and Scale up; 2) Human Resources and Deployment; 3) Supervision & Performance Quality Assurance; 4) Supply Chain Management; 5) Costs, and cost-effectiveness and financing; 6) Monitoring, Evaluation and Health Information

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.440
Teacher spread0.376 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Global HealthSame topicGlobal Maternal and Child HealthFrench-language works237,207