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Cost‐effectiveness of USAID's Regional Program for Family Planning in West Africa

2003· article· en· W1968586878 on OpenAlexaff
Donald S. Shepard, Richard N. Bail, C. Gary Merritt

Bibliographic record

VenueStudies in Family Planning · 2003
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsInstitute of Population and Public Health
FundersUnited States Agency for International Development
KeywordsFamily planningAgency (philosophy)Economic growthInternational developmentDeveloping countryProgram evaluationPopulationReproductive healthWork (physics)BusinessPolitical scienceMedicineEconomicsEnvironmental healthSociologyPublic administrationResearch methodology

Abstract

fetched live from OpenAlex

Between 1994 and 1996, the United States Agency for International Development (USAID) closed 23 country missions worldwide, of which eight were in West and Central Africa. To preserve United States support for family planning and reproductive health in four countries in that region, USAID created a subregional program through a consortium of US-based groups that hired mainly African managers and African organizations. This study assesses cost-effectiveness of the program through an interrupted time-series design spanning the 1990s and compares cost-effectiveness in four similar countries in which mission-based programs continued. Key indicators include costs, contraceptive prevalence rates, and imputed "women-years of protection." The study found that, taking into account all external financing for population and family planning, the USAID West Africa regional approach generated women-years of protection at one-third the cost of the mission-based programs. This regional approach delivered family planning assistance in West Africa cost-effectively, and the findings suggest that regional models may work well for many health and population services in small countries.

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)0.004
metaresearch head score (Gemma)0.015
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.188
GPT teacher head0.425
Teacher spread0.236 · 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

Citations7
Published2003
Admission routes1
Has abstractyes

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