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Record W1888462542 · doi:10.25336/p6gs4s

Currently married women with an unmet need for contraception in Eritrea: Profile and determinants

2011· article· en· W1888462542 on OpenAlexaffvenueabout
Gebremariam Woldemicael, Roderic Beaujot

Bibliographic record

VenueCanadian Studies in Population · 2011
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsWestern University
Fundersnot available
KeywordsFamily planningFertilityQuarter (Canadian coin)AutonomyTotal fertility rateDemographyMarital statusPopulationMedicineDeveloping countryBirth rateEconomic growthGeographyPolitical scienceSociologyResearch methodologyEconomics

Abstract

fetched live from OpenAlex

Eritrea’s contraceptive prevalence rate is one of the lowest in sub-Saharan Africa and its fertility has only started to decline. Using data from the 2002 Eritrea Demographic and Health Survey (EDHS), this study examines the determinants of unmet need for family planning that is the discrepancy between fertility goals and actual contraceptive use. More than one-quarter of currently married women are estimated to have an unmet need, and this has remained unchanged since 1995. The most important reason for unmet need is lack of knowledge of methods or of a source of supply. Currently married women with higher parity, and low autonomy, low or medium household economic status, and who know no method of contraception or source of supply are identified as the most likely to have an unmet need. Addressing the unmet need for family planning entails not merely greater knowledge of or access to contraceptive services, but also the enhancement of the status of women.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.172
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.058
GPT teacher head0.335
Teacher spread0.277 · 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

Citations53
Published2011
Admission routes3
Has abstractyes

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