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Record W1665452530 · doi:10.11564/29-2-741

Male involvement in utilization of emergency obstetric care and averting of deaths for maternal near misses in Rakai district in Central Uganda

2015· article· en· W1665452530 on OpenAlexfundno aff
Elizabeth Nansubuga, Natal Ayiga

Bibliographic record

VenueAfrican Population Studies · 2015
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
FundersAfrican Population and Health Research CenterInternational Development Research Centre
KeywordsMedicineNear missReferralPreparednessDeveloping countryFamily medicineObstetrics

Abstract

fetched live from OpenAlex

Although studies have assessed male involvement in birth preparedness and complication readiness, little is known about their involvement after the onset of maternal near miss complications. This information is important in developing appropriate strategies for male involvement in accessing emergency obstetric care (EmOC) in order to reduce Uganda’s high maternal mortality ratio. The study examined the roles played by men after the onset of maternal near miss complications in Uganda. A qualitative study using narratives of 40 purposively selected maternal near misses and in-depth interviews of 10 randomly selected men was conducted. Results showed that men were involved in postpartum uptake of long term contraceptive methods, management of obstetric complications, decision making, social support, transport arrangements and provision of financial support to access EmOC. Therefore, men should be sensitized on the recommended haemorrhage medication during home births, the need for supervised deliveries and prompt referral of their wives to health facilities.

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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.095
GPT teacher head0.359
Teacher spread0.263 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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