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Record W4200439230 · doi:10.1080/23293691.2021.2016187

Maternal Health Care in Ghana: Challenges Facing the Uptake of Services in the Shai Osudoku District

2021· article· en· W4200439230 on OpenAlexaff
Joseph Adu, Mark Fordjour Owusu, Ebenezer Martin‐Yeboah, Albert Ahenkan, Sebastian Gyamfi

Bibliographic record

VenueWomen s Reproductive Health · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsWestern University
Fundersnot available
KeywordsHealth servicesHealth careGeographyBusinessSocioeconomicsNursingMedicineEnvironmental healthEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

We assessed the challenges facing 29 women in their quest for maternal health services in the Shai Osudoku District of Ghana. In-depth, semi-structured interviews with health professionals and focus-group discussions with women on uptake of maternal health services were conducted. Findings showed inadequate human resources and logistics for maternal health care and transportation problems. Women whose pregnancies required specialized care at district or regional hospitals deliberately reported late to the community clinics in an advanced stage of labor to avoid referrals. Findings have implications for health policymakers, implementers, and researchers.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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 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

Citations4
Published2021
Admission routes1
Has abstractyes

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