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Record W4415703224 · doi:10.54536/jpp.v2i1.4625

Male Involvement in Family Planning at Tema General Hospital, Ghana

2025· article· W4415703224 on OpenAlexaff
Kate Arku Korsah, Kwesi Botchwey, Isaac Kwesi Ossuan, M. Cunningham

Bibliographic record

VenueJournal of Policy and Planning · 2025
Typearticle
Language
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsQueen's UniversityToronto Metropolitan University
Fundersnot available
KeywordsFamily planningAttendanceShynessPopulationUnit (ring theory)

Abstract

fetched live from OpenAlex

Male involvement in the family planning in Ghana is not very much encouraging as most men see family planning as a woman’s activity or responsibility. The main objective of the study was to assess the involvement of males in family planning at Tema General Hospital. The study design for this research was the cross-sectional study design. A total of 110 participants were recruited for the study, out of which 100 were men in the community and 10 were staff of the Family Planning unit of Tema General Hospital. Attendance register was also reviewed from 2015 – 2017. It was seen that attendance of males to FP clinic have been increasing gradually over the years – 596 (2015) to 695 (2017). Factors that were indicated to influence FP attendance were spear-headed by shyness and low level of knowledge and then followed by negative family perception. It can be concluded that, male involvement in family planning is not encouraging despite a gradual increase over the past three years.

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)0.001
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.025
GPT teacher head0.334
Teacher spread0.309 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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