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Record W4410001647 · doi:10.29063/ajrh2025/v29i4.9

Are traditional honour ideologies associated with fertility goals and contraceptive use? Findings from a cross-sectional study with a national sample of women and men in Uganda

2025· article· en· W4410001647 on OpenAlexaff
Arnab Dey, Kalysha Closson, Jarrod E. Bock, Ryan P. Brown, Pamela Kakande Nabukhonzo, Wilson Nyegenye, Anita Raj

Bibliographic record

VenueAfrican Journal of Reproductive Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCross-sectional studyHonourFertilitySample (material)Family planningDemographyIdeologyPopulationGender studiesMedicinePolitical scienceSociologyResearch methodologyPolitics

Abstract

fetched live from OpenAlex

We used data from a nationally representative sample of men and women of childbearing age in Uganda to assess the association between traditional honour ideologies and fertility goals and contraception use. We used multivariable regression analysis to assess the associations between honour ideologies and a) the ideal number of children, b) male control over contraceptive decision-making, and c) male/female-controlled contraceptive use. Results show that men desired more children and were less likely to use contraception compared to women. For men, honour ideologies about women are linked to both larger desired family size and lower likelihood to use male-controlled contraceptives. Additionally, men's honour ideologies for both genders were associated with a higher likelihood of male control over contraceptive decision-making. We conclude that traditional honour norms not only lead to a preference for more children but also entail male control over contraceptive decisions, undermining women's contraceptive use autonomy.

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)0.004
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.112
GPT teacher head0.407
Teacher spread0.295 · 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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