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Record W2319807976 · doi:10.3138/jcfs.31.4.485

Effects of child gender preference on contraceptive use in rural Bangladesh

2000· article· en· W2319807976 on OpenAlexvenueno aff
Akiko Nosaka

Bibliographic record

VenueJournal of Comparative Family Studies · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsnot available
Fundersnot available
KeywordsFamily planningPreferenceDemographyRural areaDeveloping countryInduced AbortionsPopulationSocioeconomicsFertilityMedicineGender studiesPsychologySociologyResearch methodologyEconomic growthEconomics

Abstract

fetched live from OpenAlex

While people in rural Bangladesh have adopted the use of modern contraceptives over the past two decades, they traditionally have a parental preference for sons over daughters. This paper examines how the child gender preference influences a woman’s use of modern contraceptives in Matlab, rural Bangladesh. This study is based on data from 300 women in the treatment area, where modern contraceptive prevalence is exceptionally high, and 144 women in the comparison area, where modern contraceptive prevalence is relatively low. These women were interviewed between 1995 and 1996. The treatment area results show that the desire for sons exerts a significant influence on contraceptive use, whereas the desire for daughters contrast, the comparison area results suggest that it is the number of currently surviving sons and daughters that exerts a significant influence on contraceptive use.

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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.144
GPT teacher head0.363
Teacher spread0.219 · 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

Citations3
Published2000
Admission routes1
Has abstractyes

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