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Son Preference in a Rural Village in North Vietnam

2002· article· en· W2045533598 on OpenAlexaff
Danièle Bélanger

Bibliographic record

VenueStudies in Family Planning · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsWestern University
Fundersnot available
KeywordsFertilityKinshipPreferenceContext (archaeology)Gender studiesSociologyInequalityPopulationSocioeconomicsFamily planningGeographyDemographyDemographic economicsEconomic growthEconomicsResearch methodologyAnthropology

Abstract

fetched live from OpenAlex

This article explores the continuing preference for sons in the context of low fertility in Vietnam. Although the total fertility rate for Vietnam declined from 6.0 children per woman of reproductive age in 1979 to 2.2 children in 1998, demographic evidence shows that son preference remains strong and influences contraceptive and fertility behavior. This study examines the underlying factors for son preference in a rural village in North Vietnam. The methodology includes focus-group discussions, an in-depth study of 25 families, and ethnographic observation. Results indicate that sons are highly desired for their social, symbolic, and economic value. In spite of four decades of socialist policies aimed at reducing gender-based inequalities and at weakening the patriarchal kinship system, the desire for sons continues to drive the family-building process. The article also indicates a gap between discourse and social practice with respect to roles assigned to children on the basis of their sex.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.219
GPT teacher head0.362
Teacher spread0.143 · 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

Citations132
Published2002
Admission routes1
Has abstractyes

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