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Record W2603005578 · doi:10.3138/jcfs.34.4.531

Postponement or Abandonment of Marriage? Evidence from Hong Kong

2003· article· en· W2603005578 on OpenAlexvenueno aff
Odalia Ming Hung Wong

Bibliographic record

VenueJournal of Comparative Family Studies · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsEducational attainmentPostponementHuman capitalAbandonment (legal)Demographic economicsEconomicsEmpirical evidenceSample (material)Labour economicsEconomic growthPolitical science

Abstract

fetched live from OpenAlex

This paper examines whether the rise in the age at first marriage among women observed across many countries in the post-war era reflects postponement or abandonment of marriage. On both theoretical and empirical grounds, we reject the oft-cited Economic Independence hypothesis, which argues that rising educational attainment and employment among women have weakened the rationale for marriage, leading more women to forego marriage. Instead, using a human capital approach, we argue that rising educational and economic opportunity would lead women to postpone, but not abandon, marriage in order to complete more human capital investment early in the life course. Empirical analysis applied to an original data set for Hong Kong women broadly supports our hypothesis. Specifically, the use of hazard analysis shows that educational and career attainment among women in our sample reduce their marriage rates, but this effect tends to diminish over the life course. This result is further supported by applying survey analysis on the same sample. Specifically, women with higher educational attainment and career attainment actually expressed a stronger desire for marriage, albeit at a late age.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.241
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.322
GPT teacher head0.444
Teacher spread0.121 · 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

Citations15
Published2003
Admission routes1
Has abstractyes

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