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Record W4308295817 · doi:10.5539/ach.v14n2p173

Legacy of the One-Child Policy: Marriage Dilemmas in Urban and Rural China

2022· article· en· W4308295817 on OpenAlexvenueno aff
Yujia Gu

Bibliographic record

VenueAsian Culture and History · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsnot available
Fundersnot available
KeywordsChinaOne-child policyDilemmaEconomicsMarriage marketTotal fertility rateEconomic growthDevelopment economicsDemographic economicsFamily planningSociologyPolitical sciencePopulationLawDemography

Abstract

fetched live from OpenAlex

China’s one-child policy, the family planning policy enforced in 1980, continued for almost 36 years and created a lasting impact on both China’s declining total fertility rate (TFR) and its sex ratio imbalance. This paper discusses the marriage dilemma caused by the one-child policy and its separate outcomes in urban and rural areas. In urban areas, the expense for childbearing, the equated monthly installment (EMI) payments, and the self-consuming nature of marriage contributed to the declining marriage rate as well as the TFR. In rural settings, the surplus of single men due to the entrenched “son preference” created a demand for the bride-trafficking market, an industry of purchasing a bride as a form of property. In this paper, I conclude that the marriage crisis and its side effects are the legacies of the one-child policy, and the Chinese government needs to craft effective approaches in addressing these problems.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.011
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.015
GPT teacher head0.233
Teacher spread0.218 · 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
Published2022
Admission routes1
Has abstractyes

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