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Record W2943065433 · doi:10.1080/1369183x.2019.1592883

<i>Hukou</i>, marriage, and access to wealth in Shanghai

2019· article· en· W2943065433 on OpenAlexaff
Zhenchao Qian, Yüan Cheng, Yue Qian

Bibliographic record

VenueJournal of Ethnic and Migration Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Socioeconomic Reforms and Governance
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthNational Institute of Child Health and Human DevelopmentFudan University
KeywordsChinaDemographic economicsInequalityBusinessSurvey data collectionWelfareGeographyPolitical scienceEconomic growthEconomics

Abstract

fetched live from OpenAlex

About two-fifths of the population in Shanghai, the largest city in China, are migrants. In order to live in Shanghai permanently, many migrants strive to gain Shanghai hukou because of its close connection to easier access to jobs, schools, social welfare, and other opportunities in Shanghai. In this paper, we use newly available data from the 2013 Fudan Yangtze River Delta Social Transformation Survey. This survey sampled Shanghai residents born in the 1980s, regardless of hukou status. We evaluate how young migrants’ original hukou type and locale as well as individual and family characteristics are associated with gaining Shanghai hukou, and explore how Shanghai hukou is related to home ownership, car ownership, and income. The analyses reveal that migrants with great resources tend to gain Shanghai hukou, which, in turn, leads to greater access to home ownership; hukou plays a weaker but important role in car ownership and income. Our study indicates that Shanghai hukou is beyond the reach of poor and less-educated migrants and remains a powerful engine of social inequality in China.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.065
GPT teacher head0.414
Teacher spread0.349 · 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 designQualitative
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

Citations28
Published2019
Admission routes1
Has abstractyes

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