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Record W3207766122 · doi:10.1002/psp.2524

Migration policies on migrant–native marriage: A multilevel analysis of 43 Chinese cities

2021· article· en· W3207766122 on OpenAlexaff
Felicia F. Tian, Yue Qian

Bibliographic record

VenuePopulation Space and Place · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChinaMerge (version control)Demographic economicsInternal migrationCensusMigrant workersInequalityLogistic regressionGeographyIndex of dissimilarityPopulationPolitical scienceDemographyDevelopment economicsEconomic geographyEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

Abstract China's household registration ( hukou ) system creates internal migration patterns similar to international patterns. Variations in the stringency of city policies for acquiring local hukou provide a unique opportunity to examine how migration policies affect migrant–native marriage. In this study, we merge a city‐level index that measures the overall difficulty of obtaining local hukou in 43 Chinese cities with China's 2005 mini‐census. Results from multilevel logistic regression models reveal that migration policies have heterogeneous effects on intermarriage. For migrant men, as it becomes more difficult to acquire local hukou , it becomes less likely that a less educated migrant man will marry and more likely that a better educated migrant man will marry a local hukou holder. For migrant women, their likelihood of intermarriage does not vary much with the stringency of hukou policies. These findings suggest that migration policies reinforce inequality between migrants and natives and within the migrant population.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.276
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.018
GPT teacher head0.323
Teacher spread0.304 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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