Diversity, Minority Share, and the Fertility Differential Between Turks and Han in China

ABSTRACT While fertility differentials between ethno‐racial groups are often attributed to socioeconomic or cultural factors, an emerging scholarship emphasises the importance of context for these differentials to occur. This study examines how context‐level ethnic composition (ethnic context) shapes fertility differentials using the case of Xinjiang, China. Contextual data from the 2010 decennial census were linked with individual‐level data from the 2015 micro‐census. Ethnic context was measured by minority share and ethnic diversity, while controlling for key individual and county‐level covariates. Hierarchical Poisson regressions show that minority share is positively associated with the number of children, whereas diversity is negatively associated. Moreover, ethnic diversity significantly reduced the fertility differential: Turks, in contrast to Han, reported lower fertility as local diversity increased and the Turk‐Han differentials narrowed. To interpret these findings, I combined quantitative analysis with a historical reading. I classified four ethnic context ideal types (the Industrial‐military type, the Han immigrant type, the Multicultural type, and the Indigenous type) and used a simple algorithm to pick three representative cases from each ideal type. With these ideal typical cases, I explained how historical processes have created the distinct ethnic contexts that matter for fertility outcomes.

Authors

Institutions

Publication Details

Journal
Population Space and Place
Published
2026-04-01
DOI
https://doi.org/10.1002/psp.70248
Primary Topic
Demographic Trends and Gender Preferences
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diversity, Minority Share, and the Fertility Differential Between Turks and Han in China

Xiaozhao Yousef Yang
Population Space and Place
Demographic Trends and Gender Preferences
article

Diversity, Minority Share, and the Fertility Differential Between Turks and Han in China

Xiaozhao Yousef Yang
article en

Abstract

ABSTRACT While fertility differentials between ethno‐racial groups are often attributed to socioeconomic or cultural factors, an emerging scholarship emphasises the importance of context for these differentials to occur. This study examines how context‐level ethnic composition (ethnic context) shapes fertility differentials using the case of Xinjiang, China. Contextual data from the 2010 decennial census were linked with individual‐level data from the 2015 micro‐census. Ethnic context was measured by minority share and ethnic diversity, while controlling for key individual and county‐level covariates. Hierarchical Poisson regressions show that minority share is positively associated with the number of children, whereas diversity is negatively associated. Moreover, ethnic diversity significantly reduced the fertility differential: Turks, in contrast to Han, reported lower fertility as local diversity increased and the Turk‐Han differentials narrowed. To interpret these findings, I combined quantitative analysis with a historical reading. I classified four ethnic context ideal types (the Industrial‐military type, the Han immigrant type, the Multicultural type, and the Indigenous type) and used a simple algorithm to pick three representative cases from each ideal type. With these ideal typical cases, I explained how historical processes have created the distinct ethnic contexts that matter for fertility outcomes.

Population Space and PlaceVol. 32(3)
Sun Yat-sen University (CN)
Openalex Percentile: Top 5%
Demographic Trends and Gender Preferences
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.