Spatial inequality and policy implications of school physical education resource allocation: evidence from Shaanxi Province, China

Introduction Equitable access to school physical education (PE) resources is central to education goals, yet sub-provincial spatial patterns in China remain underexamined. Methods Using 2024 data for 107 districts/counties in Shaanxi, we built a human–material–financial index with entropy weights, mapped distributions (GIS, standard deviational ellipse), tested clustering (Global/Local Moran’s I, LISA), decomposed inequality (Dagum’s Gini), and identified determinants and interactions (GeoDetector). Results Resources follow a core–periphery gradient centered on central Shaanxi. Global Moran’s I = 0.105 ( p = 0.037) indicates weak but significant clustering; LISA shows extensive Low–Low clusters. Overall inequality is modest (Gini = 0.176) but driven mainly by inter-city gaps (~48%) and cross-city overlap (~43%). Human resources dominate composite scores; key drivers are urbanization, PE funding share, student density, and teacher supply, with strong synergistic interactions. Discussion Findings call for teacher-workforce strengthening, rebalancing investment toward facilities and professional development, and spatially targeted multi-lever policies—especially for persistent Low–Low clusters and urban–rural margins.

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Publication Details

Journal
Frontiers in Education
Published
2025-11-26
DOI
https://doi.org/10.3389/feduc.2025.1693461
Primary Topic
Physical Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00

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article

Spatial inequality and policy implications of school physical education resource allocation: evidence from Shaanxi Province, China

Bing Shi, Chengwei Xu
Frontiers in Education
Physical Education and Pedagogy
article

Spatial inequality and policy implications of school physical education resource allocation: evidence from Shaanxi Province, China

Bing Shi, Chengwei Xu
article en

Abstract

Introduction Equitable access to school physical education (PE) resources is central to education goals, yet sub-provincial spatial patterns in China remain underexamined. Methods Using 2024 data for 107 districts/counties in Shaanxi, we built a human–material–financial index with entropy weights, mapped distributions (GIS, standard deviational ellipse), tested clustering (Global/Local Moran’s I, LISA), decomposed inequality (Dagum’s Gini), and identified determinants and interactions (GeoDetector). Results Resources follow a core–periphery gradient centered on central Shaanxi. Global Moran’s I = 0.105 ( p = 0.037) indicates weak but significant clustering; LISA shows extensive Low–Low clusters. Overall inequality is modest (Gini = 0.176) but driven mainly by inter-city gaps (~48%) and cross-city overlap (~43%). Human resources dominate composite scores; key drivers are urbanization, PE funding share, student density, and teacher supply, with strong synergistic interactions. Discussion Findings call for teacher-workforce strengthening, rebalancing investment toward facilities and professional development, and spatially targeted multi-lever policies—especially for persistent Low–Low clusters and urban–rural margins.

Frontiers in EducationVol. 10
Xi'an Physical Education University (CN), Shaanxi Normal University (CN)
Education Department of Shaanxi Province, Social Science Foundation of Shaanxi Province, National Social Science Fund of China
Openalex Percentile: Top 46%
Physical Education and Pedagogy
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