# Policy tools, objectives, and governance in China’s public sports services: an X–Y–Z framework analysis of national and provincial policies

## TL;DR

This study analyzes Chinese public sports policies using an X–Y–Z framework to identify gaps in tool selection, objectives, and thematic focus, aiming to improve policy effectiveness and equity.

## Contribution

The study introduces a novel X–Y–Z analytical framework combining policy tools, objectives, and thematic features for evaluating public sports policies.

## Key findings

- Policies heavily rely on supply-oriented tools, with demand-oriented tools underused.
- Equity and economic benefits receive less attention compared to industrial development and national fitness.
- Thematic priorities include 'health,' 'construction,' and 'development,' while 'innovation' is overlooked.

## Abstract

As part of “Healthy China 2030” strategy, China has emphasized the expansion and equalization of public sports services to improve population health and promote social equity. Despite these goals, current policies often exhibit fragmented tool selection, vague targeting, and weak alignment with public needs, limiting their effectiveness in supporting inclusive, high-quality development.

This study proposes an “X–Y–Z” analytical framework that integrates policy tools (X), policy objectives (Y), and thematic features (Z). Using content analysis, 76 national and provincial policy documents (2015–2025) were systematically coded. NVivo14 was used to extract and classify policy tools and objectives, while ROST-CM6 identified high-frequency keywords and constructed a semantic network.

The findings show a heavy reliance on supply-oriented tools, with demand-oriented tools significantly underutilized. Policy objectives are mainly concentrated on industrial development and national fitness, with relatively low attention to equity and economic benefit. Thematic analysis highlights “health,” “construction,” and “development” as core priorities, while “innovation” remains marginalized.

By combining text encoding with semantic network analysis, this study provides a replicable and data driven approach to evaluating policies in the field of public health. It points out structural imbalances and reveals key blind spots in policy design. The research results provide an empirical basis for optimizing tool selection, coordinating multiple objectives, and enhancing policy responsiveness and fairness.