Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)

A Quantitative Model for Policy Text Assessment: A Multi-Dimensional Analysis of China’s High-Standard Farmland Construction

Authors
Yuan Wang1, *
1Nanjing University of Finance and Economics, Nanjing, 210023, China
*Corresponding author. Email: wangyuan.academic@outlook.com
Corresponding Author
Yuan Wang
Available Online 15 May 2026.
DOI
10.2991/978-2-38476-577-5_126How to use a DOI?
Keywords
Policy text evaluation; the TOL index model; high-standard farmland construction policies
Abstract

Systematic evaluation of policy documents is essential for optimizing policy design; however, quantitative models for analyzing and assessing the content design of such documents remain inadequate. Accordingly, this paper introduces the TOL index model and a three-dimensional analytical framework of “theme-objective-lifecycle.” The TOL index model was developed through variable selection, parameter configuration, and index measurement. By implementing text feature extraction utilizing the Word2Vec model and LDA topic model analysis based on corpus from text mining methodologies, unstructured data was converted into structured data, thereby achieving systematic deconstruction of policy document content design and providing a scientific foundation for policy optimization. As a case study, a quantitative analysis was performed using policy documents concerning high-standard farmland construction in China during the current developmental stage. The research reveals that, overall, policy text content design exhibits considerable comprehensiveness, with policy ratings ranking above medium level. However, significant regional heterogeneity is observed in policy topics across various construction zones, substantial differences exist in policy objectives, and there are varying focuses on policy project lifecycles. The research concludes that this paper establishes a “Topic-Objective-Lifecycle” analytical framework and the TOL index model, systematically and multidimensionally deconstructing the content design of policy texts. The research findings provide scientific evidence for optimizing the content design of high-standard farmland construction policy texts in terms of policy topic coverage, progressive nature of policy objectives, and connectivity of policy lifecycles. Consequently, the TOL index model can also function as a decision support tool to facilitate policy design optimization.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
15 May 2026
ISBN
978-2-38476-577-5
ISSN
2352-5398
DOI
10.2991/978-2-38476-577-5_126How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Yuan Wang
PY  - 2026
DA  - 2026/05/15
TI  - A Quantitative Model for Policy Text Assessment: A Multi-Dimensional Analysis of China’s High-Standard Farmland Construction
BT  - Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
PB  - Atlantis Press
SP  - 1227
EP  - 1246
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-577-5_126
DO  - 10.2991/978-2-38476-577-5_126
ID  - Wang2026
ER  -