Assessment of the synergy degree of China's food safety risk governance policy tools based on text mining and machine learning methods

被引:0
作者
Sha, Di [1 ]
Qin, Ke [1 ]
Zhu, Lv [1 ]
Qian, He [2 ]
Wu, Linhai [1 ,3 ]
机构
[1] Jiangnan Univ, Sch Business, Wuxi 214122, Jiangsu, Peoples R China
[2] Jiangnan Univ, Sch Food Sci & Technol, Wuxi 214122, Jiangsu, Peoples R China
[3] Jiangnan Univ, Jiangsu Prov Lab Food Safety & Natl Strateg Govern, Wuxi 214122, Jiangsu, Peoples R China
关键词
Central and provincial governments; food safety; policy tool synergy; risk governance; Top2Vec;
D O I
10.1111/ijfs.17499
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Implementing proactive and effective policy tools is essential for governments to manage food safety risks. Existing studies have overlooked the synergistic effects among policy tools for governing food safety risks in China. This study uses policy tool synergy to develop a quantitative model to evaluate the degree of synergy among policy tools for food safety risk governance by considering its vertical, horizontal, and temporal dimensions. Using the Top2Vec topic model and text mining techniques, we examined 558 policy documents implemented by the central and six provincial governments. The findings reveal that China's food safety risk governance system has established a collaborative mechanism, with the Administration for Market Regulation, the Department of Agriculture and Rural Affairs, and the Health Commission playing crucial roles in policy implementation. Vertical and horizontal synergies between the upper and lower levels of government and among departments at the same level are crucial for enhancing comprehensive synergy. This study uses policy tool synergy to develop a quantitative model to evaluate the degree of synergy among policy tools for food safety risk governance by considering its vertical, horizontal, and temporal dimensions. The findings reveal that China's food safety risk governance system has established a collaborative mechanism. image
引用
收藏
页码:7497 / 7508
页数:12
相关论文
共 45 条
[1]   Quantitative and qualitative approach for accessing and predicting food safety using various web-based tools [J].
Abid, Hafiz Muhammad Rizwan ;
Khan, Nimrah ;
Hussain, Athar ;
Anis, Zainab Bintay ;
Nadeem, Muhammad ;
Khalid, Nauman .
FOOD CONTROL, 2024, 162
[2]   Modeling shellfish harvest policies for food safety: Wild oyster harvest restrictions to prevent foodborne Vibrio vulnificus [J].
Alvarez, Sergio ;
Solis, Daniel ;
Hwang, Joonghyun .
FOOD POLICY, 2019, 83 :219-230
[3]  
Angelov D., 2020, ARXIV, DOI [DOI 10.48550/ARXIV.2008.09470, 10.48550/arXiv.2008.09470]
[4]   Evolution of environmental policy for China's rare earths: Comparing central and local government policies [J].
Chai, Song ;
Zhang, Zhicong ;
Ge, Jianping .
RESOURCES POLICY, 2020, 68
[5]   Policy tools for agricultural nonpoint source water pollution control in the U.S. and E.U. [J].
Drevno, Ann .
MANAGEMENT OF ENVIRONMENTAL QUALITY, 2016, 27 (02) :106-123
[6]   Effects of the joint prevention and control of atmospheric pollution policy on air pollutants-A quantitative analysis of Chinese policy texts [J].
Du, Huibin ;
Guo, Yaqian ;
Lin, Zhongguo ;
Qiu, Yueming ;
Xiao, Xiao .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2021, 300 (300)
[7]   A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts [J].
Egger, Roman ;
Yu, Joanne .
FRONTIERS IN SOCIOLOGY, 2022, 7
[8]   Food safety policy enforcement and associated actions reduce lead chromate adulteration in turmeric across Bangladesh [J].
Forsyth, Jenna E. ;
Baker, Musa ;
Nurunnahar, Syeda ;
Islam, Shariful ;
Islam, M. Saiful ;
Islam, Tauhidul ;
Plambeck, Erica ;
Winch, Peter J. ;
Mistree, Dinsha ;
Luby, Stephen P. ;
Rahman, Mahbubur .
ENVIRONMENTAL RESEARCH, 2023, 232
[9]   Food safety risk behavior and social Co-governance in the food supply chain [J].
Gao, Huanyu ;
Dai, Xiaoting ;
Wu, Linhai ;
Zhang, Jingxiang ;
Hu, Wuyang .
FOOD CONTROL, 2023, 152
[10]   Government regulations and voluntary certifications in food safety in China: A review [J].
Guo, Zaidi ;
Bai, Li ;
Gong, Shunlong .
TRENDS IN FOOD SCIENCE & TECHNOLOGY, 2019, 90 :160-165