Evidence map›Paper›PMID 35910862›Full record

ReviewFrontiers in public health2022

Public-Public Collaboration for Food Safety Risk Management: Essence, Modes, and Identification of Key Influencing Factors Using DANP.

Liwei Zhang, Ke Qin, Yufeng Li, Linhai Wu

Abstract readReview
In one paragraph

Review in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liwei ZhangCollege of Economics and Management, Shanghai Ocean University, Shanghai, China.
Ke QinSchool of Business, Jiangnan University, Wuxi, China.
Yufeng LiCollege of Economics and Management, Shanghai Ocean University, Shanghai, China.
Linhai WuSchool of Business, Jiangnan University, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Food safety risk management is an important cross-boundary issue from both theoretical and practical standpoints. Because food safety has the social attributes of public goods, public-public collaboration can be considered a particularly important mode of cross-boundary governance. The study aims to provide a theoretical basis for the Chinese government to promote public-public collaboration for food safety risk management by identifying key factors. Methods: Based on a review of literature across diverse fields, such as political science, sociology, and new public governance, this study discusses the essence, modes, and dilemma of public-public collaboration for food safety risk management using practical explorations in various countries as the main thread and taking into account the actual situation in China. Moreover, this study quantitatively analyzes the relationships between the dimensions and factors affecting public-public collaboration and identifies key dimensions and factors using the Decision-making Trial and Evaluation Laboratory-based Analytic Network Process (DANP). Results: Among the 20 factors in the calculation results of DANP, Lawmaking has the highest value of ( Conclusion: The legal basis is the most important dimension affecting public-public collaboration. Legislation-based governance, administrative law enforcement-based governance, and social environment improvement-based governance in the behavior and capabilities dimension, professionalism in the basic characteristics dimension, and laws and regulations in the legal basis dimension are the five key factors.

Indexed as

Food SafetyGovernmentChinacross-boundary governanceDANPfood safety riskkey factorpublic-public collaboration

Identifiers

PMID35910862
PMCPMC9326024

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.