Evidence map›Paper›PMID 38394217›Full record

ArticlePloS one2024

Sustainable development of environmental protection talents training: Research on the behavior decision of government, university and enterprise under the background of evolutionary game.

Jinxia Wang, Yunfeng Tan, Lingling Zhan, Hongjun Yang, Xieling Li, Fang Gao, Siyuan Qiu

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

7 authors.

Jinxia WangCollege of Resources and Safety, Chongqing Vocational Institute of Engineering, Chongqing, China.ORCID 0009-0004-7186-8031
Yunfeng TanCollege of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing, China.
Lingling ZhanGeneral college, Chongqing Vocational Institute of Engineering, Chongqing, China.
Hongjun YangCollege of Resources and Environment, Southwest University, Beibei, Chongqing, China.
Xieling LiCollege of Resources and Safety, Chongqing Vocational Institute of Engineering, Chongqing, China.
Fang GaoCollege of Resources and Safety, Chongqing Vocational Institute of Engineering, Chongqing, China.
Siyuan QiuCollege of Resources and Safety, Chongqing Vocational Institute of Engineering, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Environmental protection talents training (EPTT) is recognized as a key prerequisite for maintaining environmental sustainability, and in order to study the influence of each player on EPTT. This paper innovatively constructs a tripartite evolutionary game model of government, university and enterprise. The equilibrium points and evolutionary stabilization strategies of each participant are solved by replicating the dynamic equations, and the behaviors of each subject in EPTT are analyzed so as to clarify the behavioral characteristics and optimal strategies of the government's participation in EPTT. The results show that enterprises occupy a more important position in influencing government decisions. The government should reduce the financial incentives for enterprises and replace them with greater policy support. Meanwhile, the government should actively promote the cultivation mechanism that integrates universities and enterprises. The results of the study can provide a decision-making basis for the government to promote the sustainable development of EPTT.

Indexed as

Conservation of Natural ResourcesSustainable DevelopmentBiological EvolutionChinaGame TheoryGovernmentHumansUniversities

Identifiers

PMID38394217
PMCPMC10890725

What OpenQuestion holds

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LicenceCC BY
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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.