Evidence map›Paper›PMID 37006558›Full record

ArticleFrontiers in public health2023

How does digital governance affect the level of domestic waste separation for rural residents? Empirical evidence from rural areas in Jiangsu Province, China.

Xi Chen, Lirong Xing, Kai Wang, Jianzhen Lu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.8field-weighted citation impact, top 11% of its field
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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
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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 at 3 institutions in 1 country.

Xi ChenCollege of Economics and Management, Nanjing Agricultural University, Nanjing, China.
Lirong XingCollege of Economics, Shandong University of Technology, Zibo, China.
Kai WangCollege of Economics and Management, Nanjing Agricultural University, Nanjing, China.
Jianzhen LuInstitute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing, China.
Nanjing Agricultural University · CNJiangsu Academy of Agricultural Sciences · CNShandong University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The management of rural domestic waste is directly related to the quality of China's rural habitat and the ecological security of the countryside, and is one of the important tasks of rural revitalization. Methods: Based on the perspective of digital technology empowering rural governance, this study uses the China Land Economic Survey (CLES) data to empirically test the impact of digital governance on the level of domestic waste separation for rural residents by constructing the ordered probit model. Results and discussion: The results show that in the process of rural governance modernization, digital governance helps to improve the level of domestic waste separation for rural residents in the process of rural governance modernization, and the findings still hold after robustness tests. Mechanistic tests showed that digital governance can impact the level of domestic waste separation for rural residents through cadre-mass relationship and institutional trust. The findings of this study provide a new perspective on good environmental governance in China's countryside and have important implications for promoting the improvement of rural habitat quality.

Indexed as

Conservation of Natural ResourcesEnvironmental PolicyChinaHumansRural Populationcadre-mass relationshipdigital governancedomestic waste separationinstitutional trustJiangsu

Identifiers

PMID37006558
PMCPMC10056637
OpenAlexW4324344621

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.