Evidence map›Paper›PMID 41131005›Full record

ArticleScientific reports2025

Impact of government's dual-carbon attention on urban carbon emissions reduction: evidence from the Yangtze River Delta.

Kai Chang, Jing Li, Shuqi Wei, Boyang Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kai ChangSchool of Finance and Business, Shanghai Normal University, Shanghai, 200234, China. kchang16@163.com.
Jing LiSchool of Finance and Business, Shanghai Normal University, Shanghai, 200234, China.
Shuqi WeiSchool of Finance and Business, Shanghai Normal University, Shanghai, 200234, China.
Boyang LiSchool of Data Science and Engineering, East China Normal University, Shanghai, 200241, China.

Funding

Shanghai Association for Science and Technology 22692109600; 21692108000
6 · The paper itself

Abstract

There is an ever-increasing concern among local governments in China regarding the relationship between government attention and carbon emissions. This study proposes a new dual-carbon attention dictionary and measures local governments' dual-carbon attention (GCA) level using textual analysis and the maximum reverse matching method. Our research highlights that an extended STIRPAT model exhibits the significance of local governments' efforts in achieving CO

Indexed as

Carbon emissionsEmission-reduction policiesGCAIndustrial structure upgradingSTIRPAT model

Identifiers

PMID41131005
PMCPMC12549849

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.