Evidence map›Paper›PMID 36471788›Full record

ArticleCities (London, England)2021

Collaborative neighborhood governance and its effectiveness in community mitigation to COVID-19 pandemic: From the perspective of community workers in six Chinese cities.

Zhilin Liu, Sainan Lin, Yue Shen, Tingting Lu

Open access · greenAbstract read
In one paragraph

Article in Cities (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
12.8field-weighted citation impact, top 1% 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

14 citing papers in PubMed, 72 citations in OpenAlex.

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  13. Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities.International journal of environmental research and public health · 2022
    Review
  14. Frontiers in health services · 2022
    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

4 authors at 4 institutions in 1 country.

Zhilin LiuSchool of Public Policy and Management, Hang Lung Center for Real Estate, Tsinghua University, China.
Sainan LinSchool of Urban Design, Wuhan University, China.
Yue ShenResearch Center for China Administrative Division, East China Normal University, China.
Tingting LuSchool of International and Public Affairs & China Institute for Urban Governance, Shanghai Jiao Tong University, China.
East China Normal University · CNShanghai Jiao Tong University · CNTsinghua University · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic is a governance challenge for nations and cities across the world. While early observations have primarily focused on government actions, neighborhoods are at the frontline for coordinating grassroots level joint actions to fight against the pandemic. We draw from the collaborative governance theory and develop a theoretical framework for understanding the horizontal and hierarchical dynamics of collaborative neighborhood governance during crisis responses in urban China. Using a large-scale questionnaire survey of frontline community workers operated in six Chinese cities in February 2020, we conduct statistical analyses and find that the effectiveness of neighborhood collaboration in the pandemic control is predicted by both neighborhood social capital (i.e. civic engagement and citizen participation) and hierarchical steering by the government through setting policy priorities and providing support. Our research contributes to the international literature on neighborhood governance dynamics and provides policy lessons for improving neighborhood governance capacity in crisis response situations.

Indexed as

ChinaCollaborative governanceCOVID-19Neighborhood governancePublic health crisisResidents' committees

Identifiers

PMID36471788
PMCPMC9712009
OpenAlexW3164909408

What OpenQuestion holds

Textmetadata
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.