Evidence map›Paper›PMID 35987899›Full record

ArticleNature communications2022

Untangling the network effects of productivity and prominence among scientists.

Weihua Li, Sam Zhang, Zhiming Zheng, Skyler J Cranmer, Aaron Clauset

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Unequal Scientific Recognition in the Age of LLMs.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2025
    Article
  4. Article
  5. Article
  6. Gender and racial diversity socialization in science.Nature computational science · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Collective dynamics behind success.Nature communications · 2024
    Review
  12. Article
  13. Article
  14. Productive scientists are associated with lower disruption in scientific publishing.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  15. Elements of successful NIH grant applications.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  16. Article
  17. 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

5 authors.

Weihua LiLMIB, NLSDE, BDBC, and Institute of Artificial Intelligence, Beihang University, 100191, Beijing, China. weihuali@buaa.edu.cn.ORCID http://orcid.org/0000-0003-1303-1132
Sam ZhangDepartment of Applied Mathematics, University of Colorado Boulder, Boulder, CO, 80309, USA.ORCID http://orcid.org/0000-0002-0371-9526
Zhiming ZhengLMIB, NLSDE, BDBC, and Institute of Artificial Intelligence, Beihang University, 100191, Beijing, China.
Skyler J CranmerDepartment of Political Science, The Ohio State University, Columbus, OH, 43210, USA.
Aaron ClausetDepartment of Computer Science, University of Colorado, Boulder, CO, 80309, USA. aaron.clauset@colorado.edu.ORCID http://orcid.org/0000-0002-3529-8746

Funding

Development of a statistical framework for the analysis of social network predictors of therapeutic community outcomesR34DA043079 · NIDA · OHIO STATE UNIVERSITY · PI WARREN, KEITH LEVERETT · 2018 to 2020
$690k
NIDA NIH HHS R34 DA043079
6 · The paper itself

Abstract

While inequalities in science are common, most efforts to understand them treat scientists as isolated individuals, ignoring the network effects of collaboration. Here, we develop models that untangle the network effects of productivity defined as paper counts, and prominence referring to high-impact publications, of individual scientists from their collaboration networks. We find that gendered differences in the productivity and prominence of mid-career researchers can be largely explained by differences in their coauthorship networks. Hence, collaboration networks act as a form of social capital, and we find evidence of their transferability from senior to junior collaborators, with benefits that decay as researchers age. Collaboration network effects can also explain a large proportion of the productivity and prominence advantages held by researchers at prestigious institutions. These results highlight a substantial role of social networks in driving inequalities in science, and suggest that collaboration networks represent an important form of unequally distributed social capital that shapes who makes what scientific discoveries.

Indexed as

Research PersonnelSocial NetworkingHumans

Identifiers

PMID35987899
PMCPMC9392727

What OpenQuestion holds

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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.