Evidence map›Paper›PMID 33734086›Full record

ArticleeLife2021

Weak evidence of country- and institution-related status bias in the peer review of abstracts.

Mathias Wullum Nielsen, Christine Friis Baker, Emer Brady, Michael Bang Petersen, Jens Peter Andersen

Abstract read
In one paragraph

Article in eLife, 2021. 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

5 authors.

Mathias Wullum NielsenDepartment of Sociology, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0001-8759-7150
Christine Friis BakerDanish Centre for Studies in Research and Research Policy, Department of Political Science, Aarhus University, Aarhus, Denmark.ORCID 0000-0002-3370-021X
Emer BradyDanish Centre for Studies in Research and Research Policy, Department of Political Science, Aarhus University, Aarhus, Denmark.ORCID 0000-0002-6065-8096
Michael Bang PetersenDepartment of Political Science, Aarhus University, Aarhus University, Denmark.ORCID 0000-0002-6782-5635
Jens Peter AndersenDanish Centre for Studies in Research and Research Policy, Department of Political Science, Aarhus University, Aarhus, Denmark.ORCID 0000-0003-2444-6210

Funding

Aarhus Universitets Forskningsfond AUFF-F-2018-7-5Carlsbergfondet CF19-0566
6 · The paper itself

Abstract

Research suggests that scientists based at prestigious institutions receive more credit for their work than scientists based at less prestigious institutions, as do scientists working in certain countries. We examined the extent to which country- and institution-related status signals drive such differences in scientific recognition. In a preregistered survey experiment, we asked 4,147 scientists from six disciplines (astronomy, cardiology, materials science, political science, psychology and public health) to rate abstracts that varied on two factors: (i) author country (high status vs lower status in science); (ii) author institution (high status vs lower status university). We found only weak evidence of country- or institution-related status bias, and mixed regression models with discipline as random-effect parameter indicated that any plausible bias not detected by our study must be small in size.

Indexed as

Abstracting and IndexingAstronomyCardiologyGeographyHumansLaboratory PersonnelLinear ModelsMaterials SciencePeer ReviewPsychologyPublication BiasPublic HealthSurveys and QuestionnairesUniversitieshalo effectmeta-researchnonepeer reviewstatus biassurvey experiment

Identifiers

PMID33734086
PMCPMC8009675

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.