Evidence map›Paper›PMID 26097258›Full record

ArticleMinerva

Accounting for Impact? The Journal Impact Factor and the Making of Biomedical Research in the Netherlands.

Alexander Rushforth, Sarah de Rijcke

Abstract read
In one paragraph

Article in Minerva. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Filling in the gaps: The interpretation ofSocial studies of science · 2019
    Article
  10. Beyond Trust: Plagiarism and Truth.Journal of bioethical inquiry · 2018
    Article
  11. Article
  12. Article
  13. Article
  14. The Value of Vagueness in the Politics of Authorship.Journal of bioethical inquiry · 2017
    Article
  15. Article
  16. 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

2 authors.

Alexander RushforthCenter for Science and Technology Studies (CWTS), Leiden University, P.O. Box 905, 2300 AX Leiden, The Netherlands.
Sarah de RijckeCenter for Science and Technology Studies (CWTS), Leiden University, P.O. Box 905, 2300 AX Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The range and types of performance metrics has recently proliferated in academic settings, with bibliometric indicators being particularly visible examples. One field that has traditionally been hospitable towards such indicators is biomedicine. Here the relative merits of bibliometrics are widely discussed, with debates often portraying them as heroes or villains. Despite a plethora of controversies, one of the most widely used indicators in this field is said to be the Journal Impact Factor (JIF). In this article we argue that much of the current debates around researchers' uses of the JIF in biomedicine can be classed as 'folk theories': explanatory accounts told among a community that seldom (if ever) get systematically checked. Such accounts rarely disclose how knowledge production itself becomes more-or-less consolidated around the JIF. Using ethnographic materials from different research sites in Dutch University Medical Centers, this article sheds new empirical and theoretical light on how performance metrics variously shape biomedical research on the 'shop floor.' Our detailed analysis underscores a need for further research into the constitutive effects of evaluative metrics.

Indexed as

BibliometricsBiomedicineJournal Impact FactorPerformance indicatorsResearch evaluation

Identifiers

PMID26097258
PMCPMC4469321

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.