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Studying grant decision-making: a linguistic analysis of review reports

Overview of attention for article published in Scientometrics, July 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 2,962)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

blogs
3 blogs
policy
2 policy sources
twitter
123 X users
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
71 Mendeley
Title
Studying grant decision-making: a linguistic analysis of review reports
Published in
Scientometrics, July 2018
DOI 10.1007/s11192-018-2848-x
Pubmed ID
Authors

Peter van den Besselaar, Ulf Sandström, Hélène Schiffbaenker

Abstract

Peer and panel review are the dominant forms of grant decision-making, despite its serious weaknesses as shown by many studies. This paper contributes to the understanding of the grant selection process through a linguistic analysis of the review reports. We reconstruct in that way several aspects of the evaluation and selection process: what dimensions of the proposal are discussed during the process and how, and what distinguishes between the successful and non-successful applications? We combine the linguistic findings with interviews with panel members and with bibliometric performance scores of applicants. The former gives the context, and the latter helps to interpret the linguistic findings. The analysis shows that the performance of the applicant and the content of the proposed study are assessed with the same categories, suggesting that the panelists actually do not make a difference between past performance and promising new research ideas. The analysis also suggests that the panels focus on rejecting the applications by searching for weak points, and not on finding the high-risk/high-gain groundbreaking ideas that may be in the proposal. This may easily result in sub-optimal selections, in low predictive validity, and in bias.

X Demographics

X Demographics

The data shown below were collected from the profiles of 123 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Other 8 11%
Student > Ph. D. Student 7 10%
Professor 6 8%
Student > Doctoral Student 4 6%
Other 17 24%
Unknown 13 18%
Readers by discipline Count As %
Social Sciences 18 25%
Computer Science 6 8%
Business, Management and Accounting 4 6%
Psychology 4 6%
Agricultural and Biological Sciences 3 4%
Other 16 23%
Unknown 20 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 105. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2023.
All research outputs
#408,401
of 25,732,188 outputs
Outputs from Scientometrics
#37
of 2,962 outputs
Outputs of similar age
#8,723
of 341,115 outputs
Outputs of similar age from Scientometrics
#1
of 63 outputs
Altmetric has tracked 25,732,188 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,962 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,115 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.