ArticleF1000Research2021
Understanding the funding characteristics of research impact: A proof-of-concept study linking REF 2014 impact case studies with Researchfish grant agreements.
Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Exploring the application of machine learning to expert evaluation of research impact.PloS one · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAll parts of the research community have an interest in understanding research impact whether that is around the pathways to impact, processes around impact, methods for measurement, describing impact and so on. This proof of concept study explored the relationship between research funding and research impact using the case studies submitted to the UK Research Excellence Framework (REF) exercise in 2014 as a proxy for impact.
methodsThe paper describes an approach to link the REF impact case studies with the underpinning research grants present in the Researchfish dataset, primarily using the publications captured in both datasets. Where possible the methodology utilised unique identifiers such as Digital Object Identifiers and PubMed ID's, and where this was not possible the funding information within each publication was used.
resultsThrough this automated approach 21% of the non-redacted case studies could be linked to a specific research grant. Additional qualitative analysis was then done for unlinked REF impact case studies, which involved reading the document to identify additional information to make the linkage. This approach was taken on 100 REF impact case studies selected at random and resulted in only seven having no identifiable research grants funding associated. The linked research grants were analysed to identify characteristics that are more frequently associated with these grants, than non-linked ones.
conclusionsThis analysis did point to some interesting observations such as the grant funding linked to REF impact case studies are more likely to be longer, higher financial value, have more publications and be more collaborative (amongst other characteristics). These findings should be used with caution at present and not be over interpreted, this is due to the sample size for this proof of concept study and some potential limitations on the data which were not addressed at this stage.
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Identifiers
What OpenQuestion holds
Registered trials
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.