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Interdisciplinary researchers attain better long-term funding performance

Sun, Ye, Livan, Giacomo, Ma, Athen and Latora, Vito (2021) Interdisciplinary researchers attain better long-term funding performance. Communications Physics, 4 (1). ISSN 2399-3650

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Identification Number: 10.1038/s42005-021-00769-z

Abstract

Interdisciplinary research is on the rise globally. Yet, several studies have shown that it often achieves lower impact compared to more specialized work, and is less likely to attract funding. Here, we seek to reconcile such evidence by analyzing 44,419 research grants awarded by the research councils in the UK. We find that researchers with an interdisciplinary funding track record dominate the network of academic collaborations, both in terms of centrality and knowledge brokerage, but such a competitive advantage does not translate into immediate return. Our results based on a matched pair analysis show that interdisciplinary researchers achieve lower impact with their publications in the short run; however, they eventually outperform their specialized counterparts in funding performance, both in terms of volume and value. These findings suggest that pursuing an interdisciplinary career may require perseverance to overcome extra challenges, but can pave the way for a more successful endeavor.

Item Type: Article
Additional Information: Funding Information: terms of long-term funding performance of cross-council (orange) and within-council (blue) principal investigators (PIs) with similar funding profiles. Both PIs obtained 2 research grants during the in-sample period from 2006 to 2010, but the within-council PI received grants from the same research council (both from Economic and Social Research Council (ESRC)), while the cross-council PI received grants from 2 different councils (one from Engineering and Physical Sciences Research Council (EPSRC), and the other from Biotechnology and Biological Sciences Research Council (BBSRC)). For the in-sample period 2006–2010, we pair the PIs with similar career profiles, while for the out-of-sample period 2011–2018, we compare the funding performance of each paired PIs. b Matching the cross-council and within-council PIs with similar career profiles in terms of both funding performance and research outcomes during the in-sample period. We match 8 different factors for PIs between 2006 and 2010 as follows: institutional ranking of a given PI (whereby institutions are ranked by their total amount of funding between 2006 and 2018), the number of grants a given PI has received, their average grant value, average team size, average project duration, average number of publications reported, average number of total citations received per grant (calculated as the average of the total citations received by papers associated with a grant), and the average number of citations received per paper per grant (calculated first as the average of the citations received by papers associated with a grant, and then averaged over the total number of grants awarded to a PI). Citations are considered within 5 years after publication, and have been normalized by the average citations of all papers belonging to the same year and discipline in Microsoft Academic Graph dataset. There is no statistically significant difference between the two groups of PIs across the eight factors following the pairing. The shaded areas represent the 95% confidence interval. c Difference in long-term funding performance between cross-council and within-council PIs in the following eight years (2011 to 2018). Cross-council PIs outperform within-council PIs in grant volume, value and team size. The significance levels shown refer to t-tests and Kruskal-Wallis tests. ***p < 0.01, **p < 0.05, *p < 0.1. Error bars represent the standard error of the mean. Funding Information: Fig. 1 Time evolution of the funding landscape. a The typical number of team members per grant shows a significant increase over time. b The average number of affiliations participating in each grant grows with time. c The average number of subjects listed in each grant continues to rise over time. In panels a to c, the error bars indicate 95% confidence intervals. d The fraction of cross-council investigators increases over time. In panels a to d, the solid line and the shaded area represent the regression line and 95% confidence intervals, respectively. Each regression has also been annotated with the corresponding Pearson’s r. ***p < 0.01, **p <0.05, *p < 0.1. e, f The co-activity network of investigators in two time windows, 2006–2008 and 2016–2018. Node sizes are proportional to the number of investigators that have received funding from each research council. Two councils are connected if they have both supported at least one investigator, and the link width is weighted by the ratio between the observed number of investigators funded in both councils and the expected number based on a randomized null model. Here, seven research councils are considered: Arts and Humanities Research Council (AHRC), Biotechnology and Biological Sciences Research Council (BBSRC), Economic and Social Research Council (ESRC), Engineering and Physical Sciences Research Council (EPSRC), Medical Research Council (MRC), Natural Environment Research Council (NERC) and Science and Technology Facilities Council (SFTC). Compared to 2006–2008, the links with increased weights in 2016–2018 have been highlighted in red. g, h The percentage of cross-council investigators in different institutional tiers and periods. Here, the research institutions are stratified into two tiers by checking whether their total awarded funding is larger than the average amount per institution (i.e., 1.02 × 108). Box widths are proportional to the number of investigators in Tier I and Tier II, respectively. Box heights are proportional to the percentage of cross-council and within-council investigators. The institutions in Tier I have a higher proportion of cross-council investigators than those in Tier II in both 3-y time windows (χ2 test p < 0.0001, odds ratio = 1.67 for 2006–2008; p < 0.0001, odds ratio = 1.28 for 2016–2018). The same conclusions have been reached when different time window lengths and different criteria of institutional stratification have been used (see Supplementary Note 4). Publisher Copyright: © 2021, The Author(s).
Divisions: Systemic Risk Centre
Date Deposited: 03 May 2024 23:19
Last Modified: 16 May 2024 23:42
URI: http://eprints.lse.ac.uk/id/eprint/122911

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