TY - GEN
T1 - Policy-Relevant Science
T2 - 11th International Conference on Complex Networks, CompleNet 2020
AU - Desmarais, Bruce A.
AU - Hird, John A.
N1 - Funding Information:
This work was supported in part by NSF grants 1558661, 1637089, 1619644, and 1360104. The data and code used in this study can be downloaded at https://doi. org/10.7910/DVN/IY9B1T.
Funding Information:
The complete policy-science network we construct is visualized in Fig. 1. The network includes 104 RIAs and 823 scientific articles. As can be seen, EPA is the most regular user of scientific research. There is little cross-agency and even cross-RIA overlap in the science that is used, outside of EPA. In what follows, we study the support of the research represented in this network, identifying the funders and affiliations behind the bulk of the research, and pay particular attention to the supporters of research that span multiple RIAs. In Fig. 2 we present the list of the most prominent funders and author affiliations associated with articles cited. In terms of affiliations, we see a list of several elite universities including Harvard, Yale, Cornell, Columbia and Duke, as well as the most research-active government agency, the Environmental Protection Agency, and Canada’s large government agency responsible for public health policy: Health Canada. In terms of funders, we see a list of the prominent governmental research sponsors in the US, Canada, Europe and California, including the National Science Foundation, the National Institutes of Health, EPA, the National Science and Engineering Research Council of Canada, and the European Commission. These results are largely unsurprising: the supporters of research that are associated with the large volume of scientific publications cited in RIAs include elite research universities and the largest funders of research on the planet. However, analyzing just the volume of citations leaves out an important component of the impact story: the diversity of policy that is informed by scientific research. Seen from the perspective of the supporter of the research, the return on investment in terms of policy impact depends heavily on the breadth of policy areas influenced by individual articles.
Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Proponents of basic science argue that objective scientific understanding can inform improvement in public policy. We gather data on scientific research cited in official benefit-cost analyses produced by US federal regulatory agencies to justify policy decisions between 2008 and 2012. We construct a science-policy network in which benefit-cost analyses and the studies they cite are the nodes, and citations represent the edges. We assess two features of each scientific publication in the network; how frequently is it used; and how broadly it spans across the network, as measured by betweenness centrality. We ask which author affiliations and funders are associated with the best-cited and farthest spanning publications. Elite universities and major government funders support publications that are most heavily cited, but the farthest spanning articles are written by scientists with non-academic affiliations and sponsored by non-governmental funders. These results suggest that bias towards academically affiliated investigators should be scrutinized by major funding organizations if a major objective is to support science that is used by policymakers.
AB - Proponents of basic science argue that objective scientific understanding can inform improvement in public policy. We gather data on scientific research cited in official benefit-cost analyses produced by US federal regulatory agencies to justify policy decisions between 2008 and 2012. We construct a science-policy network in which benefit-cost analyses and the studies they cite are the nodes, and citations represent the edges. We assess two features of each scientific publication in the network; how frequently is it used; and how broadly it spans across the network, as measured by betweenness centrality. We ask which author affiliations and funders are associated with the best-cited and farthest spanning publications. Elite universities and major government funders support publications that are most heavily cited, but the farthest spanning articles are written by scientists with non-academic affiliations and sponsored by non-governmental funders. These results suggest that bias towards academically affiliated investigators should be scrutinized by major funding organizations if a major objective is to support science that is used by policymakers.
UR - http://www.scopus.com/inward/record.url?scp=85081215345&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081215345&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40943-2_32
DO - 10.1007/978-3-030-40943-2_32
M3 - Conference contribution
AN - SCOPUS:85081215345
SN - 9783030409425
T3 - Springer Proceedings in Complexity
SP - 385
EP - 392
BT - Complex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020
A2 - Barbosa, Hugo
A2 - Menezes, Ronaldo
A2 - Gomez-Gardenes, Jesus
A2 - Gonçalves, Bruno
A2 - Mangioni, Giuseppe
A2 - Oliveira, Marcos
PB - Springer
Y2 - 31 March 2020 through 3 April 2020
ER -