Policy-Relevant Science: The Depth and Breadth of Support Networks

Bruce A. Desmarais, John A. Hird

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publicationComplex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020
EditorsHugo Barbosa, Ronaldo Menezes, Jesus Gomez-Gardenes, Bruno Gonçalves, Giuseppe Mangioni, Marcos Oliveira
Number of pages8
ISBN (Print)9783030409425
StatePublished - 2020
Event11th International Conference on Complex Networks, CompleNet 2020 - Exeter, United Kingdom
Duration: Mar 31 2020Apr 3 2020

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692


Conference11th International Conference on Complex Networks, CompleNet 2020
Country/TerritoryUnited Kingdom

All Science Journal Classification (ASJC) codes

  • Applied Mathematics
  • Modeling and Simulation
  • Computer Science Applications


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