TY - JOUR
T1 - A new approach for estimating research impact
T2 - An application to french cancer research
AU - Chevalier, Gérard
AU - Chomienne, Christine
AU - Jeanrenaud, Nicolas Guetta
AU - Lane, Julia
AU - Ross, Matthew
N1 - Funding Information:
Funding agencies also typically do not have a way of tracing the research activity of scientists both before and after the award of a grant (i.e., the initial results of funding). To construct data on research output prior to funding, we worked closely with the ORCID7 organization. ORCID is an established researcher identifier registry used by over 6 million researchers. ORCID enables individuals to register for a unique identifier and connect it with their activities and affiliations in common research workflows such as grant applications, publication submissions, peer review, and data set deposits. Researchers control their record and may share their information publicly. Many research funders are starting to adopt the use of ORCID, including INCa and the U.S.
Funding Information:
The data are from five different agencies in four countries: the United States National Cancer Institute, Cancer Research UK, Wellcome Trust, the Australian National Health and Medical Research Council, and cancer research funded programs by the French National Cancer Institute (INCa), the French National Alliance of Life Sciences and Health (AVIESAN) through the Institut National de la Santé et de la Recherche Médicale (INSERM), and the Ministry of Health through its Direction Générale de l’Offre de Soins (DGOS) between 2007 and 2012. Two of the agencies are cancer-specific (Cancer Research UK and National Cancer Institute): For those, all awards are considered. Wellcome Trust and the National Health and Medical Research Council, however, are general funding bodies for all medical research: To restrict our analysis to cancer-related grants, we used a machine learning classification process based on a system developed for the U.S. National Institutes of Health (the RCDC classification).
Publisher Copyright:
© 2020 Gérard Chevalier, Christine Chomienne, Nicolas Guetta Jeanrenaud, Julia Lane, and Matthew Ross.
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Much attention has been paid to estimating the impact of investments in scientific research. Historically, those efforts have been largely ad hoc, burdensome, and error prone. In addition, the focus has been largely mechanical—drawing a direct line between funding and outputs— rather than focusing on the scientists that do the work. Here, we provide an illustrative application of a new approach that examines the impact of research funding on individuals and their scientific output in terms of publications, citations, collaborations, and international activity, controlling for both observed and unobserved factors. We argue that full engagement between scientific funders and the research community is needed if we are to expand the data infrastructure to enable a more scientific assessment of scientific investments.
AB - Much attention has been paid to estimating the impact of investments in scientific research. Historically, those efforts have been largely ad hoc, burdensome, and error prone. In addition, the focus has been largely mechanical—drawing a direct line between funding and outputs— rather than focusing on the scientists that do the work. Here, we provide an illustrative application of a new approach that examines the impact of research funding on individuals and their scientific output in terms of publications, citations, collaborations, and international activity, controlling for both observed and unobserved factors. We argue that full engagement between scientific funders and the research community is needed if we are to expand the data infrastructure to enable a more scientific assessment of scientific investments.
KW - HELIOS
KW - Research impact
KW - Science data infrastructure
KW - Science impact
UR - http://www.scopus.com/inward/record.url?scp=85117797508&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85117797508&partnerID=8YFLogxK
U2 - 10.1162/qss_a_00087
DO - 10.1162/qss_a_00087
M3 - Article
AN - SCOPUS:85117797508
SN - 2641-3337
VL - 1
SP - 1586
EP - 1600
JO - Quantitative Science Studies
JF - Quantitative Science Studies
IS - 4
ER -