Abstract
The relevance and impact of political scientists’ professional activities outside of universities has become the focus of public attention, partly due to growing expectations that research should help address society’s grand challenges. One type of such activity is policy advising. However, little attention has been devoted to understanding the extent and type of policy advising activities political scientists engage in. This paper addresses this gap by adopting a classification that distinguishes four ideal types of policy advisors representing differing degrees of engagement. We test this classification by calculating a multi-level latent class model to estimate key factors explaining the prevalence of each type based on an original dataset obtained from a survey of political scientists across 39 European countries. Our results challenge the wisdom that political scientists are sitting in an “ivory tower”: the vast majority (80%) of political scientists in Europe are active policy advisers, with most of them providing not only expert guidance but also normative assessments.
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Data availability
The dataset is available online through GESIS: https://doi.org/10.7802/2564
Notes
While we agree with one of the reviewers that the label “opinionating” could be perceived negatively by some, we want to highlight that it is not meant in a judgemental way. We kept the label for the sake of consistency with the initial conceptualization as proposed by Brans et al. (2022b).
COST Action CA15207: PROSEPS Professionalization and Social Impact of European Political Science, see: http://proseps.unibo.it/
Besides these two criteria, country experts could use additional criteria in accordance with the demarcation of the discipline in their country.
As noted by one of the reviewers, of particular concern is that participation in our survey might be correlated with engagement in policy advice (i.e., that a political scientist more/less actively involved in policy advice may be more/less likely to fill out the questionnaire), which would obviously undermine the generalizability of our findings. A first look at our data suggests that this does not seem to be the case, as roughly half of the respondents in our sample are never or only rarely involved in policy advising. Nonetheless, in order to address this concern in a more “statistically principled” manner, we resort to propensity-based adjustments (Lee 2006) to account for potential selection bias. See the Online Appendix (Section B) for details.
Section A in the Additional file 1: Online Appendix provides country-specific summary statistics for the dependent and key independent variables included in our analysis.
Some of the advantages of the Bayesian framework in this setting are that it allows for a detailed description of the parameters of interest via examination of their posterior distributions, and that it helps account for the uncertainty in these parameters while avoiding asymptotic approximations—a convenient feature given that the number of individuals assigned to each advisory type could in principle be rather small (e.g., Iaryczower and Katz 2015). Additional estimation details are provided in the Online Appendix (Section B).
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Jungblut, J., Gouglas, A., Katz, G. et al. Out of the ivory tower: an explanation of the policy advisory roles of political scientists in Europe. Eur Polit Sci (2023). https://doi.org/10.1057/s41304-023-00440-x
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DOI: https://doi.org/10.1057/s41304-023-00440-x