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IPS169 Gaby U.
development of policy solutions also requires a broader, if not holistic, and in
any case multidimensional approach to cover the facets of the political
challenges at hand.
This increase of complexity goes hand-in-hand with an increasing
contestation of expertise and experts leading to the paradoxical situation that
‘expert advice is being sought with growing urgency across a proliferating
array of policy and public questions. At the same time, and often on the same
issues, the legitimacy of evidence and expertise has rarely been so fiercely
contested’ (Gluckman and Wilsdon 2016). The gap between demand for and
(contestation of) supply of data evidence and expertise hence widens to an
alarming extent for the data science and policy-making communities.
Increased research activities on trust in politics and data science
communication are hence necessary.

References
1. Bannister, J., & O’Sullivan, A. (2014). Evidence and the antisocial behaviour
policy cycle. Evidence & Policy, 10(1), 77–92.
2. Bhuta, N., Malito, D. V., & Umbach, G. (2014). Representing, Reducing or
Removing Complexity: Indicators of Sustainability and Fiscal
Sustainability (Robert Schuman Centre for Advanced Studies Working
Paper, 2014/78). Florence: European University Institute.
3. Bowker, G. C., & Susan Leigh Star, S. (1999). Sorting Things Out:
Classification and Its Consequences. Cambridge, MA: MIT Press.
4. Bradley, C. (2015). International Organizations and the Production of
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Corruption, and Rule of Law (pp. 27-74). Cambridge: Cambridge
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6. Cairney, Paul (2016). The Politics of Evidence-Based Policy Making,
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the divide between evidence and policy? Health Research Policy and
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8. Castellani, T., Valente, A., Cori, L., & Bianchi, F. (2016). Detecting the use
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9. Chalmers, Iain (2005): If evidence-informed policy works in practice, does
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