Page 383 - Invited Paper Session (IPS) - Volume 1

IPS169 Gaby U.
• and serve various other instrumental, conceptual, tactical, symbolic
and political purposes.
Moreover, measuring itself turned into an essential ‘way of doing politics’
(Malito, Bhuta, and Umbach 2018, 511), justifying and rationalising political
decisions and making progress visible and comparable. Statistics are, hence,
an essential part of governing with and through knowledge to bring ‘objective
consistency’ (Desrosières 1998, 32) of social phenomena into politics. As such,
statistics are important means of identifying policy requirements and of
holding decision-makers accountable for their policy choices. In this way, the
use of data evidence increases transparency of policy choices and can
therefore be regarded as the factual fifth power in evidence-based policy-
st
making in the 21 century.

Issues of Governing through Numbers and Challenges for Data Providers:
Limitations of Data as Factual Evidence
Increasing a post-metrological trend in EBPM, new forms of evidence and
(robust) knowledge have yet entered in competition with official statistics. Such
new forms include evidence not based on narrow scientific definitions or other
knowledge claims and propositions about the factual world. Increasing the
plurality of knowledge sources are experimental studies (such as randomised
controlled trials); observational qualitative and quantitative studies to identify
causal mechanisms; functional models; modelling; normative deduction from
principle norms; citizens and practice-informed knowledge or indigenous
knowledge and experience. While such new evidence sources need to show a
convincing degree of validity and reliability, levels of uncertainty and room for
interpretation remain, influencing the authority/contestation of evidence and
resulting in a (multidimensional) knowledge hierarchy for EBPM. A classification
(i.e. abstract, practical, subjective) and quality assessment (i.e. narrative,
storytelling, data, anecdotal) of knowledge as well as ‘systematic linkages
between context and evidence type” of knowledge necessarily follow (Bannister
& O’Sullivan 2014; see also Epstein et al. 2014).
A divide over measurement flaws and conceptual approaches
accompanies this multiplication of evidence sources that also unveils
challenges of previous one-size-fits-all measures that are not entirely
actionable or do not provide policy-relevant information. Resulting from the
proliferation of evidence and knowledge sources, official (aggregate) statistics
are complemented by more disaggregate, micro-level, local experience-based
measures to support the development of more targeted policy interventions.
At the expense of comparability, the latter are more targeted to trigger action
and steer reforms and decision-making on the ground.
Another challenge for data as evidence in policy-making lies within their
alleged objectivity: by definition, statistics define normalcy and deviancy and

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