What is it about?
These are the salient points of this work: 1) There is a crisis of science’s governance, affecting science’s reproducibility, scientific peer review and science’s integrity. 2) How can this crisis affect evidence based policy? 3) Current evidence based policy exercises entail forms of quantification which constrict the issue into narrow normative windows. 4) This closure of a given issue in a pre-established frame may corresponds to a selected normative – political stance. 5) This closure is assisted by the use of mathematical modelling and indicators. Often these convey a spurious impression of precision, prediction and control. 6) Better styles of evidence based policy should make explicit the existence of ‘uncomfortable knowledge’. 7) We suggested a strategy – which we name Quantitative Story Telling − to achieve this opening of the space of possible narratives. 8) QST screens available narratives by the attempt to refute frames that violate constraints of feasibility (compatibility with processes outside human control); viability (compatibility with processes under human control), and desirability (compatibility with a plurality of normative considerations relevant to the system’s actors). 9) Like NUSAP (www.nusap.net) and Sensitivity Auditing (https://en.wikipedia.org/wiki/Sensitivity_auditing) before it, QST is inspired by post-normal-science (https://en.wikipedia.org/wiki/Post-normal_science) theory and practice.
Why is it important?
As presently run evidence based policy may result in a dramatic simplification of the available perceptions, in flawed policy prescriptions and in the neglect of other relevant world views of legitimate stakeholders. This use of scientific method ultimately generates – rather than resolving – controversies and erodes the institutional trust of the involved actors by reinforcing existing asymmetries in information and power.
The following have contributed to this page: Professor Andrea Saltelli