A Simple, Systematic and Integrity-preserving Model for Values in Science

  • Period: 2022-09-01 – 2024-08-31
  • Funder: Vinnova/Marie Skłodowska-Curie European Postdoctoral Fellowship, funded by the European Research Executive Agency
  • Type of funding: Project grant

Abstract

In the face of controversial debates about appropriate influence of values in the assent phase of science (where hypotheses/theories are accepted or rejected), which provide only complicated guidelines on a case-by-case basis, a confused image of science arises in the view of policy makers, the wider public, and even scientists. Such unsettled debate has a potential negative impact on the trust the general public puts in science. Worse, it can be used by science deniers to support their undermining enterprise. This is why progress on this issue is of paramount importance. A simple and systematic model for incorporating values in the assent phase of science, while at the same time preserving its integrity, is sorely needed. This is what this project aims to achieve.

  1. The project will start with a systematic analysis of the philosophical debate about values in science, in order to make an inventory and classify the various positions according to criteria such as value-freedom or value-ladenness, kinds of value, types of influence, priority of some values over others, etc.
  2. Among these, a selection, at the conceptual level, will be made of the best candidate for a simple, systematic and integrity- preserving value-laden model -- which is the main methodological assumption of this project.
  3. This model will be criticized and optimized, at the conceptual level (for both theoretical and practical goals), by providing: possible adjustments, complementations, objections, or simplifications.
  4. This model will be confronted to empirical case studies, to illustrate, expand or revise it. Three case studies will be performed: in aeronautical engineering, climate science and medical science.
  5. Finally, the conceptual and empirical findings will be synthesized to reach an optimized (simple, systematic and integrity-preserving) model.

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