Recent philosophical literature has turned its attention towards assessments of how to judge scientific proposals as worthy of further inquiry. Previous work, as well as papers contained within this special issue, propose criteria for pursuitworthiness (Achinstein, 1993; Whitt, 1992; DiMarco & Khalifa, 2019; Laudan, 1977; Shan, 2020; Šešelja et al., 2012). The purpose of this paper is to assess the grounds on which pursuitworthiness demands can be legitimately made. To do this, I propose a challenge to the possibility of even (...) minimal criteria of pursuitworthiness, inspired by Paul Feyerabend. I go on to provide a framework for identifying the contexts in which pursuitworthiness criteria may promote the efficiency of scientific inquiry. I then spell out some implications this framework has for values and pursuit. (shrink)

The purpose of grant peer review is to identify the most excellent and promising research projects. However, sociologists of science and STS scholars have shown that peer review tends to promote solid low-risk projects at the expense of more original and innovative projects that often come with higher risk. It has also been shown that the review process is affected by significant measures of chance. Against this background, the aim of this study is to theorize the notions of academic judgment (...) and agonistic chance, and to present and analyze situations in which expert reviewers are faced with the challenge of trying to decide which grant proposals to select when there is strong disagreement. The empirical analysis is based on ethnographic observations of ten panel groups at the Swedish Research Council in the areas of natural and engineering sciences. By focusing on disagreement, the study provides a more in-depth understanding of how agonistic chance creeps into the peer review process and becomes part of the consensus that is created. (shrink)

Philosophers of science have argued that epistemic diversity is an asset for the production of scientific knowledge, guarding against the effects of biases, among other advantages. The growing privatization of scientific research, on the contrary, has raised important concerns for philosophers of science, especially with respect to the growing sources of biases in research that it seems to promote. Recently, Holman and Bruner ( 2017 ) have shown, using a modified version of Zollman ( 2010 ) social network model, that (...) an industrial selection bias can emerge in a scientific community, without corrupting any individual scientist, if the community is epistemically diverse. In this paper, we examine the strength of industrial selection using a reinforcement learning model, which simulates the process of industrial decision-making when allocating funding to scientific projects. Contrary to Holman and Bruner’s model, in which the probability of success of the agents when performing an action is given a priori, in our model the industry learns about the success rate of individual scientists and updates the probability of success on each round. The results of our simulations show that even without previous knowledge of the probability of success of an individual scientist, the industry is still able to disrupt scientific consensus. In fact, the more epistemically diverse the scientific community, the easier it is for the industry to move scientific consensus to the opposite conclusion. Interestingly, our model also shows that having a random funding agent seems to effectively counteract industrial selection bias. Accordingly, we consider the random allocation of funding for research projects as a strategy to counteract industrial selection bias, avoiding commercial exploitation of epistemically diverse communities. (shrink)

The way research is, and should be, funded by the public sphere is the subject of renewed interest for sociology, economics, management sciences, and more recently, for the philosophy of science. In this contribution, I propose a qualitative, epistemological criticism of the funding by lottery model, which is advocated by a growing number of scholars as an alternative to peer-review. This lottery scheme draws on the lack of efficiency and of robustness of the peer-review based evaluation to argue that the (...) majority of public resources for basic science should be allocated randomly. I first differentiate between two distinct arguments used to defend this alternative funding scheme based on considerations about the logic of scientific research. To assess their epistemological limits, I then present and develop a conceptual frame, grounded on the notion of “system of practice”, which can be used to understand what precisely it means, for a research project, to be interesting or significant. I use this epistemological analysis to show that the lottery model is not theoretically optimal, since it underestimates the integration of all scientific projects in densely interconnected systems of conceptual, experimental, or technical practices which confer their proper interest to them. I also apply these arguments in order to criticize the classical peer-review process. I finally suggest, as a discussion, that some recently proposed models that bring to the fore a principle of decentralization of the evaluation and selection process may constitute a better alternative, if the practical conditions of their implementation are adequately settled. (shrink)