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This paper discusses the so-called non-interference assumption (NIA) grounding causal inference in trials in both medicine and the social sciences. It states that for each participant in the experiment, the value of the potential outcome depends only upon whether she or he gets the treatment. Drawing on methodological discussion in clinical trials and laboratory experiments in economics, I defend the necessity of partial forms of blinding as a warrant of the NIA, to control the participants' expectations and their strategic interactions with the experimenter.

AbstractBreeds are classifications of domestic animals that share, to a certain degree, a set of conventional phenotypic traits. We are going to defend that, despite classifying biological entities, animal breeds are social kinds. We will adopt Godman's view of social kinds, classifications with predictive power based on social learning processes. We will show that, although the folk concept of animal breed refers to a biological kind, there is no way to define it. The expert definitions of breeds are instead based on socially learnt conventions and skills (artificial selection), yielding groupings in which scientific predictions are possible. We will discuss in what sense breeds are social, but not human kinds and in what sense the concept of a breed is necessary to make them real.

Over the last decade, philosophers of science have extensively criticized the epistemic superiority of randomized controlled trials (RCTs) for testing safety and effectiveness of new drugs, defending instead various forms of evidential pluralism. We argue that scientific methods in regulatory decision-making cannot be assessed in epistemic terms only: there are costs involved. Drawing on the legal distinction between rules and standards, we show that drug regulation based on evidential pluralism has much higher costs than our current RCT-based system. We analyze these costs and advocate for evaluating any scheme for drug regulatory tests in terms of concrete empirical benchmarks, like the error rates of regulatory decisions.

We discuss the role of practical costs in the epistemic justification of a novice choosing expert advice, taking as a case study the choice ofan expert statistician by a lay politician. First, we refine Goldman's criteria for the assessment of this choice, showing how the costs of not being impartial impinge on the epistemic justification of the different actors involved in the choice. Then, drawing on two case studies, we discuss in which institutional setting the costs of partiality can play an epistemic role. This way we intend to show how the sociological explanation of the choice of experts can incorporate its epistemic justification.