ABSTRACTPossibly, the replication crisis constitutes the most important problem in psychology. It calls into question whether psychology is a science. Existing conceptualizations of replicability depend on effect sizes; the larger the population effect size, the greater the probability of replication. This is problematic and contributes to the replication crisis. A different conceptualization, not dependent on population effect sizes, is desirable. The proposed solution features the closeness of sample means to their corresponding population means, in both the original and replication experiments. (...) If the researcher has specified the sampling precision desired, it is possible to calculate the probability of replication, prior to data collection, and without dependence on the population effect size or expected population effect size. In addition, it is not necessary to know population means or standard deviations, nor sample means or standard deviations, to employ the proposed a priori way of thinking about... (shrink)

This special issue on what some regard as a crisis of replicability in cognitive science (i.e. the observation that a worryingly large proportion of experimental results across a number of areas cannot be reliably replicated) is informed by three recent developments. -/- First, philosophers of mind and cognitive science rely increasingly on empirical research, mainly in the psychological sciences, to back up their claims. This trend has been noticeable since the 1960s (see Knobe, 2015). This development has allowed philosophers to (...) draw on a wider range of relevant resources, but it also makes them vulnerable to relying on claims that may not survive further scrutiny. If we have reasons to believe that a large proportion of findings in the psychological sciences cannot be reliably replicated, this would be a problem for philosophers who use such findings in their work. Second, philosophers are increasingly designing and carrying out their own experiments to back up claims, or to test claims earlier made from the armchair, for example, on the perceived permissibility of diverting trolleys or on the nature of free will. This growing field of experimental philosophy has diversified the intellectual field in philosophy, but may also be vulnerable to issues of replicability that philosophers did not face before. -/- Third, the recent evidence of apparently widespread non-replicability in the social sciences (and other fields) has forced philosophers of science to grapple with long standing questions from their field from a new perspective. To what extent does replicability matter for theory construction? How do the notions of replicability and scientific progress interact? How can normative insights from philosophy of science be used in order to improve scientific practice? -/- It is with these three developments in mind—the increasing importance of empirically-informed philosophy, of experimental philosophy, and of philosophy of science around replicability—that this special issue has been conceived. (shrink)

Kerr coined the term ‘HARKing’ to refer to the practice of ‘hypothesizing after the results are known’. This questionable research practice has received increased attention in recent years because it is thought to have contributed to low replication rates in science. The present article discusses the concept of HARKing from a philosophical standpoint and then undertakes a critical review of Kerr’s twelve potential costs of HARKing. It is argued that these potential costs are either misconceived, misattributed to HARKing, lacking evidence, (...) or that they do not take into account pre- and post-publication peer review and public availability to research materials and data. It is concluded that it is premature to conclude that HARKing has led to low replication rates. (shrink)

Proposals for regulating or nudging healthy choices are controversial. Opponents often argue that individuals should take responsibility for their own health, rather than be paternalistically manipulated for their own good. In this paper, I argue that people can take responsibility for their own health only if they satisfy certain epistemic conditions, but we live in an epistemic environment in which these conditions are not satisfied. Satisfying the epistemic conditions for taking responsibility, I argue, requires regulation of this environment. I describe (...) some proposals for such regulation and show that we cannot reject all regulation in the name of individual responsibility. We must either regulate individuals’ healthy choices or regulate the epistemic environment. (shrink)

What to do with the missing shade of blue? Some have argued that Hume's famous thought experiment undermines his central doctrine – the ‘copy principle’ – such that he should have revised his whole theory in light of it. Others contend that the MSB is not a true or actual counterexample to the copy principle, but merely an apparent or conceivable one, so that he had no such obligation to revise. In this essay, I argue that even if the MSB (...) is a true counterexample, Hume would not have been obligated to revise his theory, given methodological resources he makes available to himself elsewhere in his work and his overarching empiricist aims. And I offer a new suggestion for why he might have included and even highlighted the MSB in his writings despite its being so very vexing and peculiar. (shrink)

For decades, technologies that ease information sharing (e.g., the wireless telegraph; Mckernon, 1925) have inspired concerns about the proliferation of misinformation. Today, these worries often c...

In this paper, we provide a re-interpretation of qualitative and quantitative modeling from a representationalist perspective. In this view, both approaches attempt to construct abstract representations of empirical relational structures. Whereas quantitative research uses variable-based models that abstract from individual cases, qualitative research favors case-based models that abstract from individual characteristics. Variable-based models are usually stated in the form of quantified sentences. This syntactic structure implies that sentences about individual cases are derived using deductive reasoning. In contrast, case-based models are (...) usually stated using context-dependent existential sentences. This syntactic structure implies that sentences about other cases are justifiable by inductive reasoning. We apply this representationalist perspective to the problems of generalization and replication. Using the analytical framework of modal logic, we argue that the modes of reasoning are often not only applied to the context that has been studied empirically, but also on a between-contexts level. Consequently, quantitative researchers mostly adhere to a top-down strategy of generalization, whereas qualitative researchers usually follow a bottom-up strategy of generalization. Depending on which strategy is employed, the role of replication attempts is very different. In deductive reasoning, replication attempts serve as empirical tests of the underlying theory. Therefore, failed replications imply a faulty theory. From an inductive perspective, however, replication attempts serve to explore the scope of the theory. Consequently, failed replications do not question the theory per se, but help to shape its boundary conditions. We conclude that quantitative research may benefit from a bottom-up generalization strategy as it is employed in most qualitative research programs. Inductive reasoning forces us to think about the boundary conditions of our theories and provides a framework for generalization beyond statistical testing. In this perspective, failed replications are just as informative as successful replications, because they help to explore the scope of our theories. (shrink)

In July 2014, the roboticist Ronald Arkin suggested that child sex robots could be used to treat those with paedophilic predilections in the same way that methadone is used to treat heroin addicts. Taking this onboard, it would seem that there is reason to experiment with the regulation of this technology. But most people seem to disagree with this idea, with legal authorities in both the UK and US taking steps to outlaw such devices. In this paper, I subject these (...) different regulatory attitudes to critical scrutiny. In doing so, I make three main contributions to the debate. First, I present a framework for thinking about the regulatory options that we confront when dealing with child sex robots. Second, I argue that there is a prima facie case for restrictive regulation, but that this is contingent on whether Arkin’s hypothesis has a reasonable prospect of being successfully tested. Third, I argue that Arkin’s hypothesis probably does not have a reasonable prospect of being successfully tested. Consequently, we should proceed with utmost caution when it comes to this technology. (shrink)

. Scientists, for the most part, want to get it right. However, the social structures that govern their work undermine that aim, and this leads to nonreplicable findings in many fields. Because the social structure of science is a decentralized system, it is difficult to intervene. In this article, I discuss how we might do so, focusing on self-corrective-labor schemes. First, I argue that we need to implement a scheme that makes replication work outcome independent, systematic, and sustainable. Second, I (...) use these three criteria to evaluate extant proposals, which place the responsibility for replication on original researchers, consumers of their research, students, or many labs. Third, on the basis of a philosophical analysis of the reward system of science and the benefits of the division of cognitive labor, I propose a scheme that satisfies the criteria better: the professional scheme. This scheme has two main components. First, the scientific community is organized into two groups: discovery researchers, who produce new findings, and confirmation researchers, whose primary function is to do confirmation work. Second, a distinct reward system is established for confirmation researchers so that their career advancement is separated from whether they obtain positive experimental results. (shrink)