The replication crisis has caused researchers to distinguish between exact replications, which duplicate all aspects of a study that could potentially affect the results, and direct replications, which duplicate only those aspects of the study that are thought to be theoretically essential to reproduce the original effect. The replication crisis has also prompted researchers to think more carefully about the possibility of making Type I errors when rejecting null hypotheses. In this context, the present article considers the utility of two (...) types of Type I error probability: the Neyman–Pearson long run Type I error rate and the Fisherian sample-specific Type I error probability. It is argued that the Neyman–Pearson Type I error rate is inapplicable in social science because it refers to a long run of exact replications, and social science deals with irreversible units that make exact replications impossible. Instead, the Fisherian sample-specific Type I error probability is recommended as a more meaningful way to conceptualize false positive results in social science because it can be applied to each sample-specific decision about rejecting the same substantive null hypothesis in a series of direct replications. It is concluded that the replication crisis may be partly due to researchers’ unrealistic expectations about replicability based on their consideration of the Neyman–Pearson Type I error rate across a long run of exact replications. (shrink)

Discussions about a replicability crisis in science have been driven by the normative claim that all of science should be replicable and the empirical claim that most of it isn’t. Recently, such crisis talk has been challenged by a new localism, which argues a) that serious problems with replicability are not a general occurrence in science and b) that replicability itself should not be treated as a universal standard. The goal of this article is to introduce this emerging strand of (...) the debate and to discuss some of its implications and limitations. I will in particular highlight the issue of demarcation that localist accounts have to address, i.e. the question of how we can distinguish replicable science from disciplines where replicability does not apply. (shrink)

Recently, many scientists have become concerned about an excessive number of failures to reproduce statistically significant effects. The situation has become dire enough that the situation has been named the ‘reproducibility crisis’. After reviewing the relevant literature to confirm the observation that scientists do indeed view replication as currently problematic, I explain in philosophical terms why the replication of empirical phenomena, such as statistically significant effects, is important for scientific progress. Following that explanation, I examine various diagnoses of the reproducibility (...) crisis, and argue that for the majority of scientists the crisis is due, at least in part, to a form of publication bias. This conclusion sets the stage for an assessment of the view that evidential relations in science are inherently value-laden, a view championed by Heather Douglas and Kevin Elliott. I argue, in response to Douglas and Elliott, and as motivated by the meta-scientific resistance scientists harbour to a publication bias, that if we advocate the value-ladenness of science the result would be a deepening of the reproducibility crisis. (shrink)

Nowadays, almost everyone seems to agree that science is facing an epistemological crisis – namely the replicability crisis – and that we need to take action. But as to precisely what to do or how...

Replicability is usually considered to be one of the cornerstones of science; however, the growing recognition of nonreplicable experiments and studies in scientific journals—a phenomenon that has been called ‘replicability crisis’—has spurred a debate on the meaning, function, and significance of replicability in science. Amid this discussion, it has become clear that replicability is not a monolithic concept; what is still controversial is exactly how the distinction between different kinds of replicability should be laid out terminologically and conceptually, and to (...) what extent it bears on the more general debate on the centrality of replicability in science. This paper’s goals are to clarify the different uses of the terms related to replicability and, more importantly, to conceptually specify the kinds of replicability and their respective epistemic functions. (shrink)