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  1. 1,500 scientists lift the lid on reproducibility.M. Baker - 2016 - Nature 533 (7604):452-454.
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  • Philosophy of science and the replicability crisis.Felipe Romero - 2019 - Philosophy Compass 14 (11):e12633.
    Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I (...)
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  • (1 other version)Understanding the replication crisis as a base rate fallacy.Alexander Bird - 2018 - British Journal for the Philosophy of Science:000-000.
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  • Why Most Published Research Findings Are False.John P. A. Ioannidis - 2005 - PLoS Med 2 (8):e124.
    Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.
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  • Replicability or reproducibility? On the replication crisis in computational neuroscience and sharing only relevant detail.Marcin Miłkowski, Witold M. Hensel & Mateusz Hohol - 2018 - Journal of Computational Neuroscience 3 (45):163-172.
    Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...)
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  • The Place of Modeling in Cognitive Science.James L. McClelland - 2009 - Topics in Cognitive Science 1 (1):11-38.
    I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential—through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; (...)
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