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  1. Decoupling, Sparsity, Randomization, and Objective Bayesian Inference.Julio Michael Stern - 2008 - Cybernetics and Human Knowing 15 (2):49-68..
    Decoupling is a general principle that allows us to separate simple components in a complex system. In statistics, decoupling is often expressed as independence, no association, or zero covariance relations. These relations are sharp statistical hypotheses, that can be tested using the FBST - Full Bayesian Significance Test. Decoupling relations can also be introduced by some techniques of Design of Statistical Experiments, DSEs, like randomization. This article discusses the concepts of decoupling, randomization and sparsely connected statistical models in the epistemological (...)
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  • Styles of Valuation: Algorithms and Agency in High-throughput Bioscience.Claes-Fredrik Helgesson & Francis Lee - 2020 - Science, Technology, and Human Values 45 (4):659-685.
    In science and technology studies today, there is a troubling tendency to portray actors in the biosciences as “cultural dopes” and technology as having monolithic qualities with predetermined outcomes. To remedy this analytical impasse, this article introduces the concept styles of valuation to analyze how actors struggle with valuing technology in practice. Empirically, this article examines how actors in a bioscientific laboratory struggle with valuing the properties and qualities of algorithms in a high-throughput setting and identifies the copresence of several (...)
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  • A Dutch treat: randomized controlled experimentation and the case of heroin-maintenance in the Netherlands.Trudy Dehue - 2002 - History of the Human Sciences 15 (2):75-98.
    In 1995, the Dutch Minister of Health proposed that a randomized clinical trial (RCT) with heroin-maintenance for severe abusers be conducted. It took nearly four years of lengthy debates before the Dutch Parliament consented to the plan. Apart from the idea of prescribing heroin, the minister and her scientific advisers had to defend the quite high material and non-material costs that would arise from employing the randomized controlled design. They argued that the RCT represented the truly scientific approach and was (...)
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  • R. A. Fisher and his advocacy of randomization.Nancy S. Hall - 2007 - Journal of the History of Biology 40 (2):295-325.
    The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. (...)
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