Works by Stephan Lewandowsky ( view other items matching `Stephan Lewandowsky`, view all matches )

  1. Thomas L. Griffiths, Stephan Lewandowsky & Michael L. Kalish (2013). The Effects of Cultural Transmission Are Modulated by the Amount of Information Transmitted. Cognitive Science 37 (4).
    Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that information changes. We tested this prediction using a function-learning task, in which people learn a functional relationship between two variables by observing the values of those variables. (...)
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  2. Simon Farrell & Stephan Lewandowsky (2000). The Case Against Distributed Representations: Lack of Evidence. Behavioral and Brain Sciences 23 (4):476-477.
    We focus on two components of Page's argument in favour of localist representations in connectionist networks: First, we take issue with the claim that localist representations can give rise to generalisation and show that whenever generalisation occurs, distributed representations are involved. Second, we counter the alleged shortcomings of distributed representations and show that their properties are preferable to those of localist approaches.
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  3. Stephan Lewandowsky & Murray Maybery (1998). The Critics Rebutted: A Pyrrhic Victory. Behavioral and Brain Sciences 21 (2):210-211.
    We take up two issues discussed by Chow: the claim by critics of hypothesis testing that the null hypothesis (H0) is always false, and the claim that reporting effect sizes is more appropriate than relying on statistical significance. Concerning the former, we agree with Chow's sentiment despite noting serious shortcomings in his discussion. Concerning the latter, we agree with Chow that effect size need not translate into scientific relevance, and furthermore reiterate that with small samples effect size measures cannot substitute (...)
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