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Nina Poth [9]Nina Laura Poth [1]
  1. Where is your pain? A Cross-cultural Comparison of the Concept of Pain in Americans and South Korea.Hyo-eun Kim, Nina Poth, Kevin Reuter & Justin Sytsma - 2016 - Studia Philosophica Estonica 9 (1):136-169.
    Philosophical orthodoxy holds that pains are mental states, taking this to reflect the ordinary conception of pain. Despite this, evidence is mounting that English speakers do not tend to conceptualize pains in this way; rather, they tend to treat pains as being bodily states. We hypothesize that this is driven by two primary factors—the phenomenology of feeling pains and the surface grammar of pain reports. There is reason to expect that neither of these factors is culturally specific, however, and thus (...)
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  2. Refining the Bayesian Approach to Unifying Generalisation.Nina Poth - 2022 - Review of Philosophy and Psychology (3):1-31.
    Tenenbaum and Griffiths (2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (1987) and Tversky’s (1977) similarity-based explanations of two distinct patterns of generalisation behaviours by reconciling them under a single coherent task analysis. I argue that this proposal needs refinement: instead of unifying the heterogeneous notion of psychological similarity, the Bayesian approach unifies generalisation by rendering the distinct patterns of behaviours informationally relevant. I suggest that generalisation as a Bayesian inference should be seen as a complement to, (...)
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  3.  56
    Bayesian belief protection: A study of belief in conspiracy theories.Nina Poth & Krzysztof Dolega - 2023 - Philosophical Psychology 36 (6):1182-1207.
    Several philosophers and psychologists have characterized belief in conspiracy theories as a product of irrational reasoning. Proponents of conspiracy theories apparently resist revising their beliefs given disconfirming evidence and tend to believe in more than one conspiracy, even when the relevant beliefs are mutually inconsistent. In this paper, we bring leading views on conspiracy theoretic beliefs closer together by exploring their rationality under a probabilistic framework. We question the claim that the irrationality of conspiracy theoretic beliefs stems from an inadequate (...)
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  4. Bayesian belief protection: A study of belief in conspiracy theories.Nina Poth & Krzysztof Dolega - 2022 - Philosophical Psychology.
    Several philosophers and psychologists have characterized belief in conspiracy theories as a product of irrational reasoning. Proponents of conspiracy theories apparently resist revising their beliefs given disconfirming evidence and tend to believe in more than one conspiracy, even when the relevant beliefs are mutually inconsistent. In this paper, we bring leading views on conspiracy theoretic beliefs closer together by exploring their rationality under a probabilistic framework. We question the claim that the irrationality of conspiracy theoretic beliefs stems from an inadequate (...)
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    Refining the Bayesian Approach to Unifying Generalisation.Nina Poth - 2023 - Review of Philosophy and Psychology 14 (3):877-907.
    Tenenbaum and Griffiths (Behavioral and Brain Sciences 24(4):629–640, 2001) have proposed that their Bayesian model of generalisation unifies Shepard’s (Science 237(4820): 1317–1323, 1987) and Tversky’s (Psychological Review 84(4): 327–352, 1977) similarity-based explanations of two distinct patterns of generalisation behaviours by reconciling them under a single coherent task analysis. I argue that this proposal needs refinement: instead of unifying the heterogeneous notion of psychological similarity, the Bayesian approach unifies generalisation by rendering the distinct patterns of behaviours informationally relevant. I suggest that (...)
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  6. Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox.Nina Laura Poth & Peter Brössel - 2020 - Philosophy of Science 87 (1):135-151.
    Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it (...)
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  7. Conceptual Spaces, Generalisation Probabilities and Perceptual Categorisation.Nina Poth - 2019 - In Peter Gärdenfors, Antti Hautamäki, Frank Zenker & Mauri Kaipainen (eds.), Conceptual Spaces: Elaborations and Applications. Springer Verlag. pp. 7-28.
    Shepard’s (1987) universal law of generalisation (ULG) illustrates that an invariant gradient of generalisation across species and across stimuli conditions can be obtained by mapping the probability of a generalisation response onto the representations of similarity between individual stimuli. Tenenbaum and Griffiths (2001) Bayesian account of generalisation expands ULG towards generalisation from multiple examples. Though the Bayesian model starts from Shepard’s account it refrains from any commitment to the notion of psychological similarity to explain categorisation. This chapter presents the conceptual (...)
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    Probabilistic Learning and Psychological Similarity.Nina Poth - 2023 - Entropy 25 (10).
    The notions of psychological similarity and probabilistic learning are key posits in cognitive, computational, and developmental psychology and in machine learning. However, their explanatory relationship is rarely made explicit within and across these research fields. This opinionated review critically evaluates how these notions can mutually inform each other within computational cognitive science. Using probabilistic models of concept learning as a case study, I argue that two notions of psychological similarity offer important normative constraints to guide modelers’ interpretations of representational primitives. (...)
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  9. Schema-Centred Unity and Process-Centred Pluralism of the Predictive Mind.Nina Poth - 2022 - Minds and Machines 32 (3):433-459.
    Proponents of the predictive processing (PP) framework often claim that one of the framework’s significant virtues is its unificatory power. What is supposedly unified are predictive processes in the mind, and these are explained in virtue of a common prediction error-minimisation (PEM) schema. In this paper, I argue against the claim that PP currently converges towards a unified explanation of cognitive processes. Although the notion of PEM systematically relates a set of posits such as ‘efficiency’ and ‘hierarchical coding’ into a (...)
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    Same but Different: Providing a Probabilistic Foundation for the Feature-Matching Approach to Similarity and Categorization.Nina Poth - forthcoming - Erkenntnis:1-25.
    The feature-matching approach pioneered by Amos Tversky remains a groundwork for psychological models of similarity and categorization but is rarely explicitly justified considering recent advances in thinking about cognition. While psychologists often view similarity as an unproblematic foundational concept that explains generalization and conceptual thought, long-standing philosophical problems challenging this assumption suggest that similarity derives from processes of higher-level cognition, including inference and conceptual thought. This paper addresses three specific challenges to Tversky’s approach: (i) the feature-selection problem, (ii) the problem (...)
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