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  1. The Mechanistic and Normative Structure of Agency.Jason Winning - 2019 - Dissertation, University of California San Diego
    I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...)
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  • (1 other version)Explanation, Representation and Information.Panagiotis Karadimas - 2024 - Philosophical Problems in Science 74:21-55.
    The ontic conception of explanation is predicated on the proposition that “explanation is a relation between real objects in the world” and hence, according to this approach, scientific explanation cannot take place absent such a premise. Despite the fact that critics have emphasized several drawbacks of the ontic conception, as for example its inability to address the so-called “abstract explanations”, the debate is not settled and the ontic view can claim to capture cases of explanation that are non-abstract, such as (...)
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  • Rethinking Causality in Biological and Neural Mechanisms: Constraints and Control.Jason Winning & William Bechtel - 2018 - Minds and Machines 28 (2).
    Existing accounts of mechanistic causation are not suited for understanding causation in biological and neural mechanisms because they do not have the resources to capture the unique causal structure of control heterarchies. In this paper, we provide a new account on which the causal powers of mechanisms are grounded by time-dependent, variable constraints. Constraints can also serve as a key bridge concept between the mechanistic approach to explanation and underappreciated work in theoretical biology that sheds light on how biological systems (...)
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  • Motivation, counterfactual predictions and constraints: normativity of predictive mechanisms.Michał Piekarski - 2022 - Synthese 200 (5):1-31.
    The aim of this paper is to present the ontic approach to the normativity of cognitive functions and mechanisms, which is directly related to the understanding of biological normativity in terms of normative mechanisms. This approach assumes the hypothesis that cognitive processes contain a certain normative component independent of external attributions and researchers’ beliefs. This component consists of specific cognitive mechanisms, which I call normative. I argue that a mechanism is normative when it constitutes given actions or behaviors of a (...)
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  • Perspectival objectivity.Peter W. Evans - 2020 - European Journal for Philosophy of Science 10 (2):1-21.
    Building on self-professed perspectival approaches to both scientific knowledge and causation, I explore the potentially radical suggestion that perspectivalism can be extended to account for a type of objectivity in science. Motivated by recent claims from quantum foundations that quantum mechanics must admit the possibility of observer-dependent facts, I develop the notion of ‘perspectival objectivity’, and suggest that an easier pill to swallow, philosophically speaking, than observer-dependency is perspective-dependency, allowing for a notion of observer-independence indexed to an agent perspective. Working (...)
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  • Tracers in neuroscience: Causation, constraints, and connectivity.Lauren N. Ross - 2021 - Synthese 199 (1-2):4077-4095.
    This paper examines tracer techniques in neuroscience, which are used to identify neural connections in the brain and nervous system. These connections capture a type of “structural connectivity” that is expected to inform our understanding of the functional nature of these tissues. This is due to the fact that neural connectivity constrains the flow of signal propagation, which is a type of causal process in neurons. This work explores how tracers are used to identify causal information, what standards they are (...)
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