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Capacities and abstractions

In Philip Kitcher & Wesley Salmon (eds.), Scientific Explanation. Univ of Minnesota Pr. pp. 13--349 (1989)

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  1. From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence.Catherine Stinson - 2020 - Philosophy of Science 87 (4):590-611.
    There is a vast literature within philosophy of mind that focuses on artificial intelligence, but hardly mentions methodological questions. There is also a growing body of work in philosophy of science about modeling methodology that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the philosophy of science literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive science illuminate how relevant similarities between models and (...)
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  • Experiments in history and philosophy of science.Friedrich Steinle - 2002 - Perspectives on Science 10 (4):408-432.
    : The increasing attention on experiment in the last two decades has led to important insights into its material, cultural and social dimensions. However, the role of experiment as a tool for generating knowledge has been comparatively poorly studied. What questions are asked in experimental research? How are they treated and eventually resolved? And how do questions, epistemic situations, and experimental activity cohere and shape each other? In my paper, I treat these problems on the basis of detailed studies of (...)
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  • Deidealization: No Easy Reversals.Tarja Knuuttila & Mary S. Morgan - 2019 - Philosophy of Science 86 (4):641-661.
    Deidealization as a topic in its own right has attracted remarkably little philosophical interest despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, deidealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal (...)
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  • Strategies of Explanatory Abstraction in Molecular Systems Biology.Nicholaos Jones - 2018 - Philosophy of Science 85 (5):955-968.
    I consider three explanatory strategies from recent systems biology that are driven by mathematics as much as mechanistic detail. Analysis of differential equations drives the first strategy; topological analysis of network motifs drives the second; mathematical theorems from control engineering drive the third. I also distinguish three abstraction types: aggregations, which simplify by condensing information; generalizations, which simplify by generalizing information; and structurations, which simplify by contextualizing information. Using a common explanandum as reference point—namely, the robust perfect adaptation of chemotaxis (...)
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  • Causal explanation and scientific realism.Christopher Hitchcock - 1992 - Erkenntnis 37 (2):151 - 178.
    It is widely believed that many of the competing accounts of scientific explanation have ramifications which are relevant to the scientific realism debate. I claim that the two issues are orthogonal. For definiteness, I consider Cartwright's argument that causal explanations secure belief in theoretical entities. In Section I, van Fraassen's anti-realism is reviewed; I argue that this anti-realism is, prima facie, consistent with a causal account of explanation. Section II reviews Cartwright's arguments. In Section III, it is argued that causal (...)
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  • On the metaphysics of probabilistic causation: Lessons from social epidemiology.Bruce Glymour - 2003 - Philosophy of Science 70 (5):1413-1423.
    I argue that the orthodox account of probabilistic causation, on which probabilistic causes determine the probability of their effects, is inconsistent with certain ontological assumptions implicit in scientific practice. In particular, scientists recognize the possibility that properties of populations can cause the behavior of members of the populations. Such emergent population‐level causation is metaphysically impossible on the orthodoxy.
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  • El paradigma de la complejidad en economía: más allá de las leyes y de la causalidad lineal.Alfredo García, Leonardo Ivarola & Martín Szybisz - 2018 - Cinta de Moebio 61:80-94.
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  • In Favor of Laws that Are Not C eteris Paribus After All.Nancy Cartwright - 2002 - Erkenntnis 57 (3):425Ð439.
    Opponents of ceteris paribus laws are apt to complain that the laws are vague and untestable. Indeed, claims to this effect are made by Earman, Roberts and Smith in this volume. I argue that these kinds of claims rely on too narrow a view about what kinds of concepts we can and do regularly use in successful sciences and on too optimistic a view about the extent of application of even our most successful non-ceteris paribus laws. When it comes to (...)
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  • Legal Questions and Scientific Answers : Ontological Differences and Epistemic Gaps in the Assessment of Causal Relations.Lena Wahlberg - 2010 - Dissertation, Lund University
    A large number of legal rules create an obligation to prevent, repair or otherwise mitigate damage to human health or the environment. Many of these rules require that a legally relevant causal relation between human behaviour and the damage at issue is established, and in the establishment of causal relations of this kind scientific information is often pressed into service. This thesis examines this specifically legal use of scientific information. It shows that many legally relevant causal relations cannot be established (...)
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