Browsing by Subject "Scientific modeling"

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    Approaches to Scientific Modeling, and the (Non)Issue of Representation: A Case Study in Multi-model Research on Thigmotaxis and Group Thermoregulation
    (Springer, 2016) Sanches de Oliveira, Guilherme; Filosofía; Magnani, Lorenzo; Casadio, Claudia
    Recent contributions to the philosophical literature on scientific modeling have tended to follow one of two approaches, on the one hand addressing conceptual, metaphysical and epistemological questions about models, or, on the other hand, emphasizing the cognitive aspects of modeling and accordingly focusing on model-based reasoning. In this paper I explore the relationship between these two approaches through a case study of model-based research on the behavior of infant rats, particularly thigmotaxis (movement based on tactile sensation) and temperature regulation in groups. A common assumption in the philosophical literature is that models represent the target phenomena they simulate. In the modeling project under investigation, however, this assumption was not part of the model-based reasoning process, arising only in a theoretical article as, I suggest, a post hoc rhetorical device. I argue that the otherwise nonexistent concern with the model-target relationship as being representational results from a kind of objectification often at play in philosophical analysis, one that can be avoided if an alternative form of objectification is adopted instead.
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    Gibson’s reasons for realism and gibsonian reasons for anti-realism: an ecological approach to model-based reasoning in science
    (Cognitive Science Society, 2016) Sanches de Oliveira, Guilherme; Filosofía; Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J.C.
    Representational views of the mind traditionally face a skeptical challenge on perceptual knowledge: if our experience of the world is mediated by representations built upon perceptual inputs, how can we be certain that our representations are accurate and our perceptual apparatus reliable? J. J. Gibson’s ecological approach provides an alternative framework, according to which direct perception of affordances does away with the need to posit internal mental representations as intermediary steps between perceptual input and behavioral output. Gibson accordingly spoke of his framework as providing “reasons for realism.” In this paper I suggest that, granting Gibson his reasons for perceptual realism, the Gibsonian framework motivates antirealism when it comes to scientific theorizing and modeling. If scientists are Gibsonian perceivers, then it makes sense to take their use of models in indirect investigations of real-world phenomena not as representations of the phenomena, but rather as autonomous tools with their own affordances.
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    Radical artifactualism
    (Springer, 2022-06-02) Sanches de Oliveira, Guilherme; Filosofía
    A powerful idea put forward in the recent philosophy of science literature is that scientific models are best understood as instruments, tools or, more generally, artifacts. This idea has thus far been developed in combination with the more traditional representational approach: accordingly, current artifactualist accounts treat models as representational tools. But artifactualism and representationalism are independent views, and adopting one does not require acceptance of the other. This paper argues that a leaner version of artifactualism, free of representationalist assumptions, is both desirable and viable. Taking seriously the idea that models are artifacts can help us philosophically to make sense of how and why scientific modeling works even without reference to representation.
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    Representationalism is a dead end
    (Springer, 2018-11-01) Sanches de Oliveira, Guilherme; Sin departamento asociado
    Representationalism—the view that scientific modeling is best understood in representational terms—is the received view in contemporary philosophy of science. Contributions to this literature have focused on a number of puzzles concerning the nature of representation and the epistemic role of misrepresentation, without considering whether these puzzles are the product of an inadequate analytical framework. The goal of this paper is to suggest that this possibility should be taken seriously. The argument has two parts, employing the “can’t have” and “don’t need” tactics drawn from philosophy of mind. On the one hand, I propose that representationalism doesn’t work: different ways to flesh out representationalism create a tension between its ontological and epistemological components and thereby undermine the view. On the other hand, I propose that representationalism is not needed in the first place—a position I articulate based on a pragmatic stance on the success of scientific research and on the feasibility of alternative philosophical frameworks. I conclude that representationalism is untenable and unnecessary, a philosophical dead end. A new way of thinking is called for if we are to make progress in our understanding of scientific modeling. [online first, 2018]