An Inferential Conception of Scientific Representation

Suárez, Mauricio

doi:10.1086/421415

Cited by 338 publications

(218 citation statements)

References 9 publications

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“…And accounts of scientific representation that diverge from the copy making accounts have emerged as attractive alternatives (Hughes, 1997;Suárez, 2004;Contessa, 2007;Frigg, 2010). According to Hughes' (1997, S328) 'DDI' account: models denote their targets; allow model users to perform demonstrations on models; whose results are then interpreted in terms of their Copyright Philosophy of Science 2017 Preprint (not copyedited or formatted) Please use DOI when citing or quoting target systems.…”

Section: Representationmentioning

confidence: 99%

Scientific Representation and Theoretical Equivalence

Nguyen¹

2017

Philos. of Sci.

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In this paper I connect two debates in the philosophy of science; the questions of scientific representation and both model and theoretical equivalence. I argue that by paying attention to how a model is used to draw inferences about its target system, we can define a notion of theoretical equivalence that turns on whether their models licence the same claims about the same target systems. I briefly consider the implications of this for two questions that have recently been discussed in the context of the formal philosophy of science.

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Section: Representationmentioning

confidence: 99%

Scientific Representation and Theoretical Equivalence

Nguyen¹

2017

Philos. of Sci.

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“…1 As one example among many, Mauricio Suárez (2004) defends an inferential conception of scientific representation. His account takes careful notice of the aims of scientific practice, noting that mere stipulation (what he calls "representational force") is insufficient for representation in science.…”

Section: Callender and Cohen's Viewmentioning

confidence: 99%

“…Nonetheless, it is a common technique in discussions of scientific representation; see e.g. Suárez (2004).…”

Section: Licensing In Artistic Representationmentioning

confidence: 99%

ThereIsa Special Problem of Scientific Representation

Boesch¹

2017

Philos. of Sci.

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Callender and Cohen (2006) argue that there is no need for a special account of the constitution of scientific representation. I argue that scientific representation is communal and therefore deeply tied to the practice in which it is embedded. The communal nature is accounted for by licensing, the activities of scientific practice by which scientists establish a representation. A case study of the Lotka-Volterra model reveals how the licensure is a constitutive element of the representational relationship. Thus, any account of the constitution of scientific representation must account for licensing, meaning that there is a special problem of scientific representation.

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“…On the other hand, others emphasize models' suitability to serve as surrogate systems (see e.g. Suarez, 2004, andSwoyer, 1991) and maintain that highly idealized scientific models can prompt learning by providing means of conceptual exploration (see e.g. Hausman, 1992, ch.5) and credible 'parallel worlds' (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Why We Cannot Learn from Minimal Models

Fumagalli

2015

Erkenn

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Philosophers of science have developed several accounts of how consideration of scientific models can prompt learning about real-world targets. In recent years, various authors advocated the thesis that consideration of so-called minimal models can prompt learning about such targets. In this paper, I draw on the philosophical literature on scientific modelling and on widely cited illustrations from economics and biology to argue that this thesis fails to withstand scrutiny. More specifically, I criticize leading proponents of such thesis for failing to explicate in virtue of what properties or features minimal models supposedly prompt learning and for substantially overstating the epistemic import of minimal models. I then examine and refute several arguments one may put forward to demonstrate that consideration of minimal models can prompt learning about real-world targets. In doing so, I illustrate the implications of my critique for the wider debate on the epistemology of scientific modelling.

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An Inferential Conception of Scientific Representation

Cited by 338 publications

References 9 publications

Scientific Representation and Theoretical Equivalence

Scientific Representation and Theoretical Equivalence

ThereIsa Special Problem of Scientific Representation

Why We Cannot Learn from Minimal Models

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