David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Studies in History and Philosophy of Science 42 (2):262-271 (2011)
The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation.
|Keywords||Scientific mod Epistemic tools Representation Modelling|
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References found in this work BETA
Peter Godfrey-Smith (2006). The Strategy of Model-Based Science. Biology and Philosophy 21 (5):725-740.
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Citations of this work BETA
Richard Heersmink (forthcoming). The Cognitive Integration of Scientific Instruments: Information, Situated Cognition and Scientific Practice. Phenomenology and the Cognitive Sciences:1-21.
Tarja Knuuttila & Andrea Loettgers (2014). Varieties of Noise: Analogical Reasoning in Synthetic Biology. Studies in History and Philosophy of Science Part A 48:76-88.
Tarja Knuuttila & Andrea Loettgers (2013). Basic Science Through Engineering? Synthetic Modeling and the Idea of Biology-Inspired Engineering. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):158-169.
Sara Green (2013). When One Model is Not Enough: Combining Epistemic Tools in Systems Biology. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (2):170-180.
Elizabeth Irvine (2016). Model-Based Theorizing in Cognitive Neuroscience. British Journal for the Philosophy of Science 67 (1):143-168.
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