David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Philosophical Psychology 26 (1):139-152 (2013)
In this paper we argue that in recent literature on mechanistic explanations, authors tend to conflate two distinct features that mechanistic models can have or fail to have: plausibility and richness. By plausibility, we mean the probability that a model is correct in the assertions it makes regarding the parts and operations of the mechanism, i.e., that the model is correct as a description of the actual mechanism. By richness, we mean the amount of detail the model gives about the actual mechanism. First, we argue that there is at least a conceptual reason to keep these two features distinct, since they can vary independently from each other: models can be highly plausible while providing almost no details, while they can also be highly detailed but plainly wrong. Next, focusing on Craver's continuum of ?how-possibly,? to ?how-plausibly,? to ?how-actually? models, we argue that the conflation of plausibility and richness is harmful to the discussion because it leads to the view that both are necessary for a model to have explanatory power, while in fact, richness is only so with respect to a mechanism's activities, not its entities. This point is illustrated with two examples of functional models
|Keywords||Explanation mechanism mechanistic explanation plausibility models richness|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Carl F. Craver (2007). Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience. Oxford University Press, Clarendon Press.
Michael Strevens (2008). Depth: An Account of Scientific Explanation. Harvard University Press.
Peter K. Machamer, Lindley Darden & Carl F. Craver (2000). Thinking About Mechanisms. Philosophy of Science 67 (1):1-25.
William Bechtel (2005). Explanation: A Mechanist Alternative. Studies in History and Philosophy of Biol and Biomed Sci 36 (2):421--441.
Stuart Glennan (2002). Rethinking Mechanistic Explanation. Proceedings of the Philosophy of Science Association 2002 (3):S342-353.
Citations of this work BETA
Dingmar van Eck & Erik Weber (2014). Function Ascription and Explanation: Elaborating an Explanatory Utility Desideratum for Ascriptions of Technical Functions. Erkenntnis 79 (6):1367-1389.
Dingmar van Eck (2015). Validating Function-Based Design Methods: An Explanationist Perspective. Philosophy and Technology 28 (4):511-531.
Dingmar van Eck (2015). Mechanistic Explanation in Engineering Science. European Journal for Philosophy of Science 5 (3):349-375.
Raoul Gervais & Erik Weber (2013). Inferential Explanations in Biology. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (3):356-364.
Similar books and articles
Carl F. Craver (2006). When Mechanistic Models Explain. Synthese 153 (3):355-376.
John Matthewson & Brett Calcott (2011). Mechanistic Models of Population-Level Phenomena. Biology and Philosophy 26 (5):737-756.
David M. Kaplan & William Bechtel (2011). Dynamical Models: An Alternative or Complement to Mechanistic Explanations? Topics in Cognitive Science 3 (2):438-444.
Daniel A. Weiskopf (2011). Models and Mechanisms in Psychological Explanation. Synthese 183 (3):313-338.
Ron Sun (1999). Accounting for the Computational Basis of Consciousness: A Connectionist Approach. Consciousness and Cognition 8 (4):529-565.
Karl Schlechta (1996). Completeness and Incompleteness for Plausibility Logic. Journal of Logic, Language and Information 5 (2):177-192.
David Michael Kaplan (2011). Explanation and Description in Computational Neuroscience. Synthese 183 (3):339-373.
Martijn Meeter, Janneke Jehee & Jaap Murre (2007). Neural Models That Convince: Model Hierarchies and Other Strategies to Bridge the Gap Between Behavior and the Brain. Philosophical Psychology 20 (6):749 – 772.
Michiru Nagatsu (2010). Function and Mechanism: The Metaphysics of Neuroeconomics. Journal of Economic Methodology 17 (2):197-205.
Alisa Bokulich (2011). How Scientific Models Can Explain. Synthese 180 (1):33 - 45.
William P. Bechtel (1998). Representations and Cognitive Explanations: Assessing the Dynamicist Challenge in Cognitive Science. Cognitive Science 22 (3):295-317.
Michael H. Albert & Rami P. Grossberg (1990). Rich Models. Journal of Symbolic Logic 55 (3):1292-1298.
Ingo Brigandt (2015). Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation. In P.-A. Braillard & C. Malaterre (eds.), Explanation in Biology: An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences. Springer 135–173.
Peter Fazekas & Gergely Kertész (2011). Causation at Different Levels: Tracking the Commitments of Mechanistic Explanations. Biology and Philosophy 26 (3):365-383.
Added to index2012-02-01
Total downloads20 ( #142,353 of 1,726,249 )
Recent downloads (6 months)1 ( #369,877 of 1,726,249 )
How can I increase my downloads?