David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Many scientific models are non-representational in that they refer to merely possible processes, background conditions and results. The paper shows how such non-representational models can be appraised, beyond the weak role that they might play as heuristic tools. Using conceptual distinctions from the discussion of how-possibly explanations, six types of models are distinguished by their modal qualities of their background conditions, model processes and model results. For each of these types, an actual model example – drawn from economics, biology, psychology or sociology – is discussed. For each case, contexts and purposes are identified in which the use of such a model offers a genuine opportunity to learn – i.e. justifies changing one’s confidence in a hypothesis about the world. These cases then offer novel justifications for modelling practices that fall between the cracks of standard representational accounts of models
|Keywords||No keywords specified (fix it)|
|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
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Daniela M. Bailer-Jones (2003). When Scientific Models Represent. International Studies in the Philosophy of Science 17 (1):59 – 74.
Tarja Knuuttila (2011). Modelling and Representing: An Artefactual Approach to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):262-271.
Stephan Hartmann & Roman Frigg (2006). Models in Science. In Ed Zalta (ed.), The Stanford Encyclopedia of Philosophy. Stanford.
Sabina Leonelli & Rachel Ankeny (2011). What’s so Special About Model Organisms? Studies in History and Philosophy of Science 42 (2):313-323.
Alisa Bokulich (2011). How Scientific Models Can Explain. Synthese 180 (1):33 - 45.
Till Grüne-Yanoff (2009). Learning From Minimal Economic Models. Erkenntnis 70 (1):81 - 99.
Chuanfei Chin (2011). Models as Interpreters (with a Case Study From Pain Science). Studies in History and Philosophy of Science 42 (2):303-312.
Roman Frigg (2010). Models and Fiction. Synthese 172 (2):251 - 268.
Demetris Portides (2011). Seeking Representations of Phenomena: Phenomenological Models. Studies in History and Philosophy of Science 42 (2):334-341.
Axel Gelfert, Simulating Many-Body Models in Physics: Rigorous Results, 'Benchmarks', and Cross-Model Justification.
Stephan Hartmann (1995). Models as a Tool for Theory Construction: Some Strategies of Preliminary Physics. In William Herfel et al (ed.), Theories and Models in Scientific Processes. Rodopi.
Roman Frigg & Stephan Hartmann (2005). Scientific Models. In Sahotra Sarkar et al (ed.), The Philosophy of Science: An Encyclopedia, Vol. 2. Routledge.
Added to index2012-11-09
Total downloads5 ( #209,062 of 1,096,222 )
Recent downloads (6 months)1 ( #218,857 of 1,096,222 )
How can I increase my downloads?