David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Philosophical Psychology 6 (1):23 – 37 (1993)
Findlay and Lumsden have proposed a model of creative potential which accounts for divergent thinking but not for convergent thinking. This limitation impedes the applicability of the model to scientific creativity, where competence and thus convergent thinking play a fundamental role since the early stages of creation. This limitation is a natural consequence of the fact that Findlay and Lumsden's model is purely intrapsychic. This paper proposes a model of scientists' creative potential which accounts for both divergent and convergent processes. First, drawing from Csikszentmihalyi's and Kuhn's theories, scientists' creative potential is defined as a matching between the cognitive structure and the epistemic and social structure of the domain. Second, based on this sociopsychological definition, an extension of Findlay and Lumsden's model is proposed. The model states that the highest creative potential is achieved by those scientists who deeply understand the core of the domain and still have cognitive power to access, and experiment on many ideas that are not presently included in the domain. The new model is shown to have greater explanatory power than Findlay and Lumsden's model and to include the latter as a limiting case.
|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
Philip N. Johnson-Laird (1994). A Model Theory of Induction. International Studies in the Philosophy of Science 8 (1):5 – 29.
Dean Keith Simonton (2001). Creativity as Cognitive Selection: The Blind-Variation and Selective-Retention Model. Behavioral and Brain Sciences 24 (3):554-556.
Steve Donaldson (2008). A Neural Network for Creative Serial Order Cognitive Behavior. Minds and Machines 18 (1):53-91.
Mary S. Morgan (2001). Models, Stories and the Economic World. Journal of Economic Methodology 8 (3):361-384.
Rachel A. Ankeny (2000). Fashioning Descriptive Models in Biology: Of Worms and Wiring Diagrams. Philosophy of Science 67 (3):272.
Sang Wook Yi (2002). The Nature of Model-Based Understanding in Condensed Matter Physics. Mind and Society 3 (1):81-91.
Rogier B. Mars, Nicholas Shea, Nils Kolling & Matthew F. S. Rushworth (2012). Model-Based Analyses: Promises, Pitfalls, and Example Applications to the Study of Cognitive Control. Quarterly Journal of Experimental Psychology 65 (2):252-267.
Jeffry L. Ramsey (2007). Calibrating and Constructing Models of Protein Folding. Synthese 155 (3):307 - 320.
Ronald N. Giere (1994). The Cognitive Structure of Scientific Theories. Philosophy of Science 61 (2):276-296.
Added to index2009-03-08
Total downloads5 ( #234,982 of 1,100,145 )
Recent downloads (6 months)1 ( #304,144 of 1,100,145 )
How can I increase my downloads?