Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T02:28:28.906Z Has data issue: false hasContentIssue false

Kuhn's Risk-Spreading Argument and the Organization of Scientific Communities

Published online by Cambridge University Press:  03 January 2012

Extract

One of Thomas Kuhn's profoundest arguments (alas, sadly neglected) is introduced in the 1970 “Postscript” to The Structure of Scientific Revolutions (Kuhn 1970). Kuhn is discussing the idea of a “disciplinary matrix” as a more adequate articulation of the “paradigm” notion he'd introduced in the first, 1962, edition of his famous work (Kuhn 1962). He notes that one “element” of disciplinary matrices is likely to be common to most or even all such matrices, unlike the other elements which serve to distinguish specific disciplines and sub-disciplines from one another. This is the element which he calls “values”, which, as he notes (1970, 184), being common to a number of otherwise distinct disciplinary matrices, “do much to provide a sense of community to natural scientists as a whole”. On the other hand, they also do much, and crucially in Kuhn's view, to promote and sustain a healthy diversity among the practitioners who share any specific disciplinary matrix. In particular, Kuhn claims (1970, 186) that “individual variability in the application of shared values may serve functions essential to science.”

Type
Research Article
Copyright
Copyright © Cambridge University Press 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Barnes, B (2001). “Practice as collective action”. In Schatzki, TCetina, K Knorr & von Savigny, E (eds), The Practice Turn in Contemporary Theory. London: Routledge.Google Scholar
D'Agostino, F (1993). ‘“Demographic” Factors in Revolutionary Science: The Wave Model’. Methodology and Science, vol. 26, pp. 4152.Google Scholar
D'Agostino, F (1996). Free Public Reason. New York: Oxford University PressCrossRefGoogle Scholar
D'Agostino, F (2000). “Incommensurability and Commensuration: Lessons from (and to) Ethico-Political Theory”. Studies in the History and Philosophy of Science, vol. 31, no. 3, pp. 429–47.CrossRefGoogle Scholar
D'Agostino, F (2004). ‘Liberalism and Pluralism’, in Gaus, G & Kukathas, C (eds), Handbook of Political Theory. London: Sage.Google Scholar
Dworkin, R (1986). Law's Empire. London: Fontana Press.Google Scholar
Goldman, A (2004). “Group Knowledge versus Group Rationality: Two Approaches to Social Epistemology”. EPISTEME, vol. 1, no. 1, pp. 1122.CrossRefGoogle Scholar
Hampshire, S (1983). Morality and Conflict. Oxford: Basil Blackwell.Google Scholar
Hayek, FA (1973-1976). Law, Legislation and Liberty, Chicago: University of Chicago PressGoogle Scholar
Hoyningen-Huene, P (1993). Reconstructing Scientific Revolutions. Chicago: University of Chicago PressGoogle Scholar
Kitcher, P (1990). “The Division of Cognitive Labor”. Journal of Philosophy, vol. 87, pp. 522.Google Scholar
Kuhn, T (1962). ‘The Structure of Scientific Revolutions’, in International Encyclopedia of Unified Science: Foundations of the Unity of Science. Chicago: University of Chicago Press, vol. 2, no. 2.Google Scholar
Kuhn, T (1970). The Structure of Scientific Revolutions, 2nd edn. Chicago: University of Chicago Press.Google Scholar
Kuhn, T (1977). The Essential Tension. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Lakatos, I (1970). “Falsification and the Methodology of Scientific Research Programmes”, in Lakatos, I & Musgrave, A (eds), Criticism and the Growth of Knowledge. Cambridge: Cambridge University Press.Google Scholar
Lakatos, I & Musgrave, A (eds.) (1970). Criticism and the Growth of Knowledge. Cambridge: Cambridge University Press.Google Scholar
Laudan, R & Laudan, L (1989). “Dominance and the Disunity of Method.” Philosophy of Science, vol. 56, pp. 221–33.Google Scholar
List, C & Pettit, P (2002). “Aggregating Sets of Judgments: An Impossibility Result”. Economics and Philosophy, vol. 18, no. 1, pp. 89110.Google Scholar
Pylyshyn, Z (ed.) (1987). The Robot's Dilemma: The Frame Problem in Artificial Intelligence. Norwood, NJ: Ablex Publishing Corporation.Google Scholar
Rueger, A (1996). “Risk and Diversification in Theory Choice”. Synthese, vol. 109, pp. 263–80.CrossRefGoogle Scholar
Walstad, A (2002). “Science as a Market Process”. Independent Review, vol. 7, no. 1, p. 5ff.Google Scholar
Wenger, E (1998). Communities of Practice: Learning, Meaning and Identity, Cambridge: Cambridge University Press.Google Scholar