Getting Rid of Derivational Redundancy or How to Solve Kuhn’s Problem

Minds and Machines 17 (1):47-66 (2007)
  Copy   BIBTEX


This paper deals with the problem of derivational redundancy in scientific explanation, i.e. the problem that there can be extremely many different explanatory derivations for a natural phenomenon while students and experts mostly come up with one and the same derivation for a phenomenon (modulo the order of applying laws). Given this agreement among humans, we need to have a story of how to select from the space of possible derivations of a phenomenon the derivation that humans come up with. In this paper we argue that the problem of derivational redundancy can be solved by a new notion of “shortest derivation”, by which we mean the derivation that can be constructed by the fewest (and therefore largest) partial derivations of previously derived phenomena that function as “exemplars”. We show how the exemplar-based framework known as “Data-Oriented Parsing” or “DOP” can be employed to select the shortest derivation in scientific explanation. DOP’s shortest derivation of a phenomenon maximizes what is called the “derivational similarity” between a phenomenon and a corpus of exemplars. A preliminary investigation with exemplars from classical and fluid mechanics shows that the shortest derivation closely corresponds to the derivations that humans construct. Our approach also proposes a concrete solution to Kuhn’s problem of how we know on which exemplar a phenomenon can be modeled. We argue that humans model a phenomenon on the exemplar that is derivationally most similar to the phenomenon, i.e. the exemplar from which the largest subtree(s) can be used to derive the phenomenon.



    Upload a copy of this work     Papers currently archived: 76,215

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library


Added to PP

138 (#92,477)

6 months
1 (#449,220)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Rens Bod
University of Amsterdam

Citations of this work

De unificatie van menselijke cognitie.Rens Bod - 2008 - Algemeen Nederlands Tijdschrift voor Wijsbegeerte 100 (2):129-137.

Add more citations

References found in this work

The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - University of Chicago Press.
How the Laws of Physics Lie.Nancy Cartwright - 1983 - Oxford, England: Oxford University Press.
The Structure of Scientific Revolutions.David Bohm - 1964 - Philosophical Quarterly 14 (57):377-379.
Studies in the logic of explanation.Carl Gustav Hempel & Paul Oppenheim - 1948 - Philosophy of Science 15 (2):135-175.

View all 24 references / Add more references