Abstract
The related problems of metaphor and analogical reasoning have recently become of interest within three separate disciplines: philosophy of science, philosophy of language, and Artificial Intelligence. Classically the study of analogy has been concerned with analogical meaning (related to metaphor), and with analogical argument, which was seen in standard logic texts up to the 19th century as a very poor relation of inductive and hypothetical reasoning.1 These two aspects began to come together in the 19th century with explicit discussion of both meaning and argument from the point of view of scientific models.2 Subsequently positivist philosophy of science added “analogy” to its consideration of inductive argument as an important ingredient of induction, and post-positivist philosophy began to consider analogical meaning in models as crucial for the understanding of theoretical concepts and the problem of meaning variance between theories.3
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Notes
For example J. S. Mill, A System of Logic, London, 1843, Bk. III, Ch. 20 and W. S. Jevons, Principles of Science, Macmillan, London, 1874, Ch. 28.
See W. Thomson, Papers on Electrostatics and Magnetism, 2nd ed. London, 1884, p. 29f;
W. J. M. Rankine, Miscellaneous Scientific Papers, London, 1881, p. 209;
J. C. Maxwell, Scientific Papers, Cambridge University Press, 1890, I, p. 155;
and M. Hesse, The Structure of Scientific Inference, Macmillan, London, 1974, Ch. 11.
Hesse, ibid., specially Chs. 2 and 9.
Among the many recent books and collections of papers devoted to the philosophy of metaphor are D. E. Cooper, Metaphor, Blackwell, Oxford, 1986;
M. Johnson (ed.), Philosophical Perspectives on Metaphor, University of Minneapolis Press, 1981;
G. Lakoff and M. Johnson, Metaphors We Live By, Chicago University Press, 1980;
D. Miall (ed.), Metaphor: Problems and Perspectives, Harvester, Brighton, Sussex, 1982;
A. Ortony (ed.), Metaphor and Thought, Cambridge University Press, 1979;
P. Ricoeur, The Rule of Metaphor (trans. R. Czerny), Routledge and Kegan Paul, London, 1978;
J. F. Ross, Portraying Analogy, Cambridge University Press, 1882;
and S. Sachs (ed.), On Metaphor, Chicago University Press, 1979. There is also an extended discussion in H.-G. Gadamer, Truth and Method (English trans.) Sheed and Ward, London, 1975, p. 387ff.
I have discussed this issue in “The cognitive claims of metaphor”, in Metaphor and Religion, Theolinguistics 2 (ed. J. P. van Noppen), Brussels, 1984, and “Texts without types and lumps without laws”, New Literary History, 17, 1985–86, 32.
See M. Arbib and M. Hesse, The Construction of Reality, Cambridge University Press, 1986, Chs. 2 and 3.
See D. Rothbart, “Analogical information processing within scientific metaphors”, and P. Thagard, “Dimensions of analogy”, this volume.
For a discussion of this example, see M. Hesse, The Structure of Scientific Inference, Ch. 11.
M. Black, Models and Metaphor, Cornell University Press, Ithaca, N.Y., 1962, Chs. 3 and 13.
P. H. A. Sneath and R. R. Sokal introduce their theory of biological taxonomy by referring to polythetic classes and family resemblances, and give references to methods in information retrieval which are based on word clusters according to similar principles (Numerical Taxonomy, Freeman, San Francisco, 1973, pp. 21, 448). See also G. Dunn and B. S. Everitt, An Introduction to Mathematical Taxonomy, Cambridge University Press, 1982;
N. Jardine and R. Sibson, Mathematical Taxonomy, Wiley, London, 1971;
and K. Sparck Jones, “Some thoughts on classification for retrieval”, J. of Documentation, 26, 1970, 89; and “Clumps, Theory of”, in Encyclopedia of Library and Information Science (eds. Kent and Lancour), Marcel Dekker, New York, Vol. 5, 1971, 208.
E. Rosch, “Cognitive reference points”, Cognitive Psychology, 7, 1975, 532;
E. Rosch, “Cognitive representations of semantic categories”, J.Experimental Psychology, General, 104, 1975, 192;
E. Rosch, “Principles of categorization” in Cognition and Categorization (ed. E. Rosch and B. B. Lloyd), Wiley, New York, 1978, p. 27;
E. Rosch and C. B. Mervis, “Family resemblances: studies in the internal structure of categories”, Cognitive Psychology, 7, 1975, 573;
and C. B. Mervis and E. Rosch, “Categorization of natural objects”, Ann. Rev. Psychology, 32,1981, 89.
Relations of cue properties can be used to define the similarities and differences between objects. It is important to notice that “similarity” need not be a symmetrical relation. For example, Mervis and Rosch (op. cit. p. 94) note that Mexico is perceived as more similar to the United States than the United States is to Mexico. This asymmetric relation can be represented by a similarity function S(ab) which depends on the proportion between the number of a properties that also belong to b to the total number of a properties judged relevant to the comparison. Then S(ab) is generally not equivalent to S(ba). Cooper (op. cit. p. 186) is surely mistaken in arguing that since similarity is a symmetric relation, similes cannot be types of metaphor, and metaphors cannot be based on similarities.
M. Turner, “Categories and analogies”, and M. Johnson, “Some constraints on embodied analogical understanding”, this volume.
Dictionaries and thesauruses contain much of the information needed to construct such a nearness distribution of linguistic terms, see Sparck Jones and Jackson, op. cit.
Rosch, “Cognitive representations of semantic categories”, 226, and K. Dahlgren, “The cognitive structure of social categories”, Cognitive Science, 9, 1985, 379.
Hesse, “Texts without types and lumps without laws”.
Cooper (op. cit. p. 279) sees it as an objection to the kind of theory adopted here that it cannot be the case that “unknown to the [speakers] themselves, they are employed full-time in speaking metaphorically”. His argument is that they must have a theory of correct and consistent speech that guarantees that non-metaphoric talk is the norm. But (i) a theory of metaphoric connections does not have to be (consciously) “known to speakers” any more than the rules of grammar do, and (ii) on the theory presented here, a “theory of correctness” of metaphoric talk, though itself in principle metaphoric (because all talk is), would be at the relatively “literal” end of the scale of metaphoricalness, as a contribution to applied logic.
See my discussion of “grue” in The Structure of Scientific Inference, Ch. 3.
Ibid., Ch. 5.
What P. Suppes calls the “combinatorial jungle” (“Concept formation and Bayesian decisions”, in Aspects of Inductive Logic (ed. J. Hintikka and P. Suppes), North-Holland, Amsterdam, 1966, p. 21).
See also R. Carnap, The Logical Foundations of Probability, Routledge, Chicago, 1962, p. 124.
B. de Finetti, “Foresight: its logical laws, its subjective sources”, in Studies in Subjective Probability (ed. H. E. Kyburg and H. E. Smokler), Wiley, New York, 1964, p. 120.
See my Models and Analogies in Science, Sheed and Ward, London, 1963 and The Structure of Scientific Inference, Ch. 11.
Ibid., Ch. 9.
Alternatives are C. Glymour’s “bootstrapping” theory, in Theory and Evidence, Princeton University Press, 1980, and I. Niiniluoto, “Analogy, transitivity, and the confirmation of theories”, in Applications of Inductive Logic (ed. L. J. Cohen and M. Hesse), Clarendon, Oxford, 1980, p. 218.
Rosch (op. cit. 1978, p. 28) makes it clear that her theory is not intended as a theory of the development of categories in children or adults, but it may surely provide suggestions for such a theory.
Cooper (op. cit. p. 257f) has the best recent discussion, but in the end rejects the primacy of metaphor.
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Hesse, M. (1988). Theories, Family Resemblances and Analogy. In: Helman, D.H. (eds) Analogical Reasoning. Synthese Library, vol 197. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7811-0_15
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