The Structure of Causal Evidence Based on Eliminative Induction

Topoi 33 (2):421-435 (2014)
  Copy   BIBTEX

Abstract

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,386

External links

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

Through your library

Similar books and articles

Causality assessment in epidemiology.Paolo Vineis - 1991 - Theoretical Medicine and Bioethics 12 (2).
Variational Causal Claims in Epidemiology.Federica Russo - 2009 - Perspectives in Biology and Medicine 52 (4):540-554.
Induction and objectivity.F. John Clendinnen - 1966 - Philosophy of Science 33 (3):215-229.

Analytics

Added to PP
2014-02-24

Downloads
65 (#244,525)

6 months
9 (#290,637)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

Wolfgang Pietsch
Technische Universität München

References found in this work

Fact, Fiction, and Forecast.Nelson Goodman - 1965 - Cambridge, Mass.: Harvard University Press.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - New York: Cambridge University Press.
A treatise on probability.John Maynard Keynes - 1921 - Mineola, N.Y.: Dover Publications.
Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.

View all 41 references / Add more references