Although most discussions of methodological positions in the social sciences will cite realism alongside positivism and interpretivism, in empirical practice the first position is uncommon. The best-known realist programme in social science, Roy Bhaskar's critical realism, has many supporters yet, despite its commitment to scientific naturalism, it has had little or no impact on quantitative research in social science. The only important exception has been Ray Pawson's (1989) A Measure for Measures, which is a reconstruction of survey method along realist lines. Now there may be good sociological reasons for this lack of realist penetration into quantitative research, but there are also good ontological grounds for a rejection (by quantitative researchers) of critical realism as it currently stands. In this paper we will defend the overall project of scientific realism in social research, but we will be critical of its current principal manifestation (of critical realism) in one crucial respect, that of necessity and what this then implies for probability. We will claim that the particular view of necessity critical realists adopt leads them to criticise empiricist versions of probability, but to offer nothing back in return. We take it as axiomatic that quantitative research needs some theory of probability in order to be able to explain and predict.
|Title of host publication||Making realism work|
|Subtitle of host publication||realist social theory and empirical research|
|Editors||Bob Carter, Caroline New|
|Place of Publication||London|
|Number of pages||20|
|ISBN (Print)||9780415347716, 9780415300612|
|Publication status||Published - 19 Aug 2004|