Connectionism, a new technique for modeling cognitive processes, has been presented by its supporters as a revolutionary advance that will soon replace conventional artificial intelligence (AI) research based on the serial computer. In this thesis, I identify three 'gambits' with which critics attempt to undermine connectionist claims, and show that use of these gambits depends on the status of the respondent's own discipline. I argue that in cases where the respondent's discipline has an accepted identity, for example biology and psychology, they take contradictory stances on the issue of continuity between their discipline and connectionism. By contrast, responses from supporters of AI, which has an uncertain status, insist on a continuous relationship between connectionism and AI. To account for this, I suggest that claims made by both supporters and critics of connectionism, which those actors would regard as purely cognitive, are tacitly structured by Kuhn's model of scientific change. As certain claims which the actors would describe as purely cognitive can be accounted for by the presence in common scholarly parlance of a particular philosophical model of scientific change, I conclude that in the confrontation between connectionism and conventional AI there exists a complex relationship between social and cognitive processes. / Master of Science