Research Article

Toward a model of grammaticality judgments1

MARKUS BADER^a1 c1 and JANA HÄUSSLER^a1 c2

^a1 University of Konstanz

Abstract

This paper presents three experiments that investigate the relationship between gradient and binary judgments of grammaticality. In the first two experiments, two different groups of participants judged sentences by the method of magnitude estimation and by the method of speeded grammaticality judgments in a single session. The two experiments involved identical sentence materials but they differed in the order in which the two procedures were applied. The results show a high correlation between the magnitude estimation data and the speeded grammaticality judgments data, both within a session and across the two sessions. The third experiment was a questionnaire study in which participants judged the same sentences as either grammatical or ungrammatical without time pressure. This experiment yielded results quite similar to those of the other two experiments. Thus gradient and binary judgments both provide valuable and reliable sources for linguistic theory when assessed in an experimentally controlled way. We present a model based on Signal Detection Theory which specifies how gradient grammaticality scores are mapped to binary grammaticality judgments. Finally, we compare our experimental results to existing corpus data in order to inquire into the relationship between grammaticality and frequency of usage.

(Received September 03 2008)

(Revised June 04 2009)

(Online publication November 30 2009)

Correspondence:

^c1 Authors' addresses: University of Konstanz, Department of Linguistics, Universitätsstraße 10, Fach D191, D-78457 Konstanz, Germany markus.bader@uni-konstanz.de

^c2 University of Konstanz, Department of Linguistics, Universitätsstraße 10, Fach D191, D-78457 Konstanz, Germany jana.haeussler@uni-konstanz.de

Footnotes

[1] This work was supported by the Deutsche Forschungsgemeinschaft (SFB 471, Project D2). For helpful comments, we would like to thank Josef Bayer, Simon Hopp, Tom Wasow, and two anonymous reviewers.