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Integrating qualitative and quantitative analyses of stance: A case study of English that/zero variation

Published online by Cambridge University Press:  07 September 2021

Timothy Gadanidis
Affiliation:
University of Toronto, Canada
Angelika Kiss*
Affiliation:
University of Toronto, Canada
Lex Konnelly
Affiliation:
University of Toronto, Canada
Katharina Pabst
Affiliation:
University of Toronto, Canada
Lisa Schlegl
Affiliation:
University of Toronto, Canada
Pocholo Umbal
Affiliation:
University of Toronto, Canada
Sali A. Tagliamonte
Affiliation:
University of Toronto, Canada
*
Address for correspondence: Angelika Kiss University of Toronto, Department of Linguistics Sidney Smith Hall, 4th Floor, 100 St. George Street Toronto, ON M5S 3G3, Canada angelika.kiss@mail.utoronto.ca
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Abstract

Previous work has shown that stance—the way speakers position themselves with respect to what they are talking about and who they are talking to—provides powerful insights into why speakers choose certain linguistic variants, beyond correlations with macro-social categories such as gender, ethnicity, and social class. However, as stancetaking moves are highly context-dependent, they have rarely been explored quantitatively, making the observed variable patterns difficult to generalize. This article seeks to contribute to this methodological gap by proposing a formal guide to coding stance and demonstrating how it can be operationalized quantitatively. Drawing on a corpus of eight individuals, self-recorded in three situations with varying levels of social distance, we apply this method to variation between English complementizers that and zero (i.e. no overt complementizer), providing a replicable and theoretically grounded protocol that incorporates both quantitative and qualitative analyses in a variationist sociolinguistic study. (Stance, complementizers, that, English)*

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Type
Article
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press
Figure 0

Figure 1. The stance triangle (reproduced with permission from Du Bois 2007:163).

Figure 1

Table 1. Speaker sample.

Figure 2

Table 2. Stance framework informing the analysis.

Figure 3

Table 3. Coding protocol for stance.

Figure 4

Figure 2. Individual variation in rate of that.

Figure 5

Figure 3. Effect of social distance in rate of that.

Figure 6

Figure 4. Apparent interaction between Investment and matrix subject.

Figure 7

Table 4. Mixed-effects logistic regression model.