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Subject relative who in Ontario, Canada: Change from above in a transplanted ecology

Published online by Cambridge University Press:  28 October 2022

Marisa Brook*
Affiliation:
Department of Linguistics, University of Toronto, Toronto, ON, Canada
Sali A. Tagliamonte
Affiliation:
Department of Linguistics, University of Toronto, Toronto, ON, Canada
*
Author for correspondence: Marisa Brook. E-mail: marisa.brook@utoronto.ca
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Abstract

Who as a restrictive relativizer in English is an old change from above. In urban dialects, it still acts as a prestige form, whereas it is infrequent or negligible in rural British and American varieties. We compare earlier findings from Toronto, the largest city in the province of Ontario (D’Arcy & Tagliamonte, 2010), with a range of communities from the Ontario Dialects Project (Tagliamonte, 2003–present). While none of the rural locations has as much who as Toronto, there is a substantial range. Regions along the major highways to the north and east of the city have more who, while the smaller towns in less accessible locations have less, consistent with a Cascade Model effect (Labov, 2003). Nonetheless, who shows evidence of diffusion, increasing in apparent time in recent decades. We suggest that this reflects overt pressure from above, consistent with the enduring role that prestige plays in English relativizer variation.

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Type
Articles
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. Published by Cambridge University Press
Figure 0

Map 1. Ontario communities (Google Maps, 2018).

Figure 1

Table 1. Communities in Ontario with distances from Toronto (Google Maps 2017–2018) and populations.

Figure 2

Table 2. Contexts of the zero-subject relativizer in Belleville.

Figure 3

Table 3. Proportions and total number of subject relativizers in each Ontario community. Values for Toronto are from D’Arcy and Tagliamonte (2010:392).

Figure 4

Figure 1. Subject relativizers as percentage of the total subject relatives in 10 Ontario communities. Values for Toronto are from D’Arcy and Tagliamonte (2010:392).

Figure 5

Figure 2. Conditional inference tree (Hothorn et al., 2006) conducted in R 3.6.3 (R Core Team, 2020).

Figure 6

Figure 3. Subject relativizers as percentage of the total subject relatives in five regions of Ontario. Values for Toronto are from D’Arcy and Tagliamonte (2010:392).

Figure 7

Figure 4. Proportions of who in five Ontario locations by animacy of the head NP. Values for Toronto are from D’Arcy and Tagliamonte (2010:392).

Figure 8

Figure 5. Proportion of who among subject relativizers in apparent time (i.e., by decade of birth).

Figure 9

Figure 6. Proportion of subject relative who in apparent time (i.e. by decade of birth) by gender.

Figure 10

Figure 7. Proportion of who among subject relativizers in apparent time (i.e., by decade of birth), by education level (more-educated = at least some postsecondary education).

Figure 11

Figure 8. Proportion of who among subject relativizers in apparent time (i.e., by decade of birth), by occupation (white collar versus blue collar).

Figure 12

Table 4. Proportions of who in five Ontario locations by animacy of the head NP. Values for Toronto are from D’Arcy and Tagliamonte (2010:392).

Figure 13

Table 5. Mixed-effects logistic regression on the likelihood of who as a relativizer (versus all of the alternatives together) for tokens with [+human] head nouns.