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Jenna Hotton

Bio: Jenna Hotton is an academic researcher. The author has contributed to research in topics: Canadian English. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

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TL;DR: This paper reported on the first-ever linguistic study of the variety of English spoken in the Gaspe region of eastern Quebec, which is 86 percent French-speaking, focusing on data from the 124 participants who still live in the region.
Abstract: This paper reports on the first-ever linguistic study of the variety of English spoken in the Gaspe region of eastern Quebec, which is 86 percent French-speaking. An on-line survey was used to gather data from 200 participants on 58 phonological, grammatical and lexical variables, drawn mostly, for comparative purposes, from earlier research on Canadian and Quebec English. The analysis, focusing on data from the 124 participants who still live in the Gaspe region, produces a complex linguistic portrait of the community. It displays a unique mixture of Canadian, Quebec, Maritime and rural features, reflecting its location near the boundary between Quebec and New Brunswick, with evidence of both convergence with and divergence from Quebec English as spoken in Montreal. It also shows more frequent use of several Gallicisms, or borrowings from French, suggesting that this effect of language contact is encouraged by its minority status.

3 citations


Cited by
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TL;DR: The authors compared the effects of city and ethnicity with respect to Quebec English speakers' participation in two ongoing changes affecting /æ/ in Canadian English: retraction as part of the Canadian Shift and tensing in prenasal environments.
Abstract: This study compares the effects of city and ethnicity with respect to Quebec English speakers’ participation in two ongoing changes affecting /æ/ in Canadian English: retraction as part of the Canadian Shift and tensing in prenasal environments. Quebec English speakers might be expected to differ in their behavior with regard to these two phenomena as compared to other Canadian English speakers. Based on an analysis of Cartesian distances and a mixed-effects model using spontaneous speech, the authors find that Quebec English speakers are less advanced with respect to the Canadian Shift, especially speakers from Quebec City. For tensing, British-origin speakers from Montreal and Quebec City are found to pattern similarly, participating in the more widespread patterning, while Jewish and Italian speakers are moving in the opposite direction. The authors argue that this move away from characteristically Canadian patterns is an artefact of the interplay between the two phenomena under study, reflective of differential replication of the Canadian Shift in the two environments.

2 citations

Proceedings Article
11 May 2020
TL;DR: A 78.8-million-tweet, 1.3-billion-word corpus aimed at studying regional variation in Canadian English with a specific focus on the dialect regions of Toronto, Montreal, and Vancouver is presented.
Abstract: We present a 78.8-million-tweet, 1.3-billion-word corpus aimed at studying regional variation in Canadian English with a specific focus on the dialect regions of Toronto, Montreal, and Vancouver. Our data collection and filtering pipeline reflects complex design criteria, which aim to allow for both data-intensive modeling methods and user-level variationist sociolinguistic analysis. It specifically consists in identifying Twitter users from the three cities, crawling their entire timelines, filtering the collected data in terms of user location and tweet language, and automatically excluding near-duplicate content. The resulting corpus mirrors national and regional specificities of Canadian English, it provides sufficient aggregate and user-level data, and it maintains a reasonably balanced distribution of content across regions and users. The utility of this dataset is illustrated by two example applications: the detection of regional lexical and topical variation, and the identification of contact-induced semantic shifts using vector space models. In accordance with Twitter’s developer policy, the corpus will be publicly released in the form of tweet IDs.

2 citations