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Myths and facts about loanword development

Published online by Cambridge University Press:  23 November 2012

Shana Poplack
Affiliation:
University of Ottawa
Nathalie Dion
Affiliation:
University of Ottawa
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Abstract

This study traces the diachronic trajectory and synchronic behavior of English-origin items in Quebec French over a real-time period of 61 years. We test three standard assumptions about such foreign incorporations: (1) they increase in frequency; (2) they originate as code-switches and are gradually integrated into recipient-language grammar; and (3) the processes underlying code-switching and borrowing are the same. Results do not support the assumptions. Few other-language items persist, let alone increase. Linguistic integration is abrupt, not gradual. Speakers consistently distinguish lone other-language items from multiword fragments on each of five linguistic diagnostics tested. They borrow the former, and code-switch the latter. Code-switches are not converted into borrowings; instead the decision to code-switch or borrow is made at the moment the other-language item is accessed. We explore the implications of these findings for understanding the processes by which other-language incorporations achieve the status of native items and their consequences for theories of code-switching and borrowing.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2012
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Table 1.Characteristics of the data used for the current study

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Table 2.“Canonical” distribution of three categories of mixing strategies

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Table 3.Distribution of nonce lone other-language items (n = 2139)

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Table 4.Distribution of nonce lone other-language items with a measurable trajectory (n = 245)

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Figure 1.Token frequency (black) and diffusion across speakers (gray) of advancing nonces (based on tokens in a later corpus of lexical types that appeared as nonce forms in an earlier corpus).

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Table 5.Rate of French affixation on three types of nonce verbs over time

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Figure 2.Rate of English affixation on three types of plural nonce nouns over time (n = 106).

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Figure 3.Rate of determiner presence on three types of nonce nouns over time (n = 294).

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Table 6.Consistency in gender assignment over time

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Figure 4.Distribution of English words by part of speech. Here, and in subsequent figures, CS = code-switch.

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Figure 5.Distribution of nonce lone other-language items by part of speech: 19th, 20th and 21st-century corpora.

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Figure 6.Language of affix on verbs in three language-mixing categories (n = 721).

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Figure 7.Marks on plural nouns in three language-mixing categories (n = 173).

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Figure 8.Plural marks on plural nouns in three language-mixing categories.

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Figure 9.Determiner usage on nouns in three language-mixing categories (n = 3676).

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Figure 10.Percentage of determiner usage consistent with patterns of French and English.

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Figure 11.Placement of adjectives with respect to nouns in three language-mixing categories (n = 300).

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Figure 12.Percentage of adjective placement consistent with patterns of French and English.

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Table 7.Consistency in gender assignment to idiosyncratic other-language items

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Table 8.Consistency in gender assignment to widespread other-language items

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Figure 13.Speaker propensity to produce multiword code-switches and nonce lone other-language items. Propensity to CS: occasional = 0–3 (28 speakers, 25% of sample); moderate = 4–17 (58 speakers, 50% of sample); copious = 18–132 (30 speakers, 26% of sample). Propensity to nonce borrow: occasional = 0%–6% (34 speakers, 28% of sample), moderate = 7%–13% (56 speakers, 47% of sample), copious = 14%–39% (30 speakers, 25% of sample).

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Table 9.Characteristics of language-mixing strategies