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Exploring language dominance through code-switching: intervocalic voiced stop lenition in Afrikaans–Spanish bilinguals

  • Nicholas Henriksen EMAIL logo , Andries W. Coetzee , Lorenzo García-Amaya and Micha Fischer
From the journal Phonetica

Abstract

The present study examines the relationship between the two grammars of bilingual speakers, the linguistic ecologies in which the L1 and L2 become active, and how these topics can be explored in a bilingual community undergoing L1 attrition. Our experiment focused on the production of intervocalic phonemic voiced stops for L1-Afrikaans/L2-Spanish bilinguals in Patagonia, Argentina. While these phonemes undergo systematic intervocalic lenition in Spanish (e.g., /b d ɡ/ > [β ð ɣ]), they do not in Afrikaans (e.g., /b d/ > [b d]). The bilingual participants in our study produced target Afrikaans and Spanish words in unilingual and code-switched speaking contexts. The results show that: (i) the participants produce separate phonetic categories in Spanish and Afrikaans; (ii) code-switching affects the production of the target sounds asymmetrically, such that L1 Afrikaans influences the production of L2 Spanish sounds but not vice versa; and (iii) this L1-to-L2 influence remains robust despite the instability of the L1 itself. Altogether, our findings speak to the persistence of a bilingual’s L1 phonological grammar despite cross-generational L1 attrition.


Corresponding author: Nicholas Henriksen, Romance Languages and Literatures, University of Michigan, 4108 Modern Languages Building, 812 East Washington Street, Ann Arbor, MI48109-1275, USA, E-mail:

  1. Research funding: This project was funded by a University of Michigan Humanities Collaboratory Project Funding grant entitled “From Africa to Patagonia: Voices of Displacement”.

  2. Author contributions: All four authors contributed equally to this project.

  3. Conflict of interest statement: The authors have no conflicts of interest to declare.

  4. Ethical approval: All participants gave their informed written consent to participate in this study, per University of Michigan Institutional Review Board, #HUM00131528.

Appendix A: Target words.

AfrikaansSpanish
Word-initial/b/Stressedboek ‘book’

boer ‘farmer’

baard ‘beard’
/b/Stressedbarco ‘ship’

boca ‘mouth’

buho ‘owl’
Unstressedbedrog ‘corruption’

bedank ‘to thank’

begin ‘begin’
Unstressedbufanda ‘scarf’

barato ‘cheap’

vecino ‘neighbor’
/d/Stresseddankie ‘thank you’

dorp ‘town’

donkie ‘donkey’
/d/Stresseddedo ‘finger’

diente ‘tooth’

donde ‘where’
Unstresseddateer ‘to date’

dinee ‘formal dinner’

dosyn ‘dozen’
Unstresseddifícil ‘difficult’

domingo ‘Sunday’

dolor ‘pain’
/g/Stressedn/a/g/Stressedgoma ‘rubber’

guerra ‘war’

gordo ‘fat’
Unstressedn/aUnstressedgallina ‘hen’

ganar ‘to win’

ganado ‘livestock/cattle’
Word-medial/b/Stressedgebore ‘born-past’

gebou ‘building’

gebak ‘bake-past’
/b/Stressedcabeza ‘head’

cebollas ‘onions’

caballo ‘horse’
Unstressednaby ‘close to’

soebat ‘to beg/plead’

dobbel ‘to gamble’
Unstressedlob‘wolf’

globo ‘balloon’

rabo ‘tail’
/d/Stressedgedoen ‘do-past’

gedink ‘think-past’

geduldig ‘patient’
/d/Stressedmedir ‘to measure’

Navidad ‘christmas’ ciudad ‘city’
Unstressedhoede ‘hats’

beddens ‘beds’

padda ‘frog’
Unstresseddedo ‘finger’

casado ‘married’

sábado ‘Saturday’
/g/Stressedn/a/g/Stressedbigote ‘moustache’

regalo ‘gift’

pagar ‘to pay’
Unstressedn/aUnstressedhigo ‘fig’

amigo ‘friend’

fuego ‘fire’

Appendix B: Model summaries.

C-DurationTermEstimateStd. errort-valuedfp-Value
Fixed parametersIntercept4.650.0591.4532.10<0.001
CS Afrikaans−0.030.05−0.75257.990.452
CS Spanish−0.100.05−2.20376.630.029
Unil. Spanish−0.420.05−9.03383.30<0.001
Stressed-medial−0.080.05−1.61378.910.108
Unstressed-initial−0.300.05−5.93379.66<0.001
Unstressed-medial−0.690.05−13.98381.01<0.001
Alveolar/dental−0.130.02−7.08474.38<0.001
Velar−0.090.02−3.49470.36<0.001
CS Afrikaans-stressed-medial−0.080.06−1.31261.010.191
CS Spanish-stressed-medial−0.460.06−7.30370.58<0.001
Unil.Spanish-stressed-medial−0.270.06−4.24373.17<0.001
CS Afrikaans-unstressed-initial0.060.070.91263.280.362
CS Spanish-unstressed-initial−0.070.06−1.08379.930.283
Unil.Spanish-unstressed-initial−0.030.06−0.52383.080.602
CS Afrikaans-unstressed-medial−0.020.06−0.33260.190.739
CS Spanish-unstressed-medial0.120.061.88380.470.061
Unil.Spanish-unstressed-medial0.310.064.84384.36<0.001
Random parametersSPEAKER * WORD (Intercept)0.11 (SD)
SPEAKER * MODE * STRESS * POSITION * POA (Intercept)0.12 (SD)
SPEAKER (Intercept)0.11 (SD)
Residual0.22 (SD)--
CV-RatioTermEstimateStd. errort-valuedfp-Value
Fixed parametersIntercept0.620.0226.4024.17<0.001
CS Afrikaans−0.040.02−2.26262.580.025
CS Spanish−0.020.02−1.30371.820.196
Unil. Spanish0.050.022.82377.690.005
Stressed-medial0.020.020.85374.130.393
Unstressed-initial0.090.024.41374.41<0.001
Unstressed-medial0.140.026.89375.87<0.001
Alveolar/dental−0.020.01−2.53470.810.012
Velar−0.040.01−3.63466.97<0.001
CV-RatioTermEstimateStd. errort-valuedfp-Value
CS Afrikaans-stressed-medial0.020.030.93264.900.355
CS Spanish-stressed-medial0.130.034.94365.90<0.001
Unil.Spanish-stressed-medial0.100.033.82368.45<0.001
CS Afrikaans-unstressed-initial0.010.030.29266.870.769
CS Spanish-unstressed-initial0.040.031.33374.290.185
Unil.Spanish-unstressed-initial0.050.031.89377.130.060
CS Afrikaans-unstressed-medial0.070.032.62264.310.009
CS Spanish-unstressed-medial0.120.034.68374.36<0.001
Unil.Spanish-unstressed-medial0.070.032.45377.820.015
Random parametersSPEAKER * WORD (Intercept)0.04 (SD)
SPEAKER * MODE * STRESS * POSITION * POA (Intercept)0.05 (SD)
SPEAKER (Intercept)0.06 (SD)
Residual0.08 (SD)

Appendix C

This plot displays the mean normalized dispersion values by MODE (in vertical panels) and combination of STRESS and WORD POSITION (along x-axis). To quantify the variation of values for each combination of MODE and STRESS and WORD POSITION, we developed a metric to calculate the extent of dispersion between speakers within each of the 16 cells plotted in Figure 7. Since C/V-Ratio and C-Duration were measured on differently-scaled units, we normalized the raw values for each speaker through z-score transformation, and then recalculated the per-speaker mean normalized values from each of the 16 cells. Using these normalized means, we calculated a measure of the two-dimensional variance (i.e., “dispersion”) for each cell, defined as the mean distance between each of the per-cell speaker averages; these outcomes are plotted below. In this figure, a smaller dispersion score corresponds to values that are clustered closer together in the two-dimensional space from the respective cell in Figure 7, and a larger score corresponds to values that are more spread apart.

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Published Online: 2021-06-23
Published in Print: 2021-06-25

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