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Using a cross-modal naming paradigm this study investigated the effect of sentence constraint and language use on the expectancy of a language switch during listening comprehension. Sixty-five Algerian bilinguals who habitually code-switch between Algerian Arabic and French (AA-FR) but not between Standard Arabic and French (SA-FR) listened to sentence fragments and named a visually presented French target NP out loud. Participants’ speech onset times were recorded. The sentence context was either highly semantically constraining toward the French NP or not. The language of the sentence context was either in Algerian Arabic or in Standard Arabic, but the target NP was always in French, thus creating two code-switching contexts: a typical and recurrent code-switching context (AA-FR) and a non-typical code-switching context (SA-FR). Results revealed a semantic constraint effect indicating that the French switches were easier to process in the high compared to the low-constraint context. In addition, the effect size of semantic constraint was significant in the more typical code-switching context (AA-FR) suggesting that language use influences the processing of switching between languages. The effect of semantic constraint was also modulated by code-switching habits and the proficiency of L2 French. Semantic constraint was reduced in bilinguals who frequently code-switch and in bilinguals with high proficiency in French. Results are discussed with regards to the bilingual interactive activation model (
Some bilingual speakers may daily interact in a context where similar speakers use both languages in the same conversation or even in the same utterance of speech. This type of interaction is usually known as code-switching (CS). During code-switching, bilinguals may be listening to an utterance that starts in their first language (L1) but may or may not end in that same language depending on the speaker’s speech planning (e.g.,
The effect of sentence context in code-switched sentences was also found in studies using event-related potentials (ERPs; e.g.,
In a cross-modal naming (CMN) paradigm (i.e., naming a visual word in an auditory context)
The overall results from the above studies suggest that semantic context as well as the language of the preceding sentence affect the processing of upcoming words in bilingual speakers. However, different bilinguals may have different linguistic experiences that have prepared them as speakers/listeners to use one or the other language separately in one context, or even use both in the same utterance in another context (e.g.,
There has been an increased focus on language use and switching habits of the bilinguals and their effect on switching control processing.
When dense code-switching is not a common language practice of the bilinguals, it is likely that encountering a lexical switch within the same utterance imposes higher cognitive processing demands on control processes in which these bilinguals are not well-trained. Similarly, when bilinguals from a dense code-switching context encounter code-switches that do not allow alternative forms (adaptation), they are forced to use competitive control processes not typical of their language processing. We may speculate that the conflicting results reported in previous studies concerning the ease of code-switching may be due to incongruities between the participants’ habitual interactional contexts and the type of code-switched material on which they have been tested.
Bilinguals who code-switch may also differ in respect to the direction of code-switching, that is, the language they switch from or the “base language.” Many code-switching studies examined switching from L2 to L1. Although this switching pattern is attested among bilingual communities, it is less common than switching from L1 to L2 (e.g.,
The current experiment examined the effect of context language (base language), semantic constraints and language use on the expectancy of a language switch during listening comprehension. The habit and frequency of switching between a pair of languages rather than another may affect lexical expectancy and switching licensing. Code-switching between Algerian Arabic (AA) and French (FR) is conversational and frequent among some Algerian bilinguals but not code-switching between Standard Arabic (SA) and French. One of the possible reasons for this distribution is that although Algerians are introduced to Standard Arabic from the time they start school, and sometimes earlier, it is considered a school language used to study text books and get knowledge. Standard Arabic is never heard in conversations in the street or even in classrooms between students themselves. It is typical, however, to hear Algerian bilinguals speak Algerian Arabic and include French switches of varying length and morphological adaptation to Algerian Arabic structure (
We compared Algerian Arabic-French (AA-FR) code-switching to Standard Arabic-French (SA-FR) code-switching to investigate whether a language as a whole (base language) plays the role of a cue in expecting a language switch. In other words, when switching between a pair of languages that is typically attested in natural code-switching (AA-FR), Algerian bilinguals may expect a switch to French when they hear Algerian Arabic. However, when switching between a pair that is not so typical (SA-FR) Algerian bilinguals may not expect a language switch. In the latter case, code-switches may be harder to process and integrate with the preceding context than in the former case.
The second goal of this study was to examine whether the semantic constraints of the sentence context affects the expectancy of a language switch, and to compare the semantic constraints effect when switching between languages is typical (AA-FR) and when switching between languages is not typical (SA-FR). A high constraint context provides semantic cues that bias toward a specific lexical item and possibly its language (e.g.,
The third goal was to see whether language expectancy in code-switching was affected by the bilingual’s switching habits. Bilinguals who code-switch differ in their habits of using their languages. In a dense code-switching environment, bilinguals may interact in a context in which they switch languages between turns and sentences, or switch languages within the same utterance and tend to adapt words from one language to fit within the structure of the other (e.g.,
Finally, the study also sought to examine whether language expectancy in switching is modulated by French language proficiency. Proficiency may affect language activation in bilinguals with higher proficiency bilinguals showing more parallel activation than lower proficiency bilinguals (
To summarize, the research questions addressed in the current study are: (1) Is language expectancy in code-switching dependent on the base language? That is, does language expectancy differ between a typical code-switching (AA-FR) and a non-typical code-switching (SA-FR) context? (2) Do semantic constraints affect language expectancy in code-switching? (3) Is language expectancy dependent on the frequency of code-switching? (4) Does French L2 proficiency modulate the expectancy of language switching?
To answer these questions, we measured reaction times to the French NP code-switches using a CMN task (e.g.,
The CMN has been demonstrated to measure what is active at certain moments in time during continuing processing of a sentence (e.g.,
Two factors were manipulated in this study: base language, that is, the language preceding the target word (Algerian Arabic or Standard Arabic) and semantic constraint of the context preceding the target word (High or low constrained contexts). The results in this study extend previous findings by exploring the effect of language use and frequency of code-switching. Algerian bilinguals listened to fragments of sentences either in Algerian Arabic or in Standard Arabic then immediately after named a target NP that was always in French. The target NP was thus heard in four different switching conditions: Algerian Arabic high-constraint context (AAH), Algerian Arabic low-constraint context (AAL), Standard Arabic high-constraint context (SAH), and Standard Arabic low-constraint context (SAL). Since all critical trials are code-switching trials, faster reaction times to the presented target words can be interpreted as ease of processing due to language switching expectation. Reaction times to French switches are compared in both base languages (AA and SA) and in both semantic constraint contexts (high and low). The following hypotheses and predictions are formed based on the research questions.
Concerning the first question, if the habit of switching between a certain pair of languages affects the expectancy of a language switching, there should be a base language effect. Participants should expect a switch to French when the base language is Algerian Arabic but not when the base language is Standard Arabic. This is because a switch to French is not typically expected when listening to Standard Arabic and because AA-FR code-switching is the default language switching in everyday conversation. Reaction times to French switches should be faster when Algerian Arabic is the base language than when Standard Arabic is the base language.
As regard to the second research question, if semantic context affects the expectation of a language switch, it is predicted that reaction times to switches in the high-constraint context should be faster than in the low-constraint context, and in particular after Algerian Arabic base language than after Standard Arabic base language. This is because the highly constraining context provides more semantic clues that help in predicting upcoming words, and previous studies showed that more predictable words are processed faster in naming (e.g.,
For the third research question, if language switch expectancy depends on the bilingual’s recurrent switching habits, then reaction times for heavy code-switchers (those who frequently code-switch) should differ from light code-switchers (those who do not switch frequently). In addition, if heavy code-switchers are more experienced with dense code-switching contexts they should employ their cooperative control processes more than light code-switchers. In particular, we should see a difference in processing a switch depending on the extent of daily code-switching. In other words, bilinguals who code-switch more frequently should show more cooperative processes, which will be reflected in their reaction times. We also predict switching habits to interact with base language effect. Because AA-FR code-switching is more recurrent, anticipation of a language switch is more likely when Algerian Arabic is the base language. The difference between heavy code-switchers and light code-switchers should therefore be more apparent in AA-FR than in SA-FR code-switching. We finally predict switching habits to interact with semantic constraint. If language tasks schemas are in more cooperative mode for the heavy code-switchers compared to light code-switchers, then the effect of semantic constraint should differ between heavy and light code-switchers and more so in Algerian Arabic than in Standard Arabic base language.
For the last question, if French proficiency modulates the expectancy of language switching, then high proficiency bilinguals should be different from low proficiency bilinguals in processing the switch. If high proficiency bilinguals show more parallel activation for French, it is predicted that they should be faster overall than low proficient bilinguals and they should show a smaller effect for base language than low proficient bilinguals. Proficiency in French may also modulate the effect of semantic constraint. Highly proficient bilinguals in
The current study was approved by the University of Florida Institutional Review Board (IRB) 02: Protocol #2014-U-0904.
Sixty-five Algerian college students mostly from the National School of Computer Science and the National School of Polytechnics in Algiers participated in this experiment (mean age 22, range 18–25; 31 female and 34 male). All participants were either born in Algiers or came to Algiers at an early age. They all had Algerian Arabic as their mother tongue and either started learning Standard Arabic when they started school or at kindergarten or mosque. However, participants differed in the time of acquiring French. Early bilinguals reported that they started French together with Algerian Arabic or shortly after. They also said that they watched cartoons mostly in French. Late bilinguals started French at school at around age 8, and may or may not have watched cartoons in French before they started French at school. All Bilinguals also claimed that they code-switch with friends and family, but they differ in the time when they started code-switching or in how often they code-switch. Participants were recruited by means of an announcement for the study via leaflets containing conditions for participation and were paid for their participation.
To assess French proficiency, participants completed the French Cloze test developed by
The participants completed a language questionnaire. This was a French translated version of “
In addition to these tests participants were given a semantic fluency test, the Simon task, a working memory test, and an interview. These data will not be reported here.
The stimuli contained a total of 32 non-cognate French target words (underscored in
Sample of experimental item set.
Condition | Sample sentence |
---|---|
AA base language High-constraint (AAH) | Kul-ma naɣslu ssnaan lazem nʃallu |
SA base language High-constraint (SAH) | fi kuli maratin naɣsilu fiha ʔal ʔasnaan jadʒibu ʔan naʃStʕifa |
AA base language Low-constraint (AAL) | Had l’ewled ma rqadsh 3laxatʕer∫ kan ʕendu sʕtʕar fi |
SA base language Low-constraint (SAL) | ʔina haað ʔal walad lam janam liʔanahu kaana juʕaani min ʔalamin fi |
Another 64 sentences were constructed as fillers. Half of the fillers used Algerian Arabic and half used Standard Arabic. To avoid the adoption of a strategy by the participants, half of the fillers had switches at different points of the sentences. Filler switches appeared either earlier toward the beginning of the sentences, in the middle or toward the end of the sentences but never word finally. The other half did not contain switches and were, therefore, only heard. The filler switches were either nouns, verbs, adjectives or adverbs. All experimental and filler sentences contained switching from Arabic to French because this type is more common than switching from French to Arabic. In addition, Algerian Arabic is not traditionally written, rendering Algerian Arabic language unsuitable for the targets in the present paradigm. Four lists of stimuli were constructed using Latin Square, such that each list contained one sentence in each of the four conditions, and no list contained more than one version of each sentence. Each participant saw only one list of 96 sentences and each experimental target NP appeared only once in each list. The fillers were the same across the four lists. Sentences in each list were pseudo-randomized to avoid order effect, and lists were randomly assigned to participants. All sentences were recorded by the same bilingual Algerian female speaker in a soundproof boot using a Marantz PMD660 digital recorder, recording 16-bit stereo PCM sound at a sampling rate of 44.1 kHz. In order to minimize co-articulation, a dummy word “
Once arrived to the study site, the participants first completed the French proficiency cloze test, then completed the following tests not included in the analysis of the current study: a French semantic fluency test, the Simon task, the memory test and the interview in this order. After a short microphone test, participants started the CMN experiment with a practice session. The practice task consisted of five sample trials resembling the experimental and filler sentences, that is, the target words appeared at the end of a sentence, somewhere in the middle or the trial did not have any visual target words. During the practice session the experimenter remained next to the participants and gave feedback on their performance. When the participants started the experiment, the experimenter remained in the room but withdrew to a corner. After the completion of the naming experiment, the participants completed the cloze test for Standard Arabic proficiency followed by the Arabic semantic fluency task (not included in this analysis), and the language history and switching habits questionnaire.
Stimuli in the CMN task were presented on the screen of a laptop computer using the E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, PA, USA). Participants were seated at about 50 cm from the computer with a microphone on a stand sitting in between, and a response button box on the right side of the computer. Participants also wore a headphone set with a microphone attached to the computer digital array mic. While the headphone presented the auditory stimuli, the head-mounted microphone recorded the participants’ naming responses. Reaction times to targets naming were collected using a voice trigger via the standing microphone attached to the response button box. The participants were instructed to listen carefully to the content and read the words that appeared on the screen as quickly and accurately as possible. To make sure the participants paid attention to the content, they were told they would be asked some questions at the end. Participants had to press any button on the response box to proceed to a trial. First, the participant saw a
The analysis was conducted on correct responses only. A correct response is one which was clearly fluent with no stammering or hesitation. Correct responses after self-correction were not accepted. Answers which were ambiguous due to unclear pronunciation or lack of audibility were presented to another Algerian-French bilingual speaker. If the bilingual speaker could not identify the word or hesitated about identifying it, that word was excluded from the analysis. Raw data consisted of 2080 data points. Incorrect or non-identifiable responses constituted 1.3% (27 data points). Accurate responses were equally distributed across the four conditions: Algerian Arabic high-constraint: AAH (98%); Standard Arabic high-constraint: SAH (99%), Algerian Arabic low-constraint: AAL (99%); Standard Arabic low-constraint: SAL (98%). Overall accurate data was 2053 data points (98.7%). We conducted all analyses on the log transformed residual reaction times in order to control for potential effects of target word length, frequency and the position of the trial in the experiment. Log transformed reaction times were residualized for length (in characters) and frequency of the target words, and for the trial number, that is, the order in which a certain item appeared in the experiment. Residuals were calculated by means of a linear mixed effect model conducted on the log transformed response times in the experimental trials, with target word length (in number of characters), target word frequency, and trial order as fixed effects, and a by-subject random intercept. Response times estimated by this model were then subtracted from the log transformed response times to obtain the log residual response times. Outliers were then removed from each condition for each participant using the mean ± 3 standard deviation method. After cutting off for outliers, 2028 data points (98.8%) remained that is 25 data points (1.2%) were removed.
In order to determine which factors to include in the model, tests of correlations using the rcorr () function in the Hmisc package were utilized in order to further explore the correlations/covariances and significance levels for Pearson and Spearman correlations between code-switching habits (as measured by the ACSES questionnaire), age of acquisition of French and proficiency in French (as determined by the Cloze test). There was a medium-sized negative correlation between Age of acquisition and proficiency,
Naming latencies to the French target words were then analyzed using a linear mixed effects model lmer in R (version 3.1.3,
A maximal model was fitted and the model converged without simplifying the random slope structure. Analysis on the residual RTs for the entire group of participants as summarized in
Results of the residual naming latencies mixed effects analysis for whole group.
Effect | β | ||
---|---|---|---|
Intercept (mean) | -0.006 | 0.007 | -0.83 |
Semantic constraint | 0.03 | 0.01 | 2.78* |
Base language | 0.01 | 0.01 | 1.02 |
French proficiency | 0.0005 | 0.0005 | 1.13 |
Code-switching | 0.004 | 0.005 | 0.89 |
Semantic constraint∗Base language | -0.02 | 0.02 | -0.93 |
Semantic constraint∗Code-switching | -0.02 | 0.01 | -1.98* |
Semantic constraint∗French proficiency | -0.002 | 0.001 | -2.64* |
Base language∗Code-switching | -0.01 | 0.01 | -1.64 |
Base language∗French proficiency | 0.0003 | 0.001 | 0.28 |
There was a significant main effect of semantic constraint (
The interaction between semantic constraint and code-switching habits was significant (
Semantic constraint also interacted with French proficiency (
In order to further explore semantic constraint by code-switching habits interaction, we examined the bilinguals at the two extremities of the continuous code-switching line. We compared bilinguals with the lowest code-switching scores to bilinguals with the highest code-switching scores in the overall group. Twenty participants in each code-switching group type (light code-switchers/heavy code-switchers) were selected based on their code-switching scores in the language history and switching habits questionnaire (ACSES). The code-switching score was calculated based on the averages between daily use of languages and code-switching habits. The code-switching groups were matched on age, language proficiency and age of acquisition.
Participant characteristics in the code-switching groups.
Characteristics | Code-switching group |
||
---|---|---|---|
Light code-switchers |
Heavy code-switchers |
||
Code-switching | 4.29 | 6.37 | 0.000* |
Age | 22.05 | 22.00 | 0.90 |
French proficiency | 73.44 | 71.44 | 0.53 |
Age of FR acquisition | 6.30 | 7.15 | 0.21 |
Standard Arabic proficiency | 74.55 | 76.76 | 0.54 |
Age of SA acquisition | 5.10 | 5.15 | 0.81 |
Treating code-switching as categorical, we constructed a linear mixed effect lmer for the heavy code-switchers and a separate lmer for the light code-switchers. Both lmer models contained constraint (High Cloze/Low Cloze, with “high cloze” coded as -0.5 and “low cloze” as 0.5), base language (AA/SA, with “AA” coded as -0.5 and “SA” as 0.5), the continuous variable French Proficiency (FrProf) and the interactions between each two of these factors as fixed effects. The random effects structure was similar to that in the overall analysis model. As before, the fixed effects were centered to minimize collinearity. After centering, the maximal variance inflation factor was smaller than 1.05, and there were no signs of collinearity in the analysis (fixed effect correlations
The analysis from both lmer models for the code-switching groups separately showed a significant main effect of semantic constraint in the light code-switching group: [β: 0.04,
The interaction between semantic constraint and proficiency was explored by comparing the effect of semantic constraint in the lowest proficient bilinguals and the highest proficient bilinguals from the overall group. Based on scores in the French proficiency test, two groups (low proficient/high proficient) were selected, each containing 20 participants. The high proficiency group started learning French at an earlier age than the low proficiency group (
Participant characteristics in the proficiency groups.
Characteristics | Proficiency group |
||
---|---|---|---|
Low proficient |
High proficient |
||
Code-switching score | 5.36 | 5.24 | 0.72 |
Age | 22.05 | 21.60 | 0.34 |
French proficiency | 60.11 | 82.89 | 0.000* |
Age of FR acquisition | 7.50 | 5.40 | 0.001* |
Standard Arabic proficiency | 73.38 | 75.44 | 0.56 |
Age of SA acquisition | 4.85 | 5.05 | 0.40 |
Ninety five percentage confidence interval of the mean differences in raw RTs for semantic effect in overall and group analyses.
Semantic effect by group | 95% confidence interval |
Semantic effect by base language | 95% confidence interval |
||
---|---|---|---|---|---|
2.5 | 97.5 | 2.5 | 97.5 | ||
Overall | -32.79 | -3.32 | Overall AA | -47.57 | -10.62 |
Light code-switching | -55.77 | -6.88 | Overall SA | -29.39 | 4.37 |
Heavy code-switching | -37.52 | 15.33 | Light code-switching AA | -80.58 | -4.97 |
Low proficiency | -71.53 | -11.73 | Light code-switching SA | -52.59 | 13.35 |
High proficiency | -24.98 | 5.13 | Low proficiency AA | -104.40 | -4.143 |
Low proficiency SA | -68.96 | 16.96 | |||
We constructed two linear mixed effects lmer models separately for the two proficiency groups with proficiency treated as categorical to examine sematic effect significance. The models contained constraint (High Cloze/Low Cloze, with “high cloze” coded as -0.5 and “low cloze” as 0.5), base language (AA/SA, with “AA” coded as -0.5 and “SA” as 0.5), code-switching habits (CS) as a continuous variable, and the interactions between each two of these factors as fixed effects. The random effects structure was similar to that in the overall analysis model. The fixed effects were centered to minimize collinearity. The maximal variance inflation factor after centering was smaller than 1.04, and there were no signs of collinearity in the analysis (fixed effect correlations
The effect of semantic constraint was still significant in the low proficiency group: [β: 0.06,
Although the analysis does not show an interaction between semantic constraint and base language we wanted to explore the effect of semantic constraint in each base language separately given that we hypothesized that semantic constraint effect should be more visible in Algerian Arabic because of the high expectation of a French continuation in daily language use. Separate lmer models for Algerian Arabic base language trials and Standard Arabic base language trials revealed a significant main effect of semantic constraint in Algerian Arabic base language: [β: 0.04,
The effect of semantic constraint in the code-switching groups was found to be larger for the light code-switchers. We conducted separate analyses by base language in order to see in which base language was the effect size more important. Comparison of the analyses for Algerian Arabic base language trials and Standard Arabic base language trials in light code-switchers showed a significant main effect of semantic constraint in Algerian Arabic base language: [β: 0.05,
Similarly, the effect of semantic constraint was larger in the low proficiency group. Analysis by base language in the low proficiency group revealed a significant semantic constraint effect in Algerian Arabic base language trials: [β: 0.08,
These results are in line with our prediction that the difference in semantic constraint effect should be seen more in the typical AA-FR code-switching context than in the atypical SA-FR code-switching context. The fact that naming latencies were constantly shorter and the effect sizes constantly larger in Algerian Arabic than in Standard Arabic is evidence that base language did affect the processing of the switch. Semantic facilitation in the high-constraint context in Algerian Arabic base language promoted the processing of a code-switch. In particular, the results suggest that when the switch is part of the typical language pair that is repeatedly used in conversation, its processing is easier. It may also suggest that participants could anticipate a language switch when they heard Algerian Arabic. An observation worthy of notice is that Algerian Arabic and standard Arabic are rather similar in several aspects, and thus differences in effect sizes should not be expected. In this respect, the observed differences between Algerian Arabic and standard Arabic base languages in the different groups, though not always large, are informative for models of code switching.
In this study, we sought to examine the effect of language use and semantic constraints on the expectancy of a language switch during listening comprehension in Algerian bilingual speakers. In particular, expectation of a language switch was compared between two types of code-switched sentences that involved different pairs of languages/varieties. The first occurs between Algerian Arabic and French and is typically conversational and frequent among the bilingual community that code-switches. The second type involves code-switching between Standard Arabic and French which is neither interactional nor typical of Algerian bilinguals. Participants heard the first part of the code-switched sentences presented either in Algerian Arabic or Standard Arabic then, immediately after, read a French NP that completed the first parts. Naming latencies to the French NPs were measured and compared. Faster reaction times suggested an easier processing of the target word, which can be interpreted as a higher expectation of a language switch and ease of switch processing. We asked (1) whether language expectancy in code-switching depends on the base language; (2) whether semantic constraints affect language expectancy in code-switching; (3) whether language expectancy is dependent on the frequency of code-switching; and (4) whether French L2 proficiency modulates the expectancy of language switching.
The findings revealed three effects: semantic constraint effect; an interaction between constraint and code-switching habits; and an interaction between constraint and French proficiency. Bilinguals were significantly faster in the high than in the low-constraint context, suggesting that a language switch is more expected and/or the switch is easier to process when it is supported by the semantic information of the sentence context. This also suggests that the CMN task was sensitive to sentence context and to lexical activation. In addition, the semantic constraint effect, that is, the difference between reaction times in high and low-constraint contexts, was larger when the base language was Algerian Arabic than when it was Standard Arabic. This suggests that the listeners made more use of the semantic cues provided by the high-constraint context in the more typical code-switching that is more recurrent in the everyday interactions. In addition, the frequency of daily code switching modulated the effect of semantic constraint of a sentence context. Light code-switchers but not heavy code-switchers were significantly faster in the high-constraint context than in the low-constraint context preceding the switch. This suggests that the habit of switching between languages interferes with our predictions and with the state of activation of both languages. However, these results look counterintuitive. One would assume that the more a bilingual code-switches the more he/she expects a language switch. We will provide a speculative interpretation of this below. Finally, we found that high proficiency bilinguals had shorter naming latencies than low proficiency bilinguals. French proficiency modulated the effect of semantic constraint on language switch expectancy. Bilinguals with low proficiency in French showed larger constraint effect, with faster reaction times in high-compared to low-constraint context. As proficiency increased the difference in naming latencies between high and low-constraint contexts became smaller, probably due to the overall increase in speed, leading to a reduced effect of sentence context.
The major finding of the current study is that the effect of semantic context is contingent on the bilingual’s language use. In particular, the effect of semantic context occurred to the extent to which the bilinguals code-switch in everyday interactions. Semantic constraint effects were reduced in bilinguals who frequently code-switch, but were visible in bilinguals who code-switch less frequently. Studies reporting reduced sentence influence in the high-constraint context (e.g.,
One of the bilingual language processing models that account for sentence context influence is the Bilingual Interactive Activation+ (BIA+;
The BIA+ model also contains a layer of two language nodes that function as language tags showing the membership of a word. The language nodes become activated late in the process and do not directly influence the lexical candidates. The model recognizes that the presence of a sentence context can pre-activate the language nodes, but because the language nodes cannot inhibit the non-target language words completely, sentence context cannot restrain language non-selective activation. The model does not clearly indicate the mechanism by which sentence effect takes place. With the assumption that the language nodes are activated late and cannot directly influence the lexical candidates, boosted semantic activation by itself is not enough to explain the different effect of sentence context in both groups. To account for the absence of cognate facilitation in the high but not in the low-constraint context,
The central idea of the control process model of code-switching is that language control varies depending on the different interactional contexts of the bilingual speaker and that the processes of language control can adapt to the demands imposed on them by these different interactions. The findings in the current study reveal that the effect of semantic constraint on the naming latencies to the French switches depended on the frequency of daily code-switching. Heavy code-switchers were slower to name the French NPs in both constraint conditions. In addition, the size of constraint effect was very small in bilinguals who frequently code-switch but was larger in bilinguals who do not code-switch frequently. This finding supports the general assumption of the control process model of code-switching that different language contexts induce different habits of language control. Shorter naming latencies in the high-constraint context may suggest that light code-switchers expected more a switch to the other language or that they integrated the switch more easily than heavy code-switchers. However, this interpretation sounds counterintuitive. Bilinguals who frequently code-switch should be more prepared to hear or integrate a switch. How can these results be interpreted by the control model?
The adaptive control hypothesis makes two important assumptions. The first states that experimental contexts can trigger the types of control processes in bilinguals. The prediction that follows is that the bilingual’s reactions to an experimental context can vary depending on how well the context fits the type of control processes for that bilingual. The second assumption concerns the individual differences. While bilingual speakers may experience more than one type of interactional contexts, their dominant type of language control is contingent on the typical exchanges that are recurrent within their speech of community. The model thus predicts that bilinguals who experience different interactional contexts may show adaptive responses that vary depending on how typical they are of each interactional context. The type of bilinguals tested in the current study are more representative of the dense code-switching in the Green and Wei model because they tend to adapt words morphologically as well as phonologically in informal contexts, although they may use French only during classroom hours, or use insertion in some other contexts. However, some of those participants are better representatives of dense code-switchers than others. The light code-switchers use both languages daily but do not frequently code-switch; their switches may be more regarded as insertions rather than integrated switches. The bilinguals who claimed they code-switch regularly may include more integrated switches than bilinguals who code-switch less frequently. In fact, some bilinguals asked during the training session whether they should read the target words in Algerian Arabic (meaning with Arabic phonology) or in French. Interestingly, even reminding the participants to read the targets in French did not eliminate few errors of the kind of phonological integration. In this case, those who frequently code-switch may be more familiarized with control processes that permit opportunistic planning, but those who do not code-switch frequently, and yet use both languages daily, may be more trained with interference suppression that taps on competitive relationship between the language schemas. On the other hand, the stimuli in the current study include code-switches that are in the form of insertion, baring no syntactic or phonological adaptation in the base language structure. When these stimuli are encountered, the language schemas are forced to consistently restrain from adapting the words. The stimuli may also require the participants to be in a coupled mode in which control passes from one schema to the other. In this case, the bilinguals who do not frequently code-switch may be more used to the type of stimuli presented in this study. The results revealed that light code-switchers showed larger semantic constraint effects that reflects facilitation of response in the high compared to the low context. This may suggests that the stimuli context triggered the control processes which the light code-switchers practiced more in their daily interactional contexts. By contrast, heavy code-switchers took longer time to name the switches and showed reduced semantic effects suggesting that facilitation in the high-constraint context did not occur. The stimuli should have forced them to engage control processes that are not typical of their interactional context. Heavy code-switchers had to control for the target words adaptation and engage a coupled control needed for insertion, whereas they are more used to an open control in which adaptation is allowed.
We turn now to consider the effect of base language. A main question in this study was to determine the effect of the languages involved in code-switching on the expectancy of a language switch. Comparison of effect sizes showed systematically a larger effect of sentence constraint in Algerian Arabic base language than in Standard Arabic base language. The results suggest greater expectancy of a switch when it is part of the typically conversational, recurrent code-switching. These results are even more important taking into account the relationship between Algerian Arabic and Standard Arabic. Out of 32 sentences, tested in this study, that occurred in the high constraining context 22 sentences were biased toward a target continuation that is shared between Algerian Arabic and Standard Arabic, assuming that the items are indeed predicted in the same language of the context. For instance, if a sentence context in Algerian Arabic constrained toward the Algerian Arabic
The results concerning base language effect may be better understood by considering how the three languages are connected and stored in the bilingual memory. Both code-switching groups had moderately advanced level of proficiency in French and Standard Arabic. They acquired French at about 6/7 years of age and Standard Arabic at about 5. However, the groups differed in the frequency of code-switching. The findings suggest that in the light code-switchers, the French target item was already activated in the high-constraint context with the other translations in the base languages. When the bilinguals named the words in French they benefited from the early activation leading to a faster lexical retrieval. For the heavy code-switchers, activation of the French forms may not be as simultaneous as the other languages. Thus, naming the French targets would require extra time. The organization of lexical items may differ greatly depending on how the bilinguals represent the words semantically across the languages they speak (e.g.,
To summarize, this study investigated code-switching processing in bilinguals who belong to a community where code-switching between Algerian Arabic and French is typical and dense. However, while these bilinguals differ in the amount and daily frequency of code-switching between Algerian Arabic and French they all claim that code-switching between Standard Arabic and French is not attested, not typical and find it rather odd to hear. During code-switching, bilingual speakers may anticipate a language switch. Expectancy of a language switch is more enhanced in a semantically rich context but also in a more typical context involving languages that are more frequently used in daily interactions. Anticipation of a language switch does not seem to depend solely on proficiency in the switch language. Results in the current study show that the ease of switching also depends on the habit and frequency of code-switching. These finding could be explained within the adaptive control hypothesis (
SK designed the study, collected and analyzed the data, and wrote the manuscript; EK directed the study, and was involved in the design and data analysis, and contributed to parts of the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank