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Code-switching in linguistics: a position paper.

1. Introduction

2. Code-Switching vs. Borrowing

3. Grammaticality

4. Variability and Uniformity

5. conclusions and implications for future research, acknowledgments, conflicts of interest.

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Deuchar, M. Code-Switching in Linguistics: A Position Paper. Languages 2020 , 5 , 22. https://doi.org/10.3390/languages5020022

Deuchar M. Code-Switching in Linguistics: A Position Paper. Languages . 2020; 5(2):22. https://doi.org/10.3390/languages5020022

Deuchar, Margaret. 2020. "Code-Switching in Linguistics: A Position Paper" Languages 5, no. 2: 22. https://doi.org/10.3390/languages5020022

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HYPOTHESIS AND THEORY article

Codeswitching: a bilingual toolkit for opportunistic speech planning.

• 1 Department of Psychology, McGill University, Montreal, QC, Canada
• 2 Department of Language Science, University of California, Irvine, Irvine, CA, United States
• 3 Center for Language Science, The Pennsylvania State University, University Park, PA, United States
• 4 Department of Spanish, Italian and Portuguese, The Pennsylvania State University, University Park, PA, United States

The ability to engage in fluent codeswitching is a hallmark of the flexibility and creativity of bilingual language use. Recent discoveries have changed the way we think about codeswitching and its implications for language processing and language control. One is that codeswitching is not haphazard, but subject to unique linguistic and cognitive constraints. Another is that not all bilinguals codeswitch, but those who do, exhibit usage patterns conforming to community-based norms. However, less is known about the cognitive processes that regulate and promote the likelihood of codeswitched speech. We review recent empirical studies and provide corpus evidence that highlight how codeswitching serves as an opportunistic strategy for optimizing performance in cooperative communication. From this perspective, codeswitching is part and parcel of a toolkit available to bilingual codeswitching speakers to assist in language production by allowing both languages to remain active and accessible, and therefore providing an alternative means to convey meaning, with implications for bilingual speech planning and language control more generally.

Introduction

Traditionally, the study of codeswitching production and bilingual speech more generally has been carried out within separate disciplines, where cognitive psychologists and psycholinguists have primarily centered on exogenously-cued language switching, 1 and sociolinguists have focused on the analysis of codeswitching patterns within discourse of members of a given speech community. Formal disciplinary differences aside, one recurrent cross-disciplinary finding is that even when highly proficient bilinguals retain full control over the choice of how to use the two languages, switching is cognitively more demanding or costly than staying in one language (e.g., Gollan and Ferreira, 2009 ; Fricke et al., 2016 ; Gollan and Goldrick, 2016 ; cf. Johns and Steuck, 2018 ). This finding appears counterintuitive given the ubiquity of codeswitching in many bilingual communities, and thus begs the question of why bilinguals codeswitch in the first place. Here we put forth the proposal, based on quantitative analyses of spontaneous codeswitched speech, that codeswitching serves as a toolkit, or an opportunistic strategy for optimizing task performance in cooperative communication. While previous research has focused largely on the costs that codeswitching brings to language processing ( Guzzardo Tamargo et al., 2016 ; Adamou and Shen, 2017 ; Beatty-Martínez and Dussias, 2017 ; Byers-Heinlein et al., 2017 ; for reviews see Van Hell et al., 2015 , 2018 ), we consider the possible advantages that codeswitching may offer to language producers during bilingual language interactions. Critical to this endeavor is the view that codeswitching offers a unique flexibility that is driven by an interplay of bottom-up and top-down processes, but through which resources from both languages are ultimately recruited to convey speakers’ communicative intentions.

We refer to codeswitching patterns as the tendency to switch at particular syntactic or prosodic boundaries, or as proposed by Torres Cacoullos and Travis (2018) “…of the places where bilinguals can switch, where they prefer to do so” (p. 175; see also Poplack, 1993 ). It is important to note that bilingual speakers use their languages in different ways, and not all contexts of language use incur the same cognitive demands in speech production ( Green and Abutalebi, 2013 ; Luk and Bialystok, 2013 ; Green and Wei, 2014 ). Differences in codeswitching experience can affect not only language abilities ( Beatty-Martínez and Dussias, 2017 ; Valdés Kroff et al., 2018 ), but have also been proposed to mediate the relation between language and cognitive processes ( Beatty-Martínez et al., 2019 ). Furthermore, while not all bilinguals regularly codeswitch, those who do exhibit usage patterns conforming to community-based norms ( Beatty-Martínez et al., 2018 ; Torres Cacoullos and Travis, 2018 ; Ramírez Urbaneja, 2019 ).

Although codeswitching serves a variety of discourse functions, intentions to codeswitch are likely subject to pragmatic, and interactional constraints. Poplack (1987) compared codeswitching behaviors of Spanish-English Puerto Ricans living in New York City to those of French-English bilinguals in Ottawa-Hull, Canada, and observed differences in how the communities engaged in codeswitching. While Puerto Ricans adopted an open discourse mode, opportunistically threading together words and phrases from each language in order to convey the intended meaning, Ottawa-Hull bilinguals maximized the salience of switch points to fulfill rhetorical functions such as contrast and emphasis (see also Myslín and Levy, 2015 , for a similar observation with Czech-English bilinguals). Importantly, these findings suggest that bilinguals may plan speech differently as a function of their communicative goals ( Gardner-Chloros et al., 2013 ).

Codeswitching patterns are also constrained by bilingual ability. Whereas highly proficient bilinguals typically favor complex intra-sentential codeswitches and exhibit greater consistency of codeswitching occurrences, less proficient bilinguals tend to limit switching to freely movable constituents (e.g., tag items such as “I mean” or “you know”; Poplack, 1980 ), and show less voluntary control of their switching behavior ( Lipski, 2014 ). This observation is particularly relevant for bilingual speech planning because it shows that “fluent bilinguals codeswitch because they can, and not because they cannot speak any other way” ( Lipski, 2014 , p. 24). It follows that a better understanding of the processes that mediate codeswitching requires the consideration of bilinguals’ habits of language use as well as the interactional demands of their language environment.

This paper is not intended as a comprehensive review of the literature on codeswitching. Instead, we attempt to take stock of recent empirical findings from spontaneous language use that highlight how codeswitching enables bilinguals to handle cognitively demanding aspects of speech planning. We first consider the influence of bottom-up processes (i.e., structural priming) in codeswitching behavior, and argue that, while codeswitching may be sensitive to priming, bottom-up processes are ultimately modulated by top-down influences so as to convey speakers’ communicative intentions ( Green, 2018 ). As a first approximation, we provide corpus evidence of our own, focusing on complex noun phrases (NPs) in Spanish-English bilinguals who have extensive codeswitching experience, to exemplify how speaker intentions guide production choices in codeswitched speech. While it is beyond the scope of this article to fully evaluate our proposal, we hope to demonstrate the potential of this approach to highlight the value of naturalistic data and improve our understanding of how proficient bilinguals manage to use their two languages opportunistically in production.

The Contributions of Bottom-Up Factors in Codeswitching

Speakers’ production choices are not independent of their past experiences, as evidenced by the tendency (commonly referred to as structural persistence or priming) to reuse structures that they have recently produced or comprehended themselves ( MacDonald, 2013 ; Dell and Chang, 2014 ; Torres Cacoullos and Travis, 2018 ). Priming effects are widespread in spontaneous speech and have been observed both within individual languages (within-language priming) and cross-linguistically, where producing/hearing a structure in one language increases the probability of producing a related structure in the other language (see Pickering and Ferreira, 2008 ; Gries and Kootstra, 2017 , for reviews). Priming has been proposed as an important mechanism for speech planning, serving a facilitative function in processes related to selection and retrieval ( MacDonald, 2013 ). In the case of bilinguals, priming may provide a unique lens with respect to the strength of associations between cross-linguistic representations and the levels of processing at which cross-language activation can occur.

Priming effects are generally stronger when the prime and target are similar, which has led to the hypothesis that words with overlapping form and meaning across languages (e.g., cognates) may precipitate codeswitching ( Clyne, 2003 ; Broersma and de Bot, 2006 ; Broersma, 2009 ; de Bot et al., 2009 ). The logic is that cognate words can enhance the likelihood of a codeswitch by triggering a relatively high degree of cross-language activation, and in so doing, allowing the language system to switch from output in one language to output in another language. Indeed, cross-language priming effects are generally stronger when there is lexical overlap and shared word order across languages ( Kootstra et al., 2010 ), which is congenial to the idea that linguistic representations vary in their degree of activation in bilingual speech production ( Green, 2018 ). In an analysis of the Bangor Miami Corpus ( Deuchar et al., 2014 ), Fricke and Kootstra (2016) found that priming influenced not only the tendency to codeswitch, but the type of codeswitch as well. Importantly, they observed that other-language words, irrespective of whether they share the same word form, influenced the likelihood of codeswitching.

The Fricke and Kootstra (2016) results illustrate how bottom-up processes influence codeswitching behavior. That said, the scope of these effects in explaining codeswitching behavior is likely limited for a variety of reasons. It should be noted that cross-language priming is weaker in strength and shorter-lived than within-language priming ( Schoonbaert et al., 2007 ; Travis et al., 2017 ). In a study of coreferential subject priming, Torres Cacoullos and Travis (2018) reported that within-language priming was nearly four times stronger than cross-language priming. This result is also consistent with the observation of Myslín and Levy (2015) that words are generally more likely to reoccur in the language of most recent mention. Second, it has been established that speakers’ tendency to codeswitch is primed more by their own speech (i.e., within-speaker priming) than by the speech of others (i.e., between-speaker priming, also referred to comprehension-to-production priming), indicating that priming decreases as a function of the referential distance 2 between the prime and the target ( Fricke and Kootstra, 2016 ; see also Gries, 2005 ). Lastly, while spontaneous codeswitching is often deemed characteristic of bilingual discourse, the vast majority of utterances bilinguals produce are unilingual. For example, in the Bangor Miami Corpus, Fricke, and Kootstra reported that of the 42,291 utterances bilinguals produced, the bulk of them (94.2%) were in a single language (see also Beatty-Martínez and Dussias, 2019 for the proportion of unilingual and codeswitched NPs across four bilingual corpora). These factors taken together provide strong evidence that even habitual codeswitchers produce utterances in one language despite high levels of cross-language activation. Thus, bottom-up processes alone, no matter how robust, are not sufficient to account for codeswitching behavior in its entirety. Below, we consider how the speaker’s intentions may exert top-down control over codeswitching practices to achieve communicative goals.

Codeswitching as a Repair Strategy

The ease of producing speech with little conscious effort and few errors belies the complexity of its underlying cognitive processes. Speech disfluencies (e.g., pauses, false starts, and/or hesitations) are direct evidence of production difficulty ( Arnold et al., 2000 ); the fact that speakers make errors while planning utterances and sometimes correct them evinces the need for monitoring and control in production ( Nozari and Novick, 2017 ). 3 As a result, speakers may learn implicit strategies to mitigate production difficulty ( MacDonald, 2013 ; Dell and Chang, 2014 ). Here, we consider the idea that increased cognitive demands in language production may promote codeswitching as a deus ex machina of sorts: proficient bilinguals who have extensive codeswitching practice resort to such behavior as a way to mitigate speech planning demands that arise during the normal course of developing a speech plan (e.g., MacDonald, 2013 ). For bilinguals, speech planning is subject to the parallel activation of the two languages ( Kroll et al., 2006 ), creating many opportunities for cross-language interference, and increasing the potential for within-language interference ( Abutalebi and Green, 2007 ). Bilinguals must, therefore, develop language regulatory strategies to help them manage the relative activation of the two languages when planning goal-oriented speech ( Bogulski et al., 2019 ). Such strategies may include actively suppressing one language to enable fluent speech in the other language when the desire (or requirement) is to use one language alone, but they may also include codeswitching when the desire is to use both languages opportunistically ( Green, 2018 ).

One way to examine this issue is by identifying the types of phonetic and prosodic variation that arise in codeswitched speech. In an analysis of the Bangor Miami Corpus of Spanish-English codeswitching ( Deuchar et al., 2014 ), Fricke et al. (2016) found that lexical items involving a spontaneously-produced codeswitch had reduced speech rate and were more disfluent, relative to matched unilingual control lexical items. To a large extent, one can view these acoustic features as proxies for production difficulty, where slower speech rate and decreased fluency are associated with reduced automaticity (e.g., Segalowitz, 2010 ). Fricke et al.’s analysis of voice onset time (VOT) further revealed that low-level phonetic modulations often occur in anticipation of a codeswitch: English voiceless stops/ptk/were produced with more Spanish-like VOTs the closer they were to Spanish words, suggesting that these processing costs may more adequately reflect changes in the relative activation of the two languages (see also Balukas and Koops, 2015 , for a similar result with codeswitching bilinguals from New Mexico). It is possible that these phonetic changes arise due to the unintended activation of the non-target language, forcing the speaker to switch languages to maintain fluidity in the conversation. Conversely, speakers may have a strong desire to switch languages, and the anticipation of the switch leads to a momentary reorganization of the language system.

To dissociate these two explanations, we turn to a recent study by Johns and Steuck (2018) on the prosodic structure of codeswitched speech in the New Mexico Spanish-English Bilingual (NMSEB) corpus ( Torres Cacoullos and Travis, 2018 ). They observed that codeswitching was more likely to occur toward the end of a prosodic sentence, suggesting that harder-to-produce elements, i.e., those that tend to be produced later in utterances ( MacDonald, 2013 ), will often co-occur with codeswitched speech. Critically, however, they also observed faster speech rates within codeswitched prosodic sentences, relative to unilingual control utterances. This latter finding is important because it suggests that codeswitching is not a source of production costs per se . On the contrary, it may help bilingual speakers circumvent difficulties that are inherent to speech planning more generally, hence why it is more likely to occur toward the end of a planned utterance.

It is important to reiterate that, whereas Johns and Steuck (2018) focused on the speech rate within a prosodic sentence, Fricke et al. (2016) focused on the speech rate of words preceding codeswitches. This contrast reveals how codeswitching may come to affect bilingual speech at different levels of planning and raises the question of how to interpret the production costs observed in Fricke et al.’s study. We believe they reflect a momentary reorganization of the prosodic and phonetic systems, and that this reorganization is driven by a deliberate intent to switch languages. From this perspective, codeswitching serves two important functions in production. First, it enables speakers to negotiate lexical competition in a way that minimizes the impact of within-language and cross-language lexical interference. These prosodic and phonetic changes observed within single lexical items may in turn facilitate planning at higher levels, with the goal of maximizing fluency at the discourse level (see Hopp, 2015 , 2016 , for a similar account on how lexical processing impacts sentence comprehension in bilinguals). Second, the fact that codeswitching leads to systematic variation in speech means that listeners can reliably exploit these cues to facilitate comprehension ( Fricke et al., 2016 ; Guzzardo Tamargo et al., 2016 ; Valdés Kroff et al., 2017 ; Beatty-Martínez, 2019 ; Shen et al., 2020 ).

Codeswitching and the Problem of Variable Equivalence

If codeswitching enables bilinguals to successfully navigate linguistic interference in production, what are the strategies that reliably promote a codeswitch? One possibility is that bilinguals rely on cross-linguistic convergence to ensure that a codeswitch is successfully deployed. Research on codeswitching constraints (e.g., the equivalence constraint; Poplack, 1980 ) and cross-linguistic priming (see section “The contributions of bottom-up factors in codeswitching”) provide some basis for this idea but are insufficient to explain the overall pattern of data available to date. Interestingly, such an account predicts that bilinguals will consistently avoid “conflict sites” ( Poplack and Meechan, 1998 , p. 132) across the two languages when attempting to switch. But since we have argued that codeswitching is a tool to negotiate speech planning difficulties, we would expect opportunistic use of the languages at sites of variable equivalence, where the languages partially overlap ( Torres Cacoullos and Poplack, 2016 ). One way to tease this apart is by examining the prosodic structure of unilingual and codeswitched speech.

Recent evidence suggests that bilinguals strategically employ prosodic distancing at codeswitch junctures where the two languages sometimes differ due to independent, but inherently variable, processes to execute a codeswitch ( Torres Cacoullos and Travis, 2018 ). Like Johns and Steuck (2018) , this area of research examines prosodically-transcribed spontaneous bilingual data where the speech stream is segmented not into boundaries of major syntactic constituents but rather in stretches of speech uttered under a single intonation contour (e.g., intonation units; henceforth, IUs; Du Bois et al., 1993 ). Prosodic boundaries are perceptually delimited by a set of acoustic features (e.g., a pause, an initial rise in overall pitch level, and final phrase lengthening), and have been presented as evidence that speakers plan their speech in relatively large chunks, corresponding to IUs ( Krivokapić, 2012 ; Bishop and Kim, 2018 ). Given that it has been argued that speakers plan speech at prosodic boundaries ( Krivokapić, 2014 ), it is likely that linguistic material in the same prosodic unit is planned differently than those occurring in different units.

We illustrate this argument with recent developments in the prosodic positioning of complement clauses. Whereas main clauses typically co-occur in different IUs, main and complement clauses, which share a tighter syntactic relationship, tend to co-occur in the same IU ( Du Bois, 1987 ; Croft, 1995 ; Steuck, 2016 ). Steuck and Torres Cacoullos (2019) observed the same pattern in the speech of Spanish-English bilingual speakers when speaking in either of their two languages. Interestingly, main and complement clauses appeared to be prosodically less integrated when bilinguals codeswitched at the clause boundary, a result that could be interpreted as evidence for prosodic distancing (see example 1a below). However, Steuck and Torres Cacoullos also reported that when codeswitching occurred elsewhere (i.e., within the main or complement clause, see example 1b), the rate of prosodic integration of the two clauses was no different than unilingual IUs. Thus, prosodic distancing is not an inherent consequence of codeswitching, but rather serves as a strategy for negotiating cross-linguistic differences between the two languages: the complementizer “that” is present variably in English, while the complementizer “que” is present always in Spanish ( Torres Cacoullos and Travis, 2018 ).

Perhaps most telling is that bilinguals overwhelmingly prefer to codeswitch at prosodic boundaries rather than within IUs despite cross-linguistic differences ( Shenk, 2006 ; Durán-Urrea, 2012 ; Myslín and Levy, 2015 ). For example, Steuck and Torres Cacoullos (2019) reported that 60% of codeswitches involving main and complement clauses were at the boundary between the two clauses. Plaistowe (2015) extends this pattern more broadly too: in the NMSEB corpus ( Torres Cacoullos and Travis, 2018 ), speakers switched at IU boundaries 93% of the time. Why might this be? We consider the following possibility: the tendency of codeswitching at IU boundaries may reflect the outcome of a competitive process between active items of both languages and where codeswitching is best understood as an opportunistic response of the most active and most easily retrieved items ( Green and Wei, 2014 ). We infer that the pattern will depend, first and foremost, on how speakers manage the relative activation of their languages, as shaped by their habits of language use and the control demands of their interactional context ( Green and Abutalebi, 2013 ; Green and Wei, 2014 ; Beatty-Martínez et al., 2019 ). For example, bilinguals in single-language contexts engage language control competitively (i.e., where language membership is maximized and the activation of one language is suppressed at the expense of the other). In turn, bilinguals in codeswitching contexts engage language control cooperatively (i.e., where language membership is minimized and coactivation is maintained all the way through speech planning so that items from both languages make themselves available for selection).

Codeswitching as an Opportunistic Strategy

Recently, Green and Abutalebi (2013) and Green and Wei (2014) proposed that bilinguals in a dense-codeswitching context make use of processes related to opportunistic planning (e.g., Hayes-Roth and Hayes-Roth, 1979 ; Patalano and Seifert, 1997 ), spontaneously taking advantage of unforeseen opportunities to achieve their communicative goals. Despite growing interest in this idea, there is little empirical research directly examining how bilinguals make use of such a strategy in spontaneous discourse. Below we provide evidence for opportunistic planning by examining the production preferences in the modification of complex NPs of Spanish-English bilinguals living in San Juan, Puerto Rico. Before describing the distributions themselves, we provide a brief overview of the interactional context, participants, and data collection methodology. While Spanish remains the predominant language of Puerto Rico, the use of English is loosely supported in many contexts of everyday life (e.g., in education, media, and other societal domains). Importantly, codeswitching is very common among bilinguals, especially those of the younger generations ( Casas, 2016 ; Pousada, 2017 ; Beatty-Martínez, 2019 ; Guzzardo Tamargo et al., 2019 ). Thus, it follows that bilinguals in this context may be able to use whichever words and structures that are most active to achieve their communicative goals with little-to-no interactional cost ( Green and Abutalebi, 2013 ; Beatty-Martínez et al., 2019 ). In other words, “their skill lies less in avoiding language conflict than in utilizing the joint activation of both languages and adapting their utterances appropriately” ( Green, 2011 ; p. 2). Codeswitching in this context therefore represents a device for taking advantage of the more efficient of the two languages ( Gibson et al., 2019 ) and through which the cost in time and resources can be minimized.

The data under study here were obtained from the Puerto Rico subset of the Codeswitching Map Task (PR-CMT) corpus ( Beatty-Martínez et al., 2018 ; Beatty-Martínez and Dussias, 2019 ; Królikowska et al., 2019 ), a corpus of unscripted, task-oriented dialogs designed to assess codeswitching behaviors in bilingual speakers. The corpus consists of approximately 2.5 h of recordings with 10 Spanish-English bilinguals (6 female). All participants were native Spanish speakers who had acquired Spanish at birth and English either simultaneously or in early childhood. Participants assessed their own proficiency to be equally high in both languages (see Table 1 for a summary of participant characteristics).

Table 1. Participant self-reported characteristics.

Participants also answered questions about overall language exposure to Spanish and English and their frequency of use in various contexts in daily life. As depicted in Figure 1 , participants reported more exposure to Spanish when interacting with family, more exposure to English in the media, but being exposed to both languages equally among friends. Descriptively, these data exemplify how participants’ interactional context supports the use of both languages.

Figure 1. Participants’ self-reported exposure to Spanish and English across different social domains. Ratings were made on a 10-point scale ranging from 0 (no exposure) to 10 (high exposure). Error bars indicate standard error of the mean.

In the map task, director-matcher pairs took turns describing visual scenes (i.e., maps) to one another within a designated time limit. Participants played the role of the director, sitting at a table opposite a confederate matcher who was both a close friend and an in-group member from the same speech community (i.e., San Juan, Puerto Rico). This is important, as previous research has shown that speakers may produce four times as many codeswitches in informal contexts when they are paired with an in-group interlocutor ( Poplack, 1983 ). Furthermore, unlike other guided production tasks where the data distribution is typically controlled and participants are either forced to switch languages or familiarized with object names before the interaction takes place, dialogs were completely unscripted and conversational partners were free to use whichever language they wanted. This sacrifice in experimental control is compensated by the opportunity to offer insights of non-standard language use within the speech community ( Sankoff, 1988 ; Torres Cacoullos and Travis, 2018 ).

Director and matcher maps differed only in terms of the way the objects were arranged on a computer screen. Visual scenes contained background objects that were fixed; moveable objects were placed in reference to fixed objects, exerting the need to describe them in terms of their spatial arrangement (see Figure 2 for an example). Visual maps required to replicate the experiment are included as Supplementary Material Files . All objects were presented in color to elicit more detailed descriptions. Additionally, some objects appeared more than once in the same slide, but with different qualities (e.g., a series of faces differing in their facial expressions; see Gullberg et al., 2009 ; Pivneva et al., 2012 ; Valdés Kroff and Fernández-Duque, 2017 , for similar procedures) as evidenced in excerpt (2) below:

Figure 2. A visual panel from the Codeswitching Map Task.

Our quantitative analysis abides by the principle of accountability ( Labov, 1972 ), comparing the rate of codeswitching across different types of constructions by contextualizing them with respect to the contexts where they could have occurred but did not (i.e., by circumscribing the variable context; Labov, 2005 ). This approach has been widely employed in corpus analyses of codeswitched speech by extracting not only codeswitched tokens across the different types of constructions, but also their unilingual counterparts in Spanish and English ( Poplack, 1980 , 2017 ; Torres Cacoullos and Travis, 2018 ; Steuck and Torres Cacoullos, 2019 ). Table 3 summarizes the distribution of unilingual and mixed NPs extracted from the corpus. We begin by examining the distribution of simple NPs –composed only of a determiner and a noun– across unilingual and mixed phrases. As shown in Table 2 , the vast majority of NPs in the corpus were unilingual (Unilingual, Mixed: χ 2 = 321.14, df = 1, and p < 0.001), with roughly half of them produced in Spanish and about a third in English. This finding is congenial to past studies showing that codeswitched utterances constitute a small proportion of corpus data, even in communities where codeswitching is a regular communicative practice ( Beatty-Martínez and Dussias, 2017 , 2019 ; Green, 2019 ). For simple mixed NPs, all but three tokens (“la balloon,” “la guitar,” “the rueda”; English ballon, guitar, and wheel, respectively) were comprised of a Spanish masculine determiner and an English noun, replicating the well-documented asymmetry with respect to grammatical gender and switching direction ( Poplack, 1980 ; Valdés Kroff, 2016 ; Beatty-Martínez et al., 2018 ; Casielles-Suárez, 2018 ; cf. Blokzijl et al., 2017 ).

Table 2. Number and proportion of noun phrase utterances across languages in the PR-CMT corpus.

Table 3. Number and proportion of complex Adj + N/N + Adj constructions across languages in the PR-CMT corpus.

Next, we examine bilinguals’ structural and language choices in the modification of complex NPs (e.g., the black dog) –a site of variable equivalence between English and Spanish–relative to the mixed Determiner + Noun baseline shown in Table 3 . Critically, examining the distributional patterns of complex mixed NPs will allow us to explore whether there are opportunistic behaviors in how codeswitching bilinguals manage to negotiate their two languages.

In English, adjectives typically precede the noun (Adj + N; e.g., the Det yellow Mod house N ). In Spanish, most adjectives are typically placed post-nominally (N + Adj; e.g., la Det casa N amarilla Mod ) although there is a small group of modifiers that occurs prenominally (e.g., quantitative modifiers such as ordinals and cardinals; e.g., la Det primera Mod casa N , “the first house”). A further cross-linguistic difference is that English makes use of compounding freely and productively (i.e., N + N constructions such as “the diamond ring”) whereas compounding in Spanish is much more limited, preferring left-headed noun-prepositional-phrase (N + PP) constructions (e.g., “el anillo de diamante” ; Liceras et al., 2002 ; Varela, 2012 ). Lastly, Spanish differs from English in that Spanish agreement rules require that other grammatical elements (e.g., determiners, adjectives, etc.) match the gender of the noun they modify. Against this background, one possibility is that complex mixed NPs should be generally avoided in contexts that require overt gender marking (e.g., Otheguy and Lapidus, 2003 ; Balam and Parafita Couto, 2019 ) or “strictly limited” ( Pfaff, 1979 , p. 306) due to cross-linguistic differences in word order (for Adj + N and N + Adj constructions) and lexicalization preferences (for N + N and N + PP constructions). If this were the case, we would expect to find a decrease in the proportion of codeswitching in complex NPs relative to the proportion of codeswitching in simple NPs. However, in our data, the opposite is true. 4

While all-Spanish utterances predominate when bilinguals produce simple (Det + N) NPs (Spanish, English: χ 2 = 40.034, df = 1, and p < 0.001; Spanish, Mixed: χ 2 = 113.39, df = 1, and p < 0.001), they are not preferred when modifiers (i.e., adjectives) are used (Spanish, English: χ 2 = 22.469, df = 1, and p = 1.00; Spanish, Mixed: χ 2 = 3.504, df = 1, and p = 0.969), as shown in Table 3 . This shift in language choice cannot be due to differences in proficiency or exposure, since Spanish is the native and predominant language of this community of speakers.

One potential explanation, following Myslín and Levy (2015) , is that the use of English (participants’ less frequent and therefore more salient language) offers a distinct encoding that signals novel information. Such an account would predict an increase in the use of English within complex mixed NPs across all types of modifiers, regardless of the type of modifier and of the type of construction. An alternative hypothesis, and one that we endorse here, is that speakers will adopt strategies from both languages that are advantageous within a given communicative context. In this case, we would expect speakers to prefer the use of prenominal modification strategies (i.e., Adj+N or N+N constructions), which are overwhelmingly preferred in English but can also appear in Spanish with some types of modifiers (e.g., quantitative modifiers). Such a strategy would help disambiguate between competing sources of information in the map task. For example, when referring to duplicate objects such as the gloves displayed in Figure 2 , participants could describe the target glove as having a specific color (e.g., “The brown/gray glove” in English or “El guante marrón/gris ” in Spanish) or as being made of a specific material (e.g., “The leather/cotton glove” in English or “El guante de cuero/algodón ” in Spanish). While it is difficult to determine at which point disambiguation is achieved when using English (i.e., listeners could initially consider other brown/gray items such as the brown purse displayed in the figure), what can be said with more certainty is that for Spanish utterances, disambiguation between the target and non-target gloves cannot be achieved until after the noun is spoken (e.g., el guante marrón/de cuero ). Therefore, bilinguals’ language and structural choices should favor prenominalization in duplicate contexts to facilitate referent identification ( Fukumura, 2018 ), and thus, optimize task performance.

Indeed, a comparison of the proportion of complex mixed NPs in duplicate against singleton items confirmed that the proportion of codeswitches was greater for duplicate items (Duplicate, Singleton: χ 2 = 4.588, df = 1, and p = 0.016). Moreover, as the data in Table 4 show, complex mixed NP constructions were overwhelmingly made up of an English prenominal modifier followed by an English noun (e.g., el red car; Prenominal, Post-nominal: χ 2 = 50.330, df = 1, and p < 0.001; English, Spanish: χ 2 = 47.573, df = 1, and p < 0.001), suggesting that the use of prenominalization increased across the board. That said, we note that not all complex mixed NPs were opportunistic, as there was a smaller subset of tokens containing Spanish modifiers after the noun (e.g., el car rojo). Importantly, however, the pattern of results reported here is consistent with the distributions reported for Spanish-English bilinguals in Miami ( Parafita Couto and Gullberg, 2019 ) 5 and Northern Belize ( Balam and Parafita Couto, 2019 ).

Table 4. Distribution of complex mixed NP modifiers across languages and word order in the PR-CMT corpus.

As we mentioned earlier, quantitative modifiers ( N = 32) occur prenominally in Spanish, and as such, these were examined separately. At this point one could speculate that bilinguals simply prefer to produce complex mixed NPs with English modifiers. However, if prenominalization, rather than the use of English per se , is key to bilinguals’ structural and language choices, we should then expect a relative increase in the proportion of Spanish modifiers in complex mixed NPs with quantitative modifiers. And, indeed, this is what we observe in Table 5 (Quantitative, Non-Quantitative: χ 2 = 46.178, df = 1, and p < 0.001). Moreover, Spanish modifiers were more prevalent relative to English modifiers in this context (Spanish, English: χ 2 = 11.281, df = 1, and p < 0.001), demonstrating that bilinguals will capitalize on the dominant language when it converges with the optimal strategy (i.e., prenominalization).

Table 5. Distribution of Spanish and English quantitative modifiers in complex mixed NPs in the PR-CMT corpus.

The second pattern of results concerns bilinguals’ structural and language choices in N + N and N + PP constructions. Recall that N + N compounds are highly productive in English but dispreferred in Spanish; the opposite is true for N + PP constructions. Notwithstanding, when bilinguals codeswitch, they are able to opportunistically make use of both Spanish and English strategies. Following the same logic as described above, one possibility is that bilinguals will show a preference for English lexicalization strategies, given that the use of the N + N construction allows the speaker to focus on what is perhaps more important or conceptually salient earlier in the utterance ( MacDonald, 2013 ; Fukumura, 2018 ). Because Spanish is the dominant language, we can interpret the switch from Spanish into English in mixed N + N constructions as reflecting an opportunistic response, suggesting that the English strategy was most active and most easily retrieved. As Table 6 shows, bilinguals are actively making use of the N + N construction. In all codeswitched tokens, both the head noun and the modifier were produced in English and were preceded by a Spanish masculine determiner. Remarkably, the rate of mixed N + N constructions is nearly identical to that of unilingual English utterances (English, Mixed: χ 2 = 0.115, df = 1, and p = 0.367) and is higher than the codeswitching rate reported previously (N + N, Adj + N: χ 2 = 6.662, df = 1, and p = 0.005). We speculate that this increase may be related to chunking, the process by which frequently co-occurring sequences of words are grouped together in cognitive representation ( Bybee, 2013 ; Christiansen and Chater, 2016 ). Because chunking is a gradient phenomenon, Adj + N and N + N constructions (e.g., such as “blue shoe” and “tennis shoe”, respectively) can be conceptualized as falling on a continuum, where instances with stronger collocational associations are more likely to be accessed as a single unit rather than compositionally ( Bybee, 2010 ).

Table 6. Number and proportion of N + N constructions across languages in the PR-CMT corpus.

Consistent with the prediction that bilinguals would capitalize on language structures with prenominal modification, N + N constructions are produced at a much higher rate in the corpus relative to N + PP constructions (N + N, N + PP: χ 2 = 37.895, df = 1, and p < 0.001). As shown in Table 7 , the majority of N + PP constructions were produced in Spanish (Spanish, Mixed: χ 2 = 3.062, df = 1, and p = 0.040). This can be taken as further evidence for how bilinguals are able to accommodate their production choices to optimize task performance. Notwithstanding, we do not take this finding to indicate that bilinguals disregard the use of Spanish-preferred constructions when codeswitching. The few codeswitches that did occur in the corpus are indicative that bilinguals do consider and make use of alternative forms of expression that would be competing in monolingual contexts. We believe that, in this particular communicative context, N + PP constructions serve as a “just-in-time” or deus ex machina resource to circumvent potential pitfalls of the speech plan. An important implication is that bilinguals can use (or switch into) one language while the other language stands at the ready as future challenges and opportunities emerge.

Table 7. Number and proportion of N + PP constructions across languages in the PR-CMT corpus.

Altogether, these data provide initial empirical support for opportunistic planning during codeswitching. Contrary to the prediction that bilinguals would avoid switching in contexts of variable equivalence due to differences in word order and lexicalization preferences, we observed increased rates of codeswitching despite any potential costs, consistent with Steuck and Torres Cacoullos (2019) . This finding also speaks to bilinguals’ intention to codeswitch as a means to achieve their communicative goals. Specifically, we observed that codeswitching bilinguals capitalize on what is most optimal for the current situation (i.e., prenominal modification) by switching languages when circumstances call for such a change. Codeswitching thus may serve as an opportunistic strategy to make use of whatever comes most readily available, all the while conforming to the goals of the speaker.

Closing Remarks

The studies reviewed here, together with the data we examined, provide critical evidence for the way in which the language system is controlled. In line with contemporary theoretical models of bilingual speech production and language control ( Green, 2011 , 2018 , 2019 ; Green and Abutalebi, 2013 ; Green and Wei, 2014 ), these data support the notion of a cooperative control state, where both languages may openly contribute to production. This stands in contrast with other forms of language use in which language control is engaged competitively and where the “gate” for non-target language items is locked ( Green and Wei, 2014 , p. 502). Although, research on bilingual language production has shown that bilinguals demonstrate difficulties in language fluency, due perhaps to reduced functional use of the languages (e.g., Gollan et al., 2008 ), increased cross-language competition (e.g., Sullivan et al., 2018 ), or limited proficiency ( Bialystok et al., 2008 ), our data suggest that codeswitching might aid language fluency by allowing both languages to remain active and accessible, and therefore providing an alternative means to convey meaning. It remains to be determined what the role of cognitive control is in spontaneous codeswitched speech relative to unilingual speech ( Nozari and Novick, 2017 ). For now, we note that while such flexibility may not be impervious to production costs that arise during normal speech production (e.g., Green, 2019 ), having the option to either explore or restrict language control states throughout the planning process may potentially alleviate many cognitive demands. In this way, this finding provides support for the more general notion that speakers adopt implicit strategies to mitigate production difficulty ( MacDonald, 2013 ). While the precise mechanisms underlying codeswitching are yet to be fully understood, we hope this will be an active area of research in years to come.

Data Availability Statement

All datasets generated for this study are included in the article/ Supplementary Material .

Ethics Statement

The studies involving human participants were reviewed and approved by The Pennsylvania State University Institutional Review Board (Approval Number: 34810). The participants provided their written informed consent to participate in this study.

Author Contributions

All authors equally conceived the theory and hypotheses presented here and wrote the manuscript.

The writing of this manuscript was supported in part by NIH grant F32-AG064810 to AB-M, NSF Grant BCS-1824072 and NIH Grant F31HD098783 to CN-T, and by NSF Grants BCS-15351241 and OISE-1545900 to PD.

Conflict of Interest

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.

Acknowledgments

We are grateful to Rena Torres Cacoullos for helpful comments and discussions during the preparation of this manuscript. We would also like to thank the editor and the reviewers for their insightful comments on earlier versions of the manuscript.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2020.01699/full#supplementary-material

PRESENTATION S1 | Director slides for the Codeswitching Map Task.

PRESENTATION S2 | Matcher slides for the Codeswitching Map Task.

• ^ Although cued language-switching studies provide a direct bridge to the more general phenomenon of task switching and non-verbal cognitive control (e.g., Monsell, 2003 ; Prior and Gollan, 2011 ; Zhang et al., 2015 ), whether the same cognitive and neural processes that underlie cued language switching are also deployed for spontaneously-produced codeswitches is an open question. For present purposes, we treat language switching and codeswitching as qualitatively different phenomena, and thus focus exclusively on codeswitching research.
• ^ Under usage-based approaches, priming effects are typically evaluated in terms of “referential distance” ( Givón, 1983 ; Myhill, 2005 , p. 473), where distance is measured in terms of the number of intervening clauses between the target and the previous mention of the referent as well as the presence or absence of intervening human subjects ( Torres Cacoullos and Travis, 2018 ).
• ^ Recently there have been a number of studies that have examined disfluencies in codeswitched speech while reading aloud (e.g., Gollan and Goldrick, 2016 ; Gollan et al., 2017 ; Halberstadt, 2017 ). However, it is beyond the scope of this article to determine the extent to which the cognitive processes engaged in a reading-aloud paradigm are generalizable to spontaneous speech production (c.f., Guaïtella, 1999 ).
• ^ A reviewer raised the possibility that the absence of English-to-Spanish mixed NPs might affect the predictions regarding bilinguals’ production choices. We hypothesize that where codeswitching norms differ, opportunistic strategies may manifest differently. The codeswitching patterns of Nicaraguan bilinguals are an interesting test case as they seem to differ from other Spanish-English bilingual communities, exhibiting a marked preference for English determiners in simple mixed NPs (e.g., “the perro” instead of “el dog”; Blokzijl et al., 2017 ). Given that prenominal modification is most optimal (in terms of greater discriminatory efficiency), the more opportunistic strategy would be to avoid switching within complex mixed NP structures altogether (preferring unilingual English complex NPs instead). Our hope is that the proposal put forth here will inform and shape future research directions.
• ^ Note that this study also reports a similar pattern for two other language pairs (Welsh-English and Papiamento-Dutch) with the same conflict regarding the relative order of the adjective and the noun.

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Keywords : codeswitching, language production, speech planning, opportunistic planning, language control

Citation: Beatty-Martínez AL, Navarro-Torres CA and Dussias PE (2020) Codeswitching: A Bilingual Toolkit for Opportunistic Speech Planning. Front. Psychol. 11:1699. doi: 10.3389/fpsyg.2020.01699

Received: 05 February 2020; Accepted: 22 June 2020; Published: 17 July 2020.

Reviewed by:

Copyright © 2020 Beatty-Martínez, Navarro-Torres and Dussias. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Anne L. Beatty-Martínez, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Code-Switching in Linguistics: A Position Paper

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Article contents

• Introduction
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Supplementary material

Code-switching as a marker of linguistic competence in bilingual children.

Published online by Cambridge University Press:  04 September 2017

• Supplementary materials

Code-switching is a common phenomenon that bilinguals engage in, including bilingual children. While many researchers have analyzed code-switching behaviors to better understand more about the language processes in bilingual children, few have examined how code-switching behavior affects a child's linguistic competence. This study thus sought to examine the relationship between code-switching and linguistic competency in bilingual children. Fifty-five English–Mandarin bilingual children aged 5 to 6 years were observed during classroom activities over five days (three hours each day). A number of different word roots and mean length of utterance for both languages, and a number of code-switched utterances for each child, were computed. English receptive vocabulary scores were also obtained. Additionally, teachers rated children's English and Mandarin language competencies approximately six months later. Correlational and hierarchical regression analyses support the argument that code-switching does not indicate linguistic incompetence. Instead, bilingual children's code-switching strongly suggests that it is a marker of linguistic competence.

1. Introduction

Code-switching is a common phenomenon that bilingual speakers regularly engage in. When bilinguals code-switch, words from two languages are used within a single discourse. In some studies, code-switching has been distinguished from code-mixing – code-mixing is defined as a practice of mixing languages in a single sentence while code-switching can occur either within or across sentence boundaries within a single discourse or constituent (e.g., Brice & Anderson, Reference Brice and Anderson 1999 ; Meisel, Reference Meisel 1989 ; Muysken, Reference Muysken 2000 ; Nicoladis & Genesee, Reference Nicoladis and Genesee 1997 ). In other studies, as well as the present study, code-switching and code-mixing are synonymously regarded as an alternation of two languages within the same speech act (Bokamba, Reference Bokamba 1989 ; Clyne, Reference Clyne 1987 ; Genesee, Reference Genesee 1989 ; Genesee, Paradis & Crago, Reference Genesee, Paradis and Crago 2004 ; Poplack, Reference Poplack, Smelser and Baltes 2001 ).

Code-switching has been well studied in bilingual adults, particularly with regard to the grammatical and communicative functions of the behavior (e.g., Cantone, Reference Cantone 2007 ; Gumperz, Reference Gumperz and Dil 1971 ; MacSwan, Reference MacSwan 2014 ; MacSwan & McAlister, Reference MacSwan and McAlister 2010 ; McClure, Reference McClure 1977 ; Poplack, Reference Poplack 1980 ). The complexity of bilingual adults’ code-switching generally reveals a sophisticated knowledge of the grammars of both languages and reflects the adults’ competency in using them appropriately. However, there has been much debate with respect to what children's code-switching behavior suggests about their linguistic competency.

Early studies on children's language alternation behaviors postulated that bilingual children mix or switch languages because 1) they are confused or 2) they are linguistically incompetent. According to proponents of the position that bilingual children mix languages because they are confused and cannot differentiate between the two languages (e.g., the Unitary Language System Hypothesis in young children aged 3 years and below; Genesee, Reference Genesee 1989 ), the lexicons and grammars of both languages in young bilingual children first exist in one single system, and only gradually develop into two separate linguistic systems by a process of language differentiation. In this framework, young bilingual children's mixing of two different language elements within the same utterance was seen as evidence of the pre-separation stage and, thus, was argued to be a reflection of their inability to differentiate two language systems (Köppe & Meisel, Reference Köppe and Meisel 1995 ; Redlinger & Park, Reference Redlinger and Park 1980 ; Volterra & Taeschner, Reference Volterra and Taeschner 1978 ). For example, Redlinger and Park ( Reference Redlinger and Park 1980 ) studied four 2-year-old bilingual children over five to nine months and suggested that the children experienced various stages of language differentiation. The children would start off with high rates of language mixing as they do not separate their two language systems. The high language mixing rates would then gradually decline as these children move from an undifferentiated single language system to two distinct language systems. Proponents of this position argued that the decrease in the language-mixing rate is, therefore, positively related to language development, at least for children aged 3 years and below.

Other researchers claimed that bilingual children code-switch not because they cannot differentiate the two language systems, but because they lack the lexical, grammatical and/or pragmatic competence in one or both of the languages known. Several studies have found that bilingual children aged between 2 to 6 years code-switch in order to fill in their lexical gaps – they tend to insert words from one language into another language when they do not have the translation equivalents (e.g., Deuchar & Quay, Reference Deuchar and Quay 2000 ; Cantone, Reference Cantone 2007 ; Lindholm & Padilla, Reference Lindholm and Padilla 1978 ; see Nicoladis & Genesee, Reference Nicoladis and Genesee 1997 , for a review). Further, Bernardini and Schlyter ( Reference Bernardini and Schlyter 2004 ), who examined code-mixing patterns of five Swedish–French/Italian children aged 2 to 4 years, posited that children code-switch because they are not yet competent in structuring grammatical sentences in their “weaker” language. In addition, Vihman ( Reference Vihman 1985 ) suggested that a young bilingual child aged 3 years old or younger would not be focused on the situational context when developing a dual lexicon. As such, the child may code-switch inappropriately during this period, reflecting the absence of pragmatic competence.

Recent studies, however, have provided more complex and contradictory evidence. First, many studies have failed to confirm the Unitary Language System Hypothesis . Results suggest that young bilingual children are able to differentiate their two language systems from an early age and their code-switched utterances are systematic and conform to the grammatical constraints of each known language (e.g., MacSwan, Reference MacSwan 1999 ; Meisel, Reference Meisel 1994 ; Nicoladis & Genesee, Reference Nicoladis and Genesee 1997 ; Paradis, Nicoladis & Genesee, Reference Paradis, Nicoladis and Genesee 2000 ; van Gelderen & MacSwan, Reference van Gelderen and MacSwan 2008 ). Genesee ( Reference Genesee 1989 ) argued that, contrary to the Unitary Language System Hypothesis , young bilingual children are able to use their developing language systems differentially in contextually sensitive ways. Second, case studies have found that children's code-switching behavior illustrates a good understanding of the grammatical systems of both languages. For example, 2- to 4-year-old French–English bilingual children displayed code-switching patterns that were largely similar to that of their adult counterparts – grammatical constraints were adhered to in mixing patterns that involved sentential negation and pronominal subjects (Paradis et al., Reference Paradis, Nicoladis and Genesee 2000 ). Siri's data in Lanza ( Reference Lanza 1992 ) indicated that the two-year-old did not use the inflections of both languages interchangeably. English grammatical morphemes were only used with English lexical morphemes, such as “look s ”, but Norwegian grammatical morphemes were used with both Norwegian and English words, such as “look er ” and “ husk er ”. Results from Cantone ( Reference Cantone 2007 ) also revealed how all instances of Italian–German code-switching in 2- to 5-year-old children in her corpus were grammatical. Furthermore, an English–Spanish bilingual child, M, exhibited language-specific syntax and morphology in both her pure and mixed utterances before the age of 3 years (Deuchar & Quay, Reference Deuchar and Quay 1998 ). Therefore, the results of studies such as the aforementioned suggest that bilingual children's code-switching behavior does not indicate an inability to differentiate their two language systems or a lack of linguistic competency. Instead, they strongly suggest that children's code-switching behavior illustrates that they possess adequate grammatical knowledge of both languages.

Additionally, numerous studies have demonstrated that bilingual children are pragmatically competent and can code-switch according to the situation and interlocutor (e.g., Genesee, Boivin & Nicoladis, Reference Genesee, Boivin and Nicoladis 1996 ). Even though bilingual children below the age of 4 years have more single-noun insertions in their mixed utterances, these utterances reflect their awareness of social norms (De Houwer, Reference De Houwer, Kroll and de Groot 2005 ). For example, Siri code-switched in bilingual contexts but not in monolingual contexts, thereby reflecting her sensitivity to the social demands of the conversation (Lanza, Reference Lanza 1992 ). Two-year-old bilingual children were also able to adjust their rates of code-switching according to that of their interlocutors (Comeau, Genesee & Lapaquette, Reference Comeau, Genesee and Lapaquette 2003 ), suggesting that they are sensitive to the language choices of their interlocutors. Bilingual children's code-switched utterances were also found to be in accordance with the language socialization practices in their families. Chung ( Reference Chung 2006 ) found that a 4.5-year-old and an 11-year-old Korean-American (who were regularly exposed to both Korean and English before age 3) switched between the two languages when conversing with their family members who had different language preferences. This facilitated communication and comprehension between the family members despite these different preferences. Moreover, Vu, Bailey and Howes ( Reference Vu, Bailey and Howes 2010 ) found that 4.5- to 5.5-year-old Spanish–English bilingual children code-switched in their attempts to draw the interviewer's attention or to change speaking roles. These studies show that bilingual children have the pragmatic competence to adjust their code-switching behavior appropriately depending on the situational contexts.

Some researchers have attempted to examine the code-switching-linguistic-competency relationship through investigating whether code-switching in elicited narratives can be a marker of language impairment (LI). Iluz-Cohen and Walters ( Reference Iluz-Cohen and Walters 2012 ) found that 5- and 6-year-old Hebrew–English bilingual children with LI code-switched more than bilingual children with typical language development (TLD). Using the Bilingual English–Spanish Oral Screener (BESOS), Greene, Peña, and Badore ( Reference Greene, Peña and Bedore 2012 ) found that 5-year-old children's risk status for language impairment affected their code-mixing frequency. With the English screener, children who were identified as at-risk of LI code-switched more than the no-risk group. Interestingly, the no-risk group code-switched more on the Spanish screener than the at-risk group. The authors cited limited awareness of the social interaction and challenges in suppressing the irrelevant language as possible explanations for these findings. Contrary to these findings, Gutiérrez-Clellen, Simon-Cereijido and Erickson Leone ( Reference Gutiérrez-Clellen, Simon-Cereijido and Erickson Leone 2009 ) did not find any differences in the use of code-switching between 5- to 6-year-old bilingual children with LI and those with TLD. Clearly, the inconsistent findings across studies call for more research to be conducted in these areas.

Thus, despite earlier attempts to understand the nature of bilingual children's code-switching, the relationship between children's code-switching and linguistic competency remains not well understood, or at best, controversial (Baetens Beardsmore, Reference Baetens Beardsmore, Gopinathan, Kam, Pakir and Saravanan 1998 ; Kamwangamalu & Leng, Reference Kamwangamalu and Lee 1991 ; Ong & Zhang, Reference Ong and Zhang 2010 ). Furthermore, no study has investigated children's code-switching behavior in bilingual preschool settings, especially for children who spend a significant amount of their awake time at these centers, and at a time when their language skills are becoming more complex. Most research on children's code-switching behavior consists of case studies of parent-child interactions or is based on children's narrative samples in a laboratory setting. Information on groups of children's code-switching behavior in a larger natural language environment would be relevant and important to understand the effects of code-switching on bilingual children's language development. Many children spend approximately 10 hours a day or more away from home, such as in childcare or daycare centers. Their language development is, thus, largely influenced by their interactions in this larger and more complex environment (Chung, Reference Chung 2006 ; Comeau et al., Reference Comeau, Genesee and Lapaquette 2003 ; Nicoladis & Genesee, Reference Nicoladis and Genesee 1997 ). In short, code-switching in such sociolinguistic contexts has not yet been adequately examined. The present study, therefore, seeks to fill these gaps by investigating the relationship between children's code-switching and linguistic competency in preschool settings and adopting a quantitative approach toward the analysis of children's language behavior. Measures of 55 English–Mandarin children's spontaneous speech were obtained through five 3-hour observation sessions in two childcare centers. Information on the children's receptive vocabulary was also obtained. In addition, teachers’ assessments of the children's language competency in English and Mandarin were collected approximately six months after the observation sessions in order to ascertain whether any predictive relationship exists between code-switching and linguistic competency.

Participants

Fifty-five English–Mandarin bilingual children aged between 5;5 to 6;7 ( M = 6.06, SD = 0.34) from two private childcare centers in Singapore Footnote 1 (33 from Center 1 and 22 from Center 2; 25 females, 30 males) were observed during their classroom activities. Four additional participants were excluded either because they had very low attendance during the observation days that resulted in very little recording time (less than 5% of the total recording time in the center) or because he or she spoke fewer than ten utterances throughout the entire observation session. Both childcare centers conducted classroom activities in English and Mandarin Footnote 2 .

Parents completed a demographic and language background questionnaire prior to the observation session. The questionnaire asked about the age and gender of the child, the language first acquired by the child, and the amount of time (in percentage) their child hears or speaks a language in a typical week (see Yow & Markman, Reference Yow and Markman 2016 ). The average amount of English and Mandarin exposure children had at home as reported by the parents was 55.30% ( SD = 19.93%) and 41.80% ( SD = 20.15%) respectively. All children were reported as simultaneous bilinguals (i.e., acquiring two languages at age 3 or younger), except for one who was reported as a sequential bilingual. Preliminary analysis found that including the single sequential bilingual child did not change the results significantly, thus all children were included in the final analyses. In addition, parents reported their highest education level as a measure of socioeconomic status (SES), ranging from 0 ( no formal education ) to 5 ( postgraduate degree ). The average parental highest education level was 3.98 ( SD = 0.54).

Parents were informed about the study and were requested to complete the language background questionnaires that were distributed with the teacher-parent communication book. The observation was conducted for about three hours each day across five different days in each childcare center. We were thus able to record children's conversations in different settings throughout the week, such as during meal times, craft sessions, and free play. Teachers split children from their respective childcare center into two groups of 2 to 6 as part of their normal preschool routine. Two research assistants each followed and recorded one group of children with a video camera that also had an audio recorder attached to it throughout the recording duration. The research assistants held the camera and audio recorder as close to the children as possible without interrupting their activities. As the audio and video recording were meant to be as naturalistic as possible, there was no form of intervention from the researchers during the entire recording duration. The video recordings were transcribed and crosschecked with the audio recordings, especially when the conversations were unclear from the video recordings. After the observation sessions ended, children were tested individually on their receptive vocabulary using the Peabody Picture Vocabulary Test (4 th Edition; PPVT-IV; Dunn & Dunn, Reference Dunn and Dunn 2007 ). The respective teachers were asked to complete a short questionnaire on the language competency of those children who participated in the study approximately six months after the observation sessions ended (see section on Materials).

Measure of receptive language competency

The Peabody Picture Vocabulary Test (4 th Edition; PPVT-IV; Dunn & Dunn, Reference Dunn and Dunn 2007 ) was administered individually to assess children's receptive English vocabulary. Each child was instructed to point to one of four pictures that depicted the word spoken by the experimenter. Eleven children from Center 1 and five children from Center 2 did not complete the PPVT. Raw scores were converted to age-based standard scores according to the manual. The average standardized score was 100.69 ( SD = 12.33). As there is currently no equivalent approved version in Mandarin, the same task was not conducted in Mandarin.

Teachers’ report of language competency

Teachers were asked to rate the students’ expressive and receptive language competencies from 1 ( very poor ) to 5 ( very good ) approximately six months after the observation session ended. This questionnaire consisted of eight items ( Table A1 ), which we developed based on the Language and Literacy section of the curriculum framework for kindergartens in Singapore (Singapore Ministry of Education, 2012 ). Examples include “he or she talks about drawings and artworks he or she has created” (expressive) and “he or she understands a good variety of words” (receptive). English teachers assessed English language competency while Mandarin teachers assessed Mandarin language competency of the respective children in their charge. The average teacher's rating of English and Mandarin competency was 3.75 ( SD = 0.95) and 3.85 ( SD = 0.79) respectively.

Transcription

Children's utterances during the observation sessions were transcribed in accordance with CHAT and the transcriptions were analyzed using CLAN (MacWhinney, Reference MacWhinney 2000 ). Four additional research assistants, who were also native language speakers of English and Mandarin, were involved in the transcription and checking process. All videos were divided among the six research assistants. The research assistants independently transcribed the videos assigned to them. In accordance with the transcription and reliability checking methods detailed in Lust and Blume ( Reference Lust and Blume 2016 ), a different research assistant (i.e., second transcriber) checked through each transcription for errors or missing data. All transcriptions were checked sentence by sentence by crosschecking the video and audio recordings. When there were discrepancies, the second transcriber would discuss them with the first transcriber before making changes to the transcriptions. A third transcriber was involved if the first two transcribers could not come to an agreement.

In all transcriptions, onomatopoeia (imitation of sounds, e.g., “woof woof”) and ambiguous communicators that can be used in either English or Mandarin, such as “uh”/“哦”, “ah”/“啊”, “oh”/“噢”, Singlish Footnote 3 particles (e.g., “meh”, “la”, “na”, see Rubdy, Reference Rubdy 2007 ) were marked as non-words and thus automatically excluded from all analyses. Words that were not English or Mandarin were also marked as non-words (e.g., “chaota”, a Hokkien word which means burnt). All forms of routinized speech, such as standardized greetings before meal, text or nursery-rhyme reading, and games with standard lyrics (e.g., “scissors paper stone”) were excluded from the analyses as well. The basic unit of our analyses is an utterance, which is defined as “a word or group of words with a single intonation contour” (Lanza, Reference Lanza 1992 , p. 638). A pure utterance (either in English or Mandarin) consists of words only in one language, and excludes single proper nouns, intra-sentential switches, and utterances that contain translations and imitations of other languages.

Expressive language measures: Number of different word roots (NDWR) per minute

Lemma or word roots have often been used as a measure of children's lexical development (Hewitt, Hammer, Yont & Tomblin, Reference Hewitt, Hammer, Yont and Tomblin 2005 ; Thordardottir, Reference Thordardottir 2005 ; Watkins, Kelly, Harbers & Hollis, Reference Watkins, Kelly, Harbers and Hollis 1995 ). We computed this measure separately in English and Mandarin from the transcription data. For English, different words originating from the same word root (e.g., ‘eat-ate-eaten’) were considered as a single word root. NDWR was divided by the recording duration of each individual child because the recording duration varied from child to child (see Aukrust & Rydland, Reference Aukrust and Rydland 2011 ). Proper nouns (e.g., “Tangled”–the title of an English movie, “小兔跳楼” (xiao3tu4tiao4lou2)–the name of a local hand game) and unintelligible words were excluded from the computation of this measure.

Expressive language measures: Mean length of pure utterances (MLU)

Mean length of utterances (MLU) for English and Mandarin were calculated from the transcription data based on the guidelines provided in CHAT and CLAN (MacWhinney, Reference MacWhinney 2000 ). MLU, the ratio of morphemes over utterances (Brown, Reference Brown 1973 ), is frequently used as a measure of sentence complexity (Klee, Stokes, Wong, Fletcher & Gavin, Reference Klee, Stokes, Wong, Fletcher and Gavin 2004 ; Mishina-Mori, Reference Mishina-Mori 2011 ; Thordardottir, Reference Thordardottir 2005 ). Some researchers have noted that MLU is only meaningful until approximately 4 to 5 morphemes (Bernstein & Tiegerman-Farber, Reference Bernstein and Tiegerman-Farber 1997 ), while others have claimed that MLU is a valid measure even into the grade school years (Jones, Weismer & Schumacher, 2000; Miller, Frieberg, Rolland & Reves, Reference Miller, Frieberg, Rolland and Reves 1992 ). As there is currently no consensus on the age limit and morpheme-count limit of MLU (the mean MLUs in our study fall in the range of 4 to 5 morphemes: Mean English MLU = 5.07; Mean Mandarin MLU = 4.26), we proceeded to calculate both English and Mandarin MLU for our study and analyses.

Utterances included in the computation of MLU were those that only consisted of English or Mandarin words (i.e., pure utterances in English and Mandarin). Utterances with unintelligible words were included in the analysis, but the unintelligible words were excluded from the morpheme count. This approach was employed because noise from the environment decreased the intelligibility of many words (see Thordardottir, Reference Thordardottir 2005 ); both childcare centers had open classrooms and thus, voices of children in other groups or classrooms sometimes interfered with the recordings.

Code-switching measures

We coded two types of code-switching from the children's utterances: intra-sentential switches and inter-sentential switches (see Table 1 ). The total amount of code-switched utterances was the sum of both types of code-switching. The percentage of the total number of code-switched utterances made by each child was obtained by dividing the total number of code-switched utterances by the total number of utterances spoken by each child.

Table 1. Types and Examples of Code-switching.

A total duration of 21:16:43 hours and 30:09:48 hours of observation in Center 1 and Center 2, respectively, was transcribed and analyzed. An average of 648.78 utterances per child was recorded ( SD = 542.37; see Table 2 ). The number of observed switches (intra-sentential and inter-sentential switches) in our sample of children constituted a small percentage of their total utterances ( M = 8.95%, SD = 9.60, range = .23% to 33.83%.). There was no child who did not code-switch at all. Of the code-switched utterances, children engaged in similar amounts of intra-sentential switches and inter-sentential switches ( M = 4.46% and 4.48% respectively). Children also produced a greater number of pure English utterances than pure Mandarin utterances and code-switch utterances ( M = 77.01% vs. 16.57% and 8.95%, respectively), and a greater amount of English NDWR per minute and MLU than Mandarin NDWR per minute and MLU ( M = 1.87 and 5.07 vs. .88 and 4.26), reflecting the population's dominance in English language. Preliminary analysis showed that both types of code-switched utterances (i.e., intrasentential and intersentential switches) did not differ in their relationship with the other measures of language competency, hence they were combined as the total number of code-switched utterances in subsequent analyses. Children varied in how much they spoke during the observation period, so the total number of code-switched utterances is divided by the total number of utterances to obtain a percentage of code-switched utterances for each child. In addition, we observed that the teachers themselves did not code-switch when they interacted with the children. The teachers also did not explicitly encourage or discourage code-switching from the children, although they made efforts to speak in only one language to the children.

Table 2. Measures of Children's Spontaneous Speech.

Note: The total number of all utterances is the sum of intra-sentential switch utterances, pure English utterances, pure Mandarin utterances, and other utterances such as single proper nouns, translation, and imitation. Inter-sentential switch utterances comprise only pure utterances.

Correlational analyses

As some of the measures of interest were not normally distributed, Spearman correlations were used. Partial correlations, controlled for age, between the various measures of language competency and percentage of code-switched utterances were conducted ( Table 3 ). No significant correlations between measures of English competency (MLU of pure English utterances, English NDWR per minute, and English PPVT) and percentage of code-switched utterances were found. Thus, the amount of code-switched utterances was not significantly related to both the expressive and receptive measures of English competency. On the other hand, correlations between measures of Mandarin competency (MLU of pure Mandarin utterances, and Mandarin NDWR per minute) and percentage of code-switched utterances were positive and significant, r = .72 and r = .91, respectively, p s < .001, indicating that children who code-switched more also produced Mandarin sentences that are more complex and consist of a larger variety of words than children who code-switched less.

Table 3. Spearman Partial Correlations between Measures of Language Competency and Percentage of Code-Switched Utterances (controlled for age).

*Bonferroni corrected p value = .003

Do children code-switch because of poor language competency?

If children code-switch because they are weak in a language, then their language competency (i.e., NDWR per minute and PPVT) would negatively predict the amount of code-switching (i.e., percentage of code-switched utterances) they engaged in. To test this hypothesis, two multiple hierarchical regressions were conducted, one controlled for age and home English exposure, and the other controlled for age and home Mandarin exposure, since home English exposure and home Mandarin Exposure were highly negatively correlated with each other ( r = −.96, p < .001). The two control variables were entered in Step 1 and the language competency variables were entered in Step 2. We noted that the field has not reached a consensus about the usefulness of MLU in measuring language complexity in children aged 5 to 6 years old. Nevertheless, separate regression analyses were conducted with and without MLU as one of the language predictors and similar results were obtained. Given also that NDWR per minute was highly correlated with MLU ( r s = .55 to .81, p s < .01), we thus presented the regression analyses that included only NDWR per minute as a language predictor of code-switching. The change in R 2 was significant in Step 2 for both regression models (see Table 4a for regression analysis controlled for age and home English exposure, and Table 4b for regression analysis controlled for age and home Mandarin exposure). Both final regression models significantly predicted the percentage of code-switched utterances, F (5, 30) = 11.87, p < .001 (home English exposure), and F (5, 30) = 11.79, p < .001 (home Mandarin exposure), accounting for 66.4% and 66.3% of the variance, respectively. However, only Mandarin NDWR per minute significantly and positively predicted the percentage of code-switched utterances, over and beyond age and home language exposure: β = .79, t (30) = 5.09, p < .001 (home English exposure), and β = .76, t (30) = 5.34, p < .001 (home Mandarin exposure). English NDWR per minute and PPVT were not significant predictors of the percentage of code-switched utterances ( p s > .10).

Table 4a. Summary of Hierarchical Regression Analysis for Language Competency Variables Predicting Percentage of Code-Switched Utterances when Home English Exposure is controlled for.

* p < .05, ** p < .01, *** p < .001

Note: Similar results were obtained if Mandarin MLU and English MLU were included in Step 2: Mandarin NDWR per minute remained significant (β = .50, t (28) = 3.00, p =.006) while English NDWR per minute and PPVT standard scores remained non-significant (β = .17, t (28) = 1.34, p = .19 and β = −.04, t (28) = −.36, p = .72, respectively).

Table 4b. Summary of Hierarchical Regression Analysis for Language Competency Variables Predicting Percentage of Code-Switched Utterances when Home Mandarin Exposure is controlled for.

Note: Similar results were obtained if Mandarin MLU and English MLU were included in Step 2: Mandarin NDWR per minute remained significant (β = .46, t (28) = 2.85, p =.008) while English NDWR per minute and PPVT standard scores remained non-significant (β = −.20, t (28) = 1.30, p = .21 and β = −.02, t (28) = −.17, p = .87, respectively).

Does code-switching affect language competency?

Another important question that the current literature has not yet been able to address is whether code-switching would negatively affect language development in bilingual children. Here, we analyzed teachers’ ratings of the children's English and Mandarin competency approximately six months after the observation sessions. First, Spearman correlation analyses (controlled for age) between measures of language competency, percentage of code-switched utterances, and teachers’ ratings were conducted. Teachers’ ratings of both English and Mandarin competency were positively correlated with the various measures of language competency and code-switched utterances, except English PPVT (see Table 5 and 6 ). Next, separate three-step hierarchical regression analyses were used to examine whether the percentage of code-switched utterances and the other measures of language competency obtained during the observation sessions (i.e., time 1 - T1) predicted teachers’ ratings of language competency 6 months later (i.e., time 2 - T2). Age was entered in Step 1 as a control variable. Percentage of code-switched utterances at T1 was entered in Step 2, to examine whether this variable is significant in predicting teachers’ ratings of language competency at T2 on its own (controlled for age). Finally, language competency variables at T1 (i.e., NDWR per minute and PPVT for English) were added in Step 3 as predictors of teachers’ ratings of language competency at T2. As with earlier regression analyses, we obtained similar results with and without MLU as one of the language predictors, thus we included only NDWR per minute, and not MLU, as one of the predictors of teachers’ ratings of language competency in our final regression analyses.

Table 5. Spearman Partial Correlations between Measures of English Language Competency, Percentage of Code-Switched Utterances and Teachers’ Ratings of English Language Competency (controlled for age).

*Bonferroni corrected p value = .005

Table 6. Spearman Partial Correlations between Measures of Mandarin Language Competency and Percentage of Code-Switched Utterances and Teachers’ Ratings of Mandarin Language Competency (controlled for age).

*Bonferroni corrected p value = .008

For teachers’ ratings of English competency at T2, the change in R 2 was significant when the percentage of code-switched utterances at T1 was added in Step 2 and when English NDWR per minute and PPVT standard scores at T1 were added in Step 3 (see Table 7 ). The final regression model with four predictors at T1 (age, percentage of code-switched utterances, English NDWR per minute, and PPVT) significantly predicted teachers’ ratings of English competency at T2, F (4, 24) = 14.01, p < .001, and accounted for 70.0% of the variance. Both percentage of code-switched utterances and English NDWR per minute at T1 were significant predictors of teacher's ratings of English competency at T2, β = .36, t (24) = 2.81, p = .01, and β = .60, t (24) = 5.15, p < .001, respectively.

Table 7. Summary of Hierarchical Regression Analysis for Language Variables at Time 1 (T1) Predicting Teachers’ Ratings of English Competency at Time 2 (T2).

Note: Similar results were obtained if English MLU was included in Step 3: Percentage of code-switched utterances and English NDWR per minute remained significant (β = .34, t (23) = 2.67, p = .014, and β = .50, t (23) = 3.03, p = .006, respectively), while PPVT standard scores remained non-significant (β = .17, t (23) = 1.34, p = .19).

For teachers’ ratings of Mandarin competency at T2, the change in R 2 was also significant when the percentage of code-switched utterances at T1 was added in Step 2, and when Mandarin NDWR per minute at T1 was added in Step 3 (see Table 8 ). The final regression model with three predictors at T1 (age, percentage of code-switched utterances, and Mandarin NDWR per minute) significantly predicted teachers’ ratings of Mandarin competency at T2, F (3, 46) = 15.68, p < .001, and accounted for 50.6% of the variance. Mandarin NDWR per minute at T1 significantly predicted teachers’ ratings of Mandarin competency at T2, β = .80, t (46) = 4.73, p < .001. While percentage of code-switched utterances at T1 was a significant predictor of teachers’ rating of Mandarin competency at T2 in Step 2, it was no longer significant when Mandarin NDWR per minute was added to the model in Step 3.

Table 8. Summary of Hierarchical Regression Analysis for Language Variables at Time 1 (T1) Predicting Teachers’ Ratings of Mandarin Competency at Time 2 (T2).

* p < .05, ** p < .01, *** p < .001, + p = .051

Note: Similar results were obtained if Mandarin MLU was included in Step 3: Mandarin NDWR per minute remained significant (β = .68, t (45) = 3.45, p =.001), while percentage of code-switched utterances remained non-significant (β = −.18, t (45) = −1.06, p = .29).

As percentage of code-switched utterances was no longer significant after Mandarin NDWR per minute was added to the model, it is possible that Mandarin NDWR per minute mediated the relationship between teachers’ ratings of Mandarin competency and code-switched utterances. A mediation analysis was conducted using a four-step approach in hierarchical regressions (Baron & Kenny, Reference Baron and Kenny 1986 ). Controlled for age, the percentage of code-switched utterances and Mandarin NDWR per minute at T1 individually predicted teachers’ ratings of Mandarin competency at T2, β = .46, t (47) = 3.47, p = .001, and β = .69, t (47) = 6.27, p < .001, respectively (see Figure 1 and Table A2 for the detailed regressions). The percentage of code-switched utterances also significantly predicted Mandarin NDWR per minute at T1, β = .76, t (47) = 7.98, p < .001. However, the percentage of code-switched utterances was no longer significant when Mandarin NDWR per minute was controlled for, β = −.15, t (45) = −.86, p = .39. Thus, Mandarin NDWR per minute at T1 fully mediated the relationship between percentage of code-switched utterances at T1 and teachers’ ratings of Mandarin competency at T2. The mediation effect of Mandarin NDWR per minute at T1 suggests that the amount of code-switched utterances indirectly leads to higher levels of Mandarin competency six months later through higher Mandarin NDWR per minute during the observation period.

Figure 1. Mediation effect of Mandarin NDWR per minute.

4. General discussion

The present study investigated the relationship between children's code-switching behaviour and their language competency in preschool settings. Five- to six-year-old English–Mandarin bilinguals were observed across five days in their childcare centers. The types and amount of code-switched utterances produced by children in their daily conversations, along with their NDWR per minute and MLU for English and Mandarin were measured and analyzed. In addition to the observation sessions, children were administered the English PPVT, and teachers were asked to rate the children's English and Mandarin language competency six months after the observation sessions.

Despite lower levels of proficiency in expressive Mandarin as compared to expressive English, results indicated that the number of code-switched utterances was positively related to Mandarin expressive language competency (NDWR per minute), over and above home language exposure. In other words, children who code-switched more tended to produce a larger variety of Mandarin words, even though this bilingual population is less dominant in Mandarin compared to English. In addition, English language competency (both expressive and receptive) was not significantly related to the amount of code-switched utterances. This is consistent with recent studies that showed that code-switching is not a result of language incompetency (e.g., Cantone, Reference Cantone 2007 ). Most importantly, analyses conducted with teachers’ ratings of children's language competences for Mandarin and English showed that the amount of code-switched utterances (over and beyond the current levels of expressive English) positively predicted children's English and Mandarin competency six months later, but the latter relationship is mediated by their current levels of expressive Mandarin.

These findings illustrate that, contrary to popular belief, code-switching in bilingual children does not signal linguistic incompetency . Rather, code-switching is positively associated with language competency. These findings put forward the possibility that children may be using code-switching as a platform to aid the development of their languages, especially the weaker one. Young bilingual children may not be able to express themselves fully and accurately in both of their languages yet. Code-switching thus allows them to explore and use both languages (the weaker language with the stronger one) while keeping the intended meaning intact. This is in line with the Ivy Hypothesis, which argues that children code-switch to improve their weaker language by using the grammatical structure they have acquired in their stronger language (e.g., Bernardini & Schlyter, Reference Bernardini and Schlyter 2004 ; Gawlitzek-Maiwald & Tracy, Reference Gawlitzek-Maiwald and Tracy 1996 ). Bernardini and Schlyter ( Reference Bernardini and Schlyter 2004 ) found that the majority of the mixed utterances produced by Swedish–Italian and Swedish–French bilingual children consisted of single words or simple phrases in their weaker language combined with more complex phrases from their stronger language. Additional support for this hypothesis comes from a study illustrating syntactic transfers of wh in-situ interrogatives and prenominal relative clauses from Cantonese to English in a Cantonese–English bilingual child during the period when his Cantonese syntactic development was significantly ahead of his English syntactic development (Yip & Matthews, Reference Yip and Matthews 2000 ). Thus, code-switching can be used as a scaffold for the weaker language, where more complex syntactic structures from the stronger language are used in combination with lexical items and simpler syntactic structures from the weaker language.

This argument that code-switching may be helpful to young bilingual learners is not dissimilar to that proposed by researchers on translanguaging. According to Garcia and Wei (2013), translanguaging refers to the idea that bilingual speakers have one linguistic repertoire that holds concepts socially constructed from both languages. Research on translanguaging, which focused mainly on the use of translanguaging within the classroom context, have found that translanguaging facilitates deeper thinking in bilingual students, and can be used by teachers to aid bilingual speakers in subjects taught in their weaker language (e.g., Creese & Blackledge, Reference Creese and Blackledge 2010 ; Hornberger & Link, Reference Hornberger and Link 2012 ). Teachers can leverage on the bilingual students’ stronger language to provide the students with a platform to participate, elaborate on their thought processes and raise questions. This is similar to our proposal that code-switching allows young bilingual children to leverage on their stronger language in daily communications and dual language learning contexts. It provides young bilingual children with an alternative tool to express their thoughts, feelings, and ideas. For these young learners of two languages, code-switching can be used as a form of communicative support and as a way to expand these emergent bilinguals’ understanding and linguistic competency.

This follows that, despite mounting concerns about the potential negative impacts of parental code-switching on an infant's language development (Byers-Heinlein, Reference Byers-Heinlein 2013 ), children's code-switching behaviour itself does not necessarily indicate linguistic incompetency, nor will it negatively affect children's language development. Research has shown that language input from parents and teachers are critical to children's language development, in terms of vocabulary size (Bowers & Vasilyeva, Reference Bowers and Vasilyeva 2011 ; Hammer, Davison, Lawrence & Miccio, Reference Hammer, Davison, Lawrence and Miccio 2009 ; Hoff, Reference Hoff 2006 ; Hoff, Core, Place, Rumiche, Señor & Parra, Reference Hoff, Core, Place, Rumiche, Señor and Parra 2012 ; Hurtado, Marchman & Fernald, Reference Hurtado, Marchman and Fernald 2008 ), grammatical development (Blom, Reference Blom 2010 ; Bohman, Bedore, Peña, Mendez-Perez & Gillam, Reference Bohman, Bedore, Peña, Mendez-Perez and Gillam 2010 ) and comprehension skills (Dickinson & Porche, Reference Dickinson and Porche 2011 ; Huttenlocher, Vasilyeva, Cymerman & Levine, Reference Huttenlocher, Vasilyeva, Cymerman and Levine 2002 ). However, children's usage of the language(s) is also an important factor in language development. Studies, for example, found that increasing the use of a second language is associated with improved proficiency in that language (Freed, Segalowitz & Dewey, Reference Freed, Segalowitz and Dewey 2004 ; Martinsen, Baker, Bown & Johnson, Reference Martinsen, Baker, Bown and Johnson 2011 ). Thus, while it remains important that the language input children receive should accurately reflect the linguistic characteristics of the target languages, bilingual children's regular use of both languages should be highly encouraged too, even if it involves switching between the two languages. Our results elucidate that the act of code-switching by children may have provided them with a way to engage both their languages more frequently, particularly the weaker language. To put it simply, code-switching in a multilingual environment may present bilingual children with opportunities to use both their languages in ways that a pure language environment alone would not be able to provide them with. This, in turn, has a positive outcome on language development with improved proficiency.

Language and literacy development guidelines from the local curriculum framework were used in this study to create a teacher's rating scale to measure children's language competencies. This scale is relevant to the local context and it captures the major receptive and expressive language proficiency requirements as expected of a 6-year-old. Similar uses of teachers’ assessment of children's language skills are often employed in both research and educational settings (e.g., August, Shanahan & Escamilla, Reference August, Shanahan and Escamilla 2009 ; Sundberg & Partington, Reference Sundberg and Partington 1998 ). Nevertheless, this scale has some limitations. First, the rating scale is not a standardized measurement of language competency. Second, teachers’ ratings could be subjective and were based on retrospective reporting. Thus, measures of children's language competency based on teachers’ ratings may not reflect children's full extent of their language ability. However, finding an assessment tool that has been validated for use in multiple languages, in this case English and Mandarin, is a challenge. Standardized measures of language ability such as the Peabody Picture Vocabulary Test (Dunn & Dunn, Reference Dunn and Dunn 2007 ), subtests of Woodcock-Johnson Tests of Achievement (Woodcock, McGrew & Mather, Reference Woodcock, McGrew and Mather 2001 ), and Clinical Evaluation of Language Fundamental Preschool (CELF; Wiig, Secord & Semel, Reference Wiig, Secord and Semel 2004 ) are available in English but not in Mandarin. Even if they are available in Mandarin, there remains a possibility that the materials of these language assessment tools may not be appropriate for the local children and thus may not accurately reflect their true language ability (Brebner, Rickard-Liow & McCormack, Reference Brebner, Rickard-Liow, McCormack and Lind 2000 ; Carter, Lees, Murira, Gona, Neville & Newton, Reference Carter, Lees, Murira, Gona, Neville and Newton 2005 ). Furthermore, researchers have not agreed on the assessment tools that are best for assessing the language ability of bilingual children (e.g., Bedore & Pena, Reference Bedore and Pena 2008 ; Gutiérrez-Clellen, Reference Gutiérrez-Clellen 2002 ; Saenz & Huer, Reference Saenz and Huer 2003 ), and published self-report tools are not appropriate for use by children (e.g., LEAP-Q; Marian, Blumenfeld & Kaushanskaya, Reference Marian, Blumenfeld and Kaushanskaya 2007 ). Taking these challenges into consideration, we believe that our teacher's rating scale of language competency is a relatively appropriate language measure in this context, albeit with limitations. Future studies should consider replicating the present study with a different population of children where standardized language assessment tools in both languages are available and well tested.

It is worth noting that a bilingual child's exposure to his or her two languages may vary a lot during six months due to external factors, such as changed input at home or at school, or internal factors, such as when the child identifies himself or herself more with one language's culture or when the child refuses to speak in one language, Such factors may affect a child's code-switching behavior as well. While we agree that bilingualism could vary substantially in an individual within six months, we believe that the bilingual status of the children in our study is relatively stable throughout the study. The children in our study had been in the same preschool for the past 6 months with no known significant changes to their family or parental background, or to their preschool routines and teachers. Thus, it is unlikely that these children experienced a significant change in their language environments. Nevertheless, future studies should consider collecting information about possible external and internal factors affecting children's language balance during the period of study, such as through additional parental and teachers’ surveys.

We have earlier raised the possibility that the use of MLU to assess children's language complexity in this study may be limited due to a ceiling in age and morpheme count. Compounding this issue is the challenge of computing MLU as an indicator of language competence across two typologically different languages like English and Mandarin. The difficulty in using MLU to assess children's English language complexity is particularly noted in the case of Singapore Colloquial English (SCE). Two common features of SCE are the absence of subject, for example, (e.g., “ (That car) very expensive, you know”) and the deletion of the copula ‘be’ (e.g., “that boat ø very short one”) (Leimgruber, Reference Leimgruber 2011 ). Thus, the use of English MLU to assess children's English language complexity in this context may be limited. Future investigations examining whether code-switching affects children's syntactic development of their two languages could employ more specific measures other than MLU, e.g., an elicited imitation task to assess sentence formation (Lust, Chien & Flynn, Reference Lust, Chien, Flynn and Lust 1987 ; Lust, Flynn & Foley, Reference Lust, Flynn, Foley, McDaniel, McKee and Cairns 1996 ), the truth-value judgment task (Lust & Blume, Reference Lust and Blume 2016 ), or an adaptation of adult syntactic complexity tasks that use not just length measures but also ratio measures such as sub-clauses/sentence (e.g., Bulté & Housen, Reference Bulté and Housen 2012 ; Norris & Ortega, Reference Norris and Ortega 2009 ).

Children code-switch for various reasons. Future studies can tap on multiple age groups or conduct a longitudinal study to further investigate the developmental shifts in the use of code-switched utterances. For example, studies that have found that children engaged in code-switching behavior in order to fill their lexical gaps considered younger children typically around or before the age of 3 years (Cantone, Reference Cantone 2007 ). Studies that have found that children make use of code-switches for sociocultural or pragmatic purposes have focused mainly on older children (Chung, Reference Chung 2006 ; Reyes, Reference Reyes 2004 ; Vu et al., Reference Vu, Bailey and Howes 2010 ). It is logical that very young bilingual children first start off with a limited lexicon, and would, therefore, code-switch when they do not have the translation equivalent of a particular concept (De Houwer, Reference De Houwer, Kroll and de Groot 2005 ; Cantone, Reference Cantone 2007 ). After acquiring a sizeable lexicon in both languages and learning their sociolinguistic rules and cultural practices, older bilingual children would begin to code-switch depending on the social demands of the conversation (Nicoladis & Genesee, Reference Nicoladis and Genesee 1997 ). The children in our study were 5 to 6 years of age and were likely aware, to some degree, of the sociolinguistic rules used in their community. Including multiple age groups in future studies would shed light on the developmental trends in bilingual children's code-switching behavior.

In conclusion, the goal of the present study was to further elucidate the relationship between bilingual children's code-switching behavior in their larger language environment and their linguistic competency. Debate about whether bilingual children's code-switching behavior reflects their linguistic incompetency is ongoing. The present study is the first attempt to investigate this relationship using a quantitative approach. Findings from the present study provide counter-evidence against the linguistic incompetency hypothesis – there was no indication that bilingual children's code-switching behavior was a result of their linguistic incompetency. Instead, bilingual children's code-switching behavior suggests greater language competency. The findings from the present study provide an alternative perspective on the linguistic incompetency hypothesis – that, far from being debilitating, code-switching plays an important and positive role in language development of bilingual children, especially in the context of the larger language environment.

To view supplementary material for this article, please visit https://doi.org/10.1017/S1366728917000335

Appendix 1. Questionnaire for Teacher's Ratings of Language Competency.

Appendix 2. Summary of Mediation Analysis of Mandarin NDWR Per Minute.

* We are grateful to the children and parents who participated in the study and to the teachers and staff of Creative O Preschoolers’ Bay, and Red SchoolHouse. We thank Ferninda Patrycia, Xiaoqian Li, Wanyu Hung, Yvonne Yong, Wei Xing Toh, Lu Xing, Qi Xuan Yap, Tony Zhao Ming Lim, and Yuxin Lou for their help in this study. The corpus from this study is published in CHILDES/Biling/Singapore. Portions of this work were previously presented at the BUCLD 39 (2014) and in Yow, Patrycia, and Flynn (2016). This research was supported by the SUTD SRG grant (SRG HASS 2011 011) and the SUTD-MIT IDC grant (IDG31100106 and IDD41100104) awarded to the first author.

Supplementary material can be found online at https://doi.org/10.1017/S1366728917000335

1 Singapore is made up of 74.3% ethnic Chinese, 13.3% ethnic Malay, 9.1% ethnic Indian and 3.2% Others (Singapore Department of Statistics, 2015). English is the official working language while Mandarin, Bahasa Melayu and Tamil are the official mother tongue languages. Singapore adopts a bilingualism policy that obliges all children enrolled in Singapore schools to learn English and a mother tongue according to their ethnicity, but most subjects are taught in English (Gopinathan, 1999). Hence, all Singaporean children speak English as a shared language, but they are also expected to be fluent in their mother tongue language.

2 Many childcare centers conduct lessons in English and one of the mother tongue languages to prepare the children before entering elementary school.

3 Singlish, also known as Singapore Colloquial English, is a creolized form of English spoken in Singapore (Platt, 1975).

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• Volume 21, Issue 5
• W. QUIN YOW (a1) , JESSICA S. H. TAN (a1) and SUZANNE FLYNN (a2)
• DOI: https://doi.org/10.1017/S1366728917000335

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• DOI: 10.15282/ijleal.v13i2.9585
• Corpus ID: 265267461

Issues and Functions of Code-switching in Studies on Popular Culture: A Systematic Literature Review

• Siti Nur Atikah Nazri , Asiah Kassim
• Published in International Journal of… 15 October 2023
• Linguistics
• International Journal of Language Education and Applied Linguistics

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