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Shared processing strategies as a mechanism for contact-induced change in flexible constituent order

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Published/Copyright: February 17, 2025

Abstract

This article argues for collecting primary data using psycholinguistic methods to better explain contact-induced change in constituent order. I compare the results of acceptability judgment experiments in Hindi-Urdu, Korean, and Malayalam, asking how ratings of the six grammatical orderings of subject, object, and verb might be affected by different contexts of experience with English. Two hypotheses are considered: (1) shared constructions: ratings of SVO, the canonical order in English, will vary with respect to language contact measures, or (2) shared processing strategies: overall ratings of noncanonical orders in each language will be affected by experience with English, a less flexible language. More contact with English corresponded to a greater difference in acceptability between canonical and noncanonical orders in Korean and Malayalam. For Hindi-Urdu, language contact was operationalized via agglomerative clustering, and SVO only behaved differently from other noncanonical orders in one of four participant groups. The shared strategies hypothesis is supported in all cases but one; this variation in results aligns with the variation found in nonexperimental studies of contact effects in constituent order. Taking a gradient approach to measuring both language contact and constituent order is thus a crucial step toward specifying descriptions and explanations of contact-induced syntactic change.

1 Introduction: psycholinguistic processes as a mechanism for contact-induced change in constituent order

How does language contact contribute to language change? This article proposes that finding systematicities across contexts in how language experience contributes to processing and acceptability will allow us to understand how language contact might causally contribute to language change. I compare the effect of experience with English on the acceptability of constituent order in three languages: Korean, Malayalam, and Hindi-Urdu. Despite differences across experiments, it is possible to make relatively fine-grained predictions, and the results are promising for more systematic crosslinguistic comparisons in the future. Rather than providing concrete answers, this article argues for an approach: rejecting dichotomous characterizations of both constituent order and language experience as a step toward explanatory models of contact-induced syntactic change.

Constituent order has been claimed to be particularly prone to influence from language contact (Thomason 2001; Thomason and Kaufman 1988). For example, Bickel (2015) found that geography was a stronger predictor of word order than genetic relationship, which was interpreted to mean that diffusion via language contact is a relevant factor above and beyond genetic relationships in explaining areal tendencies in word order patterns. Indeed, contact-induced change in word and constituent order has been widely documented (e.g., Naccarato et al. (2021) on Russian spoken in Daghestan, Anderssen et al. (2018) on Norwegian spoken in the United States, Friedman (2003) on Turkish spoken in Macedonia, and El Zarka and Ziagos (2020) on Arabic in contact with Persian). The phenomenon is pervasive, but the mechanisms remain underexplored.

I take a typological approach (see also Chen and Myers 2017; Hemforth et al. 2015; Moore et al. 2015), assuming that crosslinguistic processing and production are domain-general mechanisms which interact with the specific linguistic structures in the languages speakers know. Under this set of assumptions, systematically investigating the outcomes of language contact via psycholinguistic methods can help explain crosslinguistic tendencies in contact-induced change. Ultimately, the goal of this enterprise largely aligns with Bickel’s (2015) characterization of the goals of Distributional Typology – to determine “What’s where, why?” – albeit with the added emphasis on “what,” as sharpening description is necessary to better understand mechanisms.

1.1 Crosslinguistic differences in constituent order processing

Proposed psycholinguistic mechanisms for diachronic change in constituent order almost universally refer to some notion of parsing or production efficiency, though the degree to which the functional explanations themselves are foregrounded varies greatly (Futrell et al. 2020; Hawkins 1994, 2014; Kauhanen and Walkden 2018; Levshina 2021). These studies mainly employ corpora as data sources, which are advantageous in that they provide examples of language as it is used in context, as well as allowing for explanations which take frequency of use as an explanatory factor. However, written varieties of spoken languages are overrepresented in corpora, and there are no appropriate corpora for many languages or varieties (though see Kramer 2021; Levshina 2017). Behavioral experiments can include languages and varieties not represented in corpora, alongside allowing for more direct testing of the proposed psycholinguistic factors hypothesized to contribute to syntactic change.

Previous psycholinguistic research has consistently shown that, absent a discourse context, canonical and noncanonical orders are distinguishable behaviorally and neurally, with noncanonical orders being read more slowly (Miyamoto and Takahashi 2001), rated lower (Bader et al. 2023; Weskott and Fanselow 2011), and resulting in sustained anterior negativity (Kwon et al. 2013) as compared to canonical orders. These measures are each interpreted as corresponding to processing effort associated with noncanonical orders as compared to canonical ones, and there is robust experimental evidence that factors such as prosody (Wolff et al. 2008) and discourse context (Bader et al. 2023; Kaiser and Trueswell 2004) either remove or make irrelevant this effort. In order for processing strategies to be a candidate mechanism for contact-induced change, a crucial question to address is what meaningful differences there might be across languages in how constituent order is processed. Here, the predictions are not straightforward, and the evidence is mixed (Husain et al. 2014; Konieczny 2000; Schwab et al. 2022; Suresh 2021).

The present approach is motivated by two literatures which discuss similar phenomena across different timescales, using slightly different terminology. In the language contact and historical linguistics literature, contact effects are often described across years and generations, while psycholinguistic experiments, often situated in bilingualism or heritage language research, ask about the effect of participants’ language experience on a particular behavioral or neural measure within the timescale of an experiment or the unfolding of a single sentence. I draw on approaches such as those of Hawkins (1994), Christiansen and Chater (2016), and Backus (2020), which assume that processes which can be measured at the timescale of an experiment feed into and can explain processes at longer timescales, such as language change and language evolution (see also Roberts et al. 2020; Roberts and Sneller 2020). For identifying psycholinguistic mechanisms of contact-induced change, under this approach, differences in linguistic behavior in an experimental context based on language experience measures are assumed to be directly relevant to longer-term community level contact effects which can then be detected and described across years or generations.

In addition, assuming gradience in constituent order (Levshina et al. 2023) allows us to more accurately capture variation and facilitates the use of statistical tools for identifying the sources of variation across languages, constructions, and individuals. Taking a gradient approach allows us to investigate the role of contact in causing more systemic influences on constituent order, such as changes in degree of flexibility (Heine 2008), alongside detecting the types of changes which are more easily measured, such as a shift in the canonical or basic order (Valk 2014).

1.2 Moving past dichotomous notions of language contact

Models such as the one presented in Lucas (2012) discuss processing factors as a mechanism of contact-induced change. However, most models of contact-induced change make relatively coarse-grained assumptions about how individuals differ when it comes to language experience, making strict divides between L1 acquirers and L2 learners. Here, bringing in insights from the bilingualism literature (Luk and Bialystok 2013; Ortega 2020; Surrain and Luk 2019) and related work pushing against essentialist notions like “nativeness” (Cheng et al. 2021, 2022) allows us to make more precise predictions and more accurately characterize a larger range of diversity when it comes to language experience.

Following these assumptions, this article compares higher- and lower-contact varieties. This approach intentionally does not treat a “monolingual” variety as the reference population (Rothman et al. 2022) because there are likely important qualitative differences in terms of contexts of language learning and use between such groups (cf. Ellis 2008), if the groups themselves can be said to exist at all. Furthermore, it is crucial that psycholinguistics and language contact research does not ignore the multilingualism and heterogeneous linguistic repertoires of lower-contact groups either. Instead, this approach assumes heterogeneity within each language group and compares how specific measures of language contact might have an effect on acceptability (Cheng et al. 2022). Language contact is operationalized slightly differently in each case, as the factors which correspond to increased contact with English were different for each participant population (Table 3).

2 Experiments

This section presents and compares results from three acceptability judgment experiments conducted in Korean (Namboodiripad et al. 2017), Malayalam (Namboodiripad 2017: Chapter 4), and Hindi-Urdu (Upreti and Namboodiripad 2022).

2.1 Korean, Malayalam, and Hindi-Urdu constituent order

Korean, Malayalam, and Hindi-Urdu could each be labeled as “SOV flexible,” as the canonical (discourse neutral, intonationally unmarked) order of major constituents is SOV, all six orders of subject, object, and verb are attested and have the same truth-conditional meaning, and considerable discourse-mediated flexibility has been described (Asher and Kumari 1997; Huh 1988; Ko 2014; Namboodiripad 2017; Ranjan et al. 2022; Sohn 2001). Each language also allows omission of subjects and objects. As such, a sentence beginning with a verb could either signal the end of a sentence with two omitted arguments or the beginning of a verb-initial sentence with one or two expressed arguments. Prosodic cues should reduce or remove this uncertainty (Šimík and Wierzba 2015), but the extent to which that is the case is currently unexplored.

Argument flagging and indexing, morphological marking on arguments and verbs that indicates who did what to whom (Haspelmath 2019), are also potentially relevant to constituent order processing. Verbs in Korean and Malayalam do not agree with subjects or objects, while Hindi-Urdu has subject-verb agreement. Subjects and topics, as well as objects, are marked in Korean, while subjects and objects are marked in Hindi-Urdu. In Malayalam, subjects are not overtly marked, and there is differential object marking, in that inanimate objects of transitive verbs are not marked. Some relevant typological features are summarized in Table 1.

Table 1:

Some typological features of the three languages in contact with English.

Korean Malayalam Hindi-Urdu
Glottocode Kore1280 Mala1464 Hind1270
Language family Koreanic South Dravidian Indo-Iranian
Canonical order SOV SOV SOV
# Grammatical orders 6 6 6
Argument flagging Yes Differential object marking Yes
Argument indexing None None Subject-verb
Argument-drop Yes Yes Yes

2.2 Methods

This section describes the similarities and differences across experiments; I refer the reader to Namboodiripad et al. (2017), Namboodiripad (2017), and Cheng et al. (2022) for details.

2.2.1 Experimental items

Experimental items (Table 2) consisted of animate subjects (all agents), inanimate objects (all patients), and transitive verbs. Words were chosen to be high in subjective frequency, early-acquired, and culturally relevant. Fillers which varied in length and structure were constructed to avoid ceiling and floor effects and to mask experimental items; these included unambiguously ungrammatical and semantically implausible items (with an approximately 2-to-1 ratio of fillers to experimental items; Goodall 2021). Items were recorded by collaborators who grew up speaking the relevant language (see Sedarous and Namboodiripad 2020).

Table 2:

Example stimuli for each experiment.

Korean Malayalam Hindi-Urdu
‘(The) girl drank green tea’ ‘An ironer pressed (a) blouse’ ‘(The) boy stole (the) toy’
SOV sonyeo-ka nokcha-lul masi-ess-ta bacche-ne khilona churaya-tha
girl-nom green tea-acc drink-pst-decl an ironer blouse pressed boy-nom toy-acc steal-pst
OSV nokcha-lul sonyeo-ka masi-ess-ta khilona bacche-ne churaya-tha
green tea-acc girl-nom drink-pst-decl blouse an ironer pressed toy-acc boy-nom steal-pst
SVO sonyeo-ka masi-ess-ta nokcha-lul bacche-ne churaya-tha khilona
girl-nom drink-pst-decl green tea-acc an ironer pressed blouse boy-nom steal-pst toy-acc
OVS nokcha-lul masi-ess-ta sonyeo-ka khilona churaya-tha bacche-ne
green tea-acc drink-pst-decl girl-nom blouse pressed an ironer toy-acc steal-pst boy-nom
VSO masi-ess-ta sonyeo-ka nokcha-lul churaya-tha bacche-ne khilona
drink-pst-decl girl-nom green tea-acc pressed an ironer blouse steal-pst boy-nom toy-acc
VOS masi-ess-ta nokcha-lul sonyeo-ka churaya-tha khilona bacche-ne
drink-pst-decl green tea-acc girl-nom pressed blouse an ironer steal-pst toy-acc boy-nom

Mediated by given-new preferences, definiteness is known to influence ordering preferences (Faghiri et al. 2014; Kizach and Balling 2013; Šimík and Wierzba 2015); definiteness was held constant across conditions within experiments, based on what sounded most natural to the collaborator who recorded the items. For Korean and Hindi-Urdu, with overt case-marking on all arguments, no additional determiners were used. In Malayalam, the indefinite determiner oɾu was used with subjects.

For each language, noncanonical orders have been described as associated with non-neutral discourse contexts. However, the extent to which factors such as information structure facilitate particular orders is not agreed upon, either for these individual languages or for flexible languages overall (Laleko 2022). The picture is further complicated by language contact research which proposes that changes to the extent to which particular orders are tied to a discourse context could be a mechanism of contact-induced change in constituent order (e.g., Fortescue 1993), alongside bi/multilingualism research which shows differential relationships between language experience and processing or acceptability of noncanonical orders in particular discourse contexts (Hoot 2017, 2019; Ionin et al. 2023; Laleko 2022). This means that crosslinguistic and within-language variability in the role of discourse context should be expected in contact situations. Practically speaking, the number of experimental conditions required for a systematic investigation of contexts across all six orders would not be feasible in a single experiment (cf. Hoot (2012) which investigates three orders in context). As such, these experiments held discourse context constant by not including it, keeping the relative tightness of particular orders with particular contexts as an important topic for future inquiry.

2.2.2 Participants and procedure

There were three groups of Korean speakers in Namboodiripad et al. (2017): “Korean-dominant,” “English-dominant, Korean-speaking,” and “English-dominant, Korean-understanding”; all were college-educated and in their early to mid 20s and grew up with Korean as their home language. The Korean-dominant group grew up in Korea, hearing, speaking, and being educated in Korean, with some understanding of spoken English and experience writing and reading English, mainly in academic contexts (cf. Leuckert and Rüdiger 2020). Both English-dominant groups grew up mainly in the United States, hearing Korean at home. The US-based participants were recruited from a heritage Korean language class at a large public university in Southern California. Two distinct groups were identified. The “English-dominant, Korean-speaking” participants, who grew up speaking Korean at home, felt very comfortable speaking it, and sounded fluent to a linguistically trained Korean speaker from Korea. The “English-dominant, Korean-understanding” participants had more limited experience and less comfort speaking Korean, but had no trouble understanding Korean (cf. “receptive bilinguals”; Beardsmore 1986).

All Malayalam-speaking participants lived within 15 square kilometers of each other in a region of India where Malayalam is the official language. They ranged in age (18–82), occupation, and socio-ethnic background. An exploratory analysis was conducted to investigate which aspects of language history and use might be most relevant to predicting degree of English contact in this population. Age emerged as the strongest predictor of a range of factors, such as preference for reading and writing in English, medium of education, and consumption of English media (see also Kala 1977; Namboodiripad 2021). Age was thus selected as a continuous proxy variable for language contact (Namboodiripad 2017).

The Hindi-Urdu participants were recruited online, ranged in age (18–57), listed English as the main or only “other” language in their linguistic repertoires, and were located in both South Asia and the United States. Cheng et al. (2022) divided these participants into four groups based on an agglomerative clustering analysis of their responses to 10 continuously measured questions about their experience and comfort with Hindi-Urdu. Details can be found in Cheng et al. (2022); here, I note that this yielded four groups whose language experience profiles were interpretable based on previous research on diaspora varieties (Benmamoun et al. 2013; Hopp and Putnam 2015). Group B rated themselves the highest across the board for all measures, while Group A rated themselves the lowest overall. Group C patterned with Group B when it came to self-ratings of comfort understanding, speaking, reading, and writing Hindi-Urdu, but rated themselves lower in terms of current and childhood experience with the language. Group D patterned with Group B in terms of experience with Hindi-Urdu, but rated themselves much less comfortable producing the language. While Group B can be thought of as most Hindi-Urdu dominant and Group A the least, the comparisons with Groups C and D are not straightforward. Instead, these groups are best thought of as representing four different profiles of contact between Hindi-Urdu and English.

Table 3 summarizes the contact situations for each group and describes how language contact was operationalized.

Table 3:

Description of participants and contact contexts across the three experiments.

Korean Malayalam Hindi-Urdu
Year 2016 2016 2021
Contact context Diaspora Globalization Diaspora + globalization
Location US, Korea Kerala, India US, South Asia
Questions asked Location, comfort speaking Language use, history Language use, history
Proxy variable Location, dominance Age Cluster
Variable type Categorical Continuous Emergent category
Experimental context In classrooms In homes Online
Total participants 57 43 60

2.2.3 Procedure

Acceptability judgment experiments were used because they are portable, yield gradient results, and are relatively robust to noise, so ideal for non-lab data collection (see Francis 2021; Goodall 2021; Levshina et al. 2023; Namboodiripad 2017; Sedarous and Namboodiripad 2020). Crucially for investigating constituent order in these languages, acceptability ratings are sensitive enough to consistently detect differences between grammatical sentences and can reliably detect potentially subtle differences across participants (Dąbrowska 2012; Weskott and Fanselow 2011).

Participants were instructed that they would hear sentences which range in terms of how strange or natural they might sound. Participants were asked to rate each sentence based on how good it sounded to them, keeping in mind everyday language. Participants heard each sentence only once; the in-person experiments were run on the researcher’s laptop in a quiet room, and participants were provided headphones to wear. In the online experiment, participants were asked to use headphones and/or complete the experiment in a quiet room, using their own devices.

The Malayalam and Korean experiments were approved by the University of California, San Diego Human Research Protections Program (#140943SX), and the Hindi-Urdu experiment was reviewed and given the status EXEMPT by the University of Michigan Institutional Review Board (HUM00142209).

2.3 Predictions

These experiments investigate varieties of Korean, Malayalam, and Hindi-Urdu which are in contact with at least one variety of English. Noncanonical orders are expected to be rated lower than canonical orders, reflecting complex interactions between factors such as lower conventionality (Perek and Hilpert 2014; Valk 2014), having to construct a felicitous discourse context (Bader et al. 2023; Kaiser and Trueswell 2004), and typologically variable constraints such as dependency-length minimization and agent-first preferences (Clark et al. 2023; Ferrer-i Cancho and Namboodiripad 2023; Futrell et al. 2020; Garrido Rodriguez et al. 2023; Liu et al. 2022; Nordlinger et al. 2022). The following predictions are based on the assumption that differences in language experience across the lifespan can lead to differences in how these factors interact, surfacing as variation in acceptability ratings.

American English, a relevant contact variety for all participants based in the United States, is a canonically SVO West Germanic language, with OSV order via topicalization (Gregory and Michaelis 2001). All other orders of subject, object, and verb are ungrammatical. Increased topicalization has been associated with language contact in several varieties of English (Prince 1988, 1998), including “Korean (ized) English” (Leuckert and Rüdiger 2020), relevant for the South Korean participants. While the relevant contact varieties of Indian English are notably diverse, across and within participants in the Malayalam and Hindi-Urdu experiments, the degree to which there is variation in constituent order is as of yet unknown, though wider use of non-SVO orders have been documented (Lange 2012). Based on the available literature, these predictions assume that all relevant Englishes are (1) canonically SVO and (2) less flexible than the target languages, Malayalam, Korean, or Hindi-Urdu.

2.3.1 SVO is affected: shared constructions

A straightforward prediction is that more English contact means more experience with SVO order, which could correspond to differences in the status of SVO in the target language. For measures of online processing, this might lead to faster relative reading times, smaller pupil dilations, or other measures corresponding to reduced surprisal for the post-verbal object. For acceptability, this would correspond to higher ratings of SVO order. However, previous research has also shown that increased dominance in English leads to lower ratings of SVO in the target language; Anderssen et al. (2018) found that English-dominant Norwegian speakers, associating the noncanonical but grammatical VO order as being more “English-like,” rated it lower than did participants who were less English-dominant. This indicates an effect of language ideology and metapragmatic salience, both of which are mechanisms of contact-induced change and non-change (Gal and Irvine 1995; Rodríguez-Ordóñez 2019; Thomason 2014). Whatever the direction, if SVO is uniquely affected by English contact, this means that SVO constructions are shared to some degree across languages (see Ungerer 2021).

2.3.2 Noncanonical orders overall are affected: shared strategies

English contact could also lead to a greater preference for the canonical order in the non-English language, here, SOV. One reason for this could be about overall language experience; if more experience with English means less experience with the other language, this could also mean less experience with the noncanonical orders in those languages, which are also less frequent. Reduced experience with a construction could lead to increased processing effort and lowered acceptability for noncanonical orders across the board. Because acquisition of noncanonical orders occurs relatively early in development (Gavarró et al. 2015; Kim 1997; Kim et al. 2018; Leela 2016), this would most likely be driven by differences in language experience later in life.

A related explanation has to do with the discourse functions of noncanonical orders, whereby noncanonical orders become less tied to particular discourse contexts in times of change or shift and are therefore used more interchangeably (Fortescue 1993; Kiparsky 1996). The prediction for acceptability based on this would be fewer distinctions between noncanonical orders, as these constructions would be less differentiated. Similarly, bilingualism research finds that decreased dominance and/or proficiency corresponds to a weaker relationship between discourse context and focus constructions in canonically SVO flexible constituent order languages in contact with English. Depending on the details of the relevant constructions, higher-contact participants have shown a greater relative preference for canonical order (e.g., in Russian; Laleko 2022) or higher ratings of a noncanonical order (e.g., in Spanish; Hoot 2017).

For the present study, experience with a non-verb-final language could modulate expectations about arguments appearing after the verb in general (as opposed to specifically SVO). Further, experience with a language in which all arguments usually appear – as is the case for the translation equivalents of the experimental items in the relevant Englishes – might lead participants to expect arguments to appear, even if in a noncanonical position. Alternatively, high-contact participants might make weaker predictions overall because, being in multilingual contexts, they are more used to processing over uncertainty, leading them to make less strong expectations and therefore showing fewer or weaker indicators of processing effort (cf. Evans and Tomé Lourido 2019; Kutlu et al. 2022).

Acceptability judgment experiments can address the question of shared constructions versus shared strategies by asking whether acceptability of SVO in Korean, Malayalam, and Hindi-Urdu is affected by contact with English, either in addition to or as opposed to acceptability of noncanonical orders overall. Further, we can ask how contact with English corresponds to the degree to which orders are rated similarly to each other, addressing the question of how contact affects overall constituent order flexibility.

2.4 Results

This section describes the results across experiments, focusing on the relative ratings of SOV and SVO, the extent to which orders were rated reliably differently from each other, and which orders grouped together. Figure 1 plots the conditional effects of Bayesian ordinal regression models for each experiment, fit using the brms package (Bürkner 2017) in R (R Core Team 2024); see Table 4 (code with full models and data is available at https://osf.io/wmr9f/.).

Figure 1: 
Plot of the conditional effects of the Bayesian ordinal regression models. For Korean and Hindi-Urdu, dots represent estimates and bars represent 95 % confidence intervals. For Malayalam, slopes represent the estimates of ratings for each condition by age, and shaded areas represent 95 % confidence intervals.
Figure 1:

Plot of the conditional effects of the Bayesian ordinal regression models. For Korean and Hindi-Urdu, dots represent estimates and bars represent 95 % confidence intervals. For Malayalam, slopes represent the estimates of ratings for each condition by age, and shaded areas represent 95 % confidence intervals.

Table 4:

The fixed effects and random intercepts in the brms models used to reanalyze the data from each experiment.

Fixed effects Random intercepts
Korean Response ∼ condition * group Participant, item
Malayalam Response ∼ condition * age Participant, item
Hindi-Urdu Response ∼ condition * group Participant, item

Note that it is possible for groups of participants to have the same number of distinctions and yet differ in the degree to which those orders are rated differently from each other. This was the case for the Korean experiment: SOV was rated highest, followed by OSV. SVO and OVS grouped together in acceptability, followed by VSO and VOS (confirmed via post hoc t-tests with pooled SD, Bonferroni-corrected, using p < 0.05 as a significance threshold). The main difference between groups was in the relative rating of SOV and noncanonical orders – this difference increased with greater dominance in English (Namboodiripad et al. 2017). So, despite having the same number of distinctions, there was a quantitative difference across groups, with a greater difference between orders – lower flexibility – corresponding to more contact.

For Malayalam, there was a main effect of age such that older participants tended to give lower ratings, driven by their ratings of canonical SOV order. Namboodiripad (2017) divided participants into two groups based on a median split in age and conducted post hoc t-tests (pooled SD, Bonferroni-corrected, p < 0.05 significance threshold). Younger participants had a three-way distinction in constituent order: SOV was rated highest, followed by OSV, SVO, and OVS, and VSO and VOS were rated equal lowest. Older participants only showed a two-way distinction in constituent order, with the verb-final and verb-medial orders grouping together (SOV, OSV, SVO, and OVS), and the two verb-initial orders being rated equal lowest. The younger, higher-contact participants showed a greater relative preference for SOV, in that they rated SOV differently from all the other orders, unlike the older, lower-contact participants. Increased contact with English corresponds here to less interchangeability between orders as well as a greater difference in mean ratings – lower flexibility.

For Hindi-Urdu, we see distinct patterns in each group. Groups are ordered based on their average self-reported comfort understanding Hindi-Urdu. Figure 2 shows the same estimates from Figure 1, except faceted by group to aid comparison. Group B, which had the highest self-ratings across all language experience questions, patterned similarly to the Korean-dominant group, with SOV rated the highest (Bonferroni-corrected post hoc t-tests with pooled SD confirmed the difference was marginally significant; p < 0.097), followed by OSV. Then, SVO and OVS grouped together in acceptability, followed by VSO and VOS.

Figure 2: 
Plot of the conditional effects of the Bayesian ordinal regression models for Hindi-Urdu, by group. Shapes represent estimates and bars represent 95 % confidence intervals. Verb position is represented by shape, and argument order is represented by border color.
Figure 2:

Plot of the conditional effects of the Bayesian ordinal regression models for Hindi-Urdu, by group. Shapes represent estimates and bars represent 95 % confidence intervals. Verb position is represented by shape, and argument order is represented by border color.

Group C reported high comfort producing Hindi-Urdu but lower childhood experience with the language; they showed a three-way distinction, with verb-final orders grouping together and rated higher than verb-medial orders, followed by verb-initial orders (see a similar pattern in Namboodiripad and Goodall 2016). Groups D and A reported lower childhood experience with and lower comfort producing Hindi-Urdu; for both groups, noncanonical orders were rated similarly as compared to Groups B and C. However, Group D shows a strong relative preference for SOV, with OSV and the verb-medial orders rated similarly, followed by the verb-initial orders. Group A is the only group where SVO patterns differently from OVS, and, indeed, it is rated similarly to canonical SOV.

Constituent order flexibility can be defined as degree of preference for canonical order, which would be operationalized here as the degree to which canonical SOV is rated higher than the other orders (as in Korean and Malayalam). Under such a definition, Group D is the most rigid, followed by Group B, then Group C, then Group A. If defined in terms of number of distinctions (as in Malayalam), Group B is the most rigid, followed by Group C, then Groups D and A.

3 Comparison across experiments

Section 2.3 presented two hypotheses as to how experience with English might affect acceptability of constituent order in Korean, Malayalam, and Hindi-Urdu. First was that acceptability of SVO order would be targeted; this was only found in Hindi-Urdu Group A. Second was that the acceptability of noncanonical orders overall would be affected; this was found in each experiment, but in different ways, as summarized in Table 5. In Korean, the average rating of all noncanonical orders decreased as dominance in English increased, leading to an increased relative preference for SOV being associated with English dominance. However, the number of distinctions between orders was the same. This speaks to the necessity of investigating qualitative and quantitative patterns when it comes to contact effects in constituent order.

Table 5:

Summary of findings across all three experiments.

Effect of English contact on:
Relative SVO preference Relative SOV preference Number of distinctions
Korean None Greater preference None
Malayalam None Greater preference More distinctions
Hindi-Urdu Group A greater preference Group D greater preference Fewer distinctions

For Malayalam, younger participants, who had more intense contact with English, rated noncanonical orders lower as compared to canonical SOV. Analyzing the data via a median split in age showed that older participants had fewer distinctions between orders than did younger participants. This effect was driven by SOV and OSV, with ratings of non-verb-final orders showing little variation based on contact.

The Hindi-Urdu results speak to the importance of how constituent order flexibility is defined. Defining flexibility as a greater relative preference for the canonical order would mean that Group D, one of the higher-contact groups, was least flexible. Defining flexibility based on number of distinctions would mean that Group B, the group most dominant in Hindi-Urdu, was least flexible. However, a greater relative preference for SVO, as in Group A, would lead to greater flexibility under both definitions.

For each experiment, some or all noncanonical orders were affected by contact, pointing to shared processing strategies being a relevant explanatory factor. However, the outcome of contact varied across languages. As found in Korean, Malayalam, and Hindi-Urdu Group D, contact can correspond to higher relative ratings of canonical SOV. The number of distinctions between orders differed based on English experience in Malayalam and Hindi-Urdu, but not in Korean.

How can these findings be reconciled? Language contact research defies neat accounts; as Thomason (2008) argues, the default assumption must be that there are no absolute linguistic constraints, and counterexamples abound. As contact effects are the result of complex interactions of sociocognitive factors, requiring an emergentist and atelic approach (Larsen-Freeman 2013), it is therefore rather expected that English experience had different effects on constituent order, both within and across languages. In fact, the different patterns across Hindi-Urdu groups align with findings that individual variation should be assumed, even for groups hypothesized to be more homogenous, such as “monolinguals” or “native speakers” (Dąbrowska 2012, 2018; Kidd and Donnelly 2020), and even for potentially very basic and early-learned syntactic constructions, such as flexible constituent order.

The differences across these experiments could also be due to meaningful differences in the contexts of language contact. It could be that these differences correspond to real differences in the linguistic ecology of the high-contact speakers, or that the apparent similarities between the three languages are not sufficient to expect similar outcomes in an experimental context. Systematic investigation of the effect of contact between the same varieties in different contexts of contact (insofar as that is possible) and between different varieties in more similar contexts of contact would be crucial next steps for building out and testing the value of this approach, alongside using more online measures of processing effort such as pupilometry (Breakell Fernandez 2016) and asking directly about the role of discourse context in contact (Hoot 2012).

4 Conclusions

This article compared the results of three experiments as a demonstration of how crosslinguistic experimentation might help to address questions about mechanisms of contact-induced change in constituent order. The experiments showed both qualitative and quantitative effects of language contact on the acceptability of flexible constituent order. Despite similarities across these languages, there were differences as to how the noncanonical orders grouped together even in the low-contact groups, indicating that a more fine-grained approach to both typology and contact are necessary in attempting to determine the role of psycholinguistic processes on contact-induced change. For example, noncanonical orders were not consistently rated lower than canonical orders in some higher- and some lower-contact groups of participants, even without discourse context.


Corresponding author: Savithry Namboodiripad, University of Michigan, Ann Arbor, USA, E-mail:

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Received: 2023-06-27
Accepted: 2024-09-13
Published Online: 2025-02-17

© 2025 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  53. Corrigendum to: Sign recognition: the effect of parameters and features in sign mispronunciations
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