A sociolinguistic view of null subjects and VOT in Toronto heritage languages

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A sociolinguistic view of null subjects and VOT in Toronto heritage languages Naomi Nagy * Department of Linguistics, University of Toronto, Sidney Smith Hall, 4th Floor, 100 St. George St., Toronto, Ontario M5S 3G3, Canada Received 7 June 2013; received in revised form 21 April 2014; accepted 22 April 2014

Abstract Multivariate comparison of conversational speech patterns from three generations of heritage language speakers confirm that, for two linguistic variables, no consistent pattern of either attrition or incomplete acquisition emerges. The primary structure examined, for Heritage Cantonese, Italian and Russian, is variable subject pronoun presence. Neither rate of null subject pronouns nor patterns of most contextual factors conditioning the presence/absence of these pronouns differ by generation since immigration or from available Homeland comparators. A second variable, Voice Onset Time (VOT), is introduced for comparative purposes. Unlike the null subject pattern, this variable shows cross-generational drift toward English norms in Heritage Russian and Ukrainian, while Heritage Italian speakers again show no inter-generational differences. For both variables, lack of correlation with measures of language contact, use and attitude makes it difficult to interpret these patterns of variation as evidence of either incomplete acquisition or attrition. Differing outcomes from those of studies conducted in experimental and elicitation paradigms underline the benefit of multiple methodologies. © 2014 Elsevier B.V. All rights reserved. Keywords: Null subjects; Voice Onset Time (VOT); Heritage Italian; Heritage Russian; Heritage Cantonese; Heritage Ukrainian; Variationist sociolinguistics

1. Introduction: Approaches to heritage language study Heritage language studies is an emerging field in linguistics, predicated on the benefit of better understanding how heritage speakers differ both from monolingual and other bilingual speakers (Benmamoun et al., 2010). Two distinct approaches have evolved in the study of heritage languages, with little contact between them. The Experimental Approach, represented in Benmamoun et al. (2010), is based in language acquisition and psycholinguistic methods. The other is based in Comparative Variationist sociolinguistic methods. This paper applies the latter approach and reflects on how methodological differences may produce different views of heritage language grammars and speakers. In the Comparative Variationist Approach, we analyze extended extracts of naturalistic conversational speech elicited via traditional ‘‘sociolinguistic interview’’ methods (cf. Labov, 1984). The grammar of each language variety (e.g., heritage vs. homeland, Generation 1 vs. Generation 2) is first examined as a complete variable system that stands on its own.

Abbreviations: AIC, Akaike Information Criterion; ANOVA, analysis of variance; HLVC, Heritage Language Variation and Change; gen, generation; L1, first language; L2, second language; ms, milliseconds; VOT, Voice Onset Time. * Tel.: +1 416 978 1767. E-mail address: [email protected]. http://dx.doi.org/10.1016/j.lingua.2014.04.012 0024-3841/© 2014 Elsevier B.V. All rights reserved.

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Comparisons between systems (e.g., between generations or between heritage and homeland varieties) are then made using the same methods for each group of speakers. Multivariate regression analysis simultaneously quantifies the effects of multiple contextual factors (linguistic, social and stylistic) that are hypothesized to influence speakers’ performance. This approach allows us to see which factors have an effect on the observed linguistic variation and which may be spurious effects due to interactions with other factors. In the case of heritage language study, comparisons across generations of speakers of one language, between heritage languages and English, and between Heritage and Homeland varieties, allow innovations to be identified and mapped. A critical issue in heritage language studies is the very definition of a heritage language speaker -- the type of speaker included in a study has an important effect on the findings. In the Experimental approach, the definition often relates to performance. For example, Polinsky (2011a:1) states that Heritage languages are spoken by early bilinguals [. . .] whose L1 (home language) is severely restricted because of insufficient input. [. . .] they can understand the home language and may speak it to some degree but feel more at ease in the dominant language of their society. Some prominent examples of this approach include Polinsky and Kagan (2007), who note that features of heritage languages include limited vocabulary, incomplete morphology, impoverished syntax, spotty socio-cultural knowledge and registers that are not fully developed. Similarly, Montrul (2009:241) notes that ‘‘many aspects of grammar may not reach full development and remain incompletely acquired.’’ While Benmamoun et al. (2010:10--11 and subsequent) leave open the possibility that heritage languages speakers may be as proficient as monolinguals, they designate heritage language speakers as ‘‘more likely to speak English . . . [whose] comfort in English increases . . . often at the expense of the home language,’’ following Cho et al. (1997). They continue, ‘‘the crucial criterion is that the heritage language was . . . not completely acquired’’ (Benmamoun et al., 2010:11). After reviewing many experimental studies of heritage language performance in a range of linguistic domains, they conclude that heritage language speakers’ ability lies below the native ability of L1 speakers (Benmamoun et al., 2010:81).1 Certainly, not all experimental work on heritage languages employs ‘‘deficit’’ definitions of heritage language speakers. Experimental studies with participant selection determined by autobiographical characteristics, such as when each language was acquired and when/how often they are used, can be found in, for example, Cuza and Frank (2010:5), Cuza, Pérez-Leroux and Sánchez (2013:14), Liceras and Senn (2009:42). In these reports, there is no indication that participants were filtered according to speaking ability. Putnam and Sánchez (2013:478) define a heritage speaker as ‘‘an individual who acquired an L1 grammar (to some degree of success) of a language that is not the socially dominant language in a given geographical area.’’ However, they do stipulate (Putnam and Sánchez, 2013) that it is not the speaker’s dominant language. In the Comparative Variationist approach, heritage language speakers are defined by their linguistic autobiography. In the case of the present study, this follows from the Canadian government’s definition of a heritage language as a mother tongue that is neither an official language, nor an indigenous language (Harrison, 2000; Cummins, 2005). It is independent of how the language is spoken and independent of proficiency in the majority language. This mirrors Rothman’s (2007:360) definition: Like all monolingual and childhood bilingual learners, heritage speakers are exposed naturalistically to the heritage language; however, this language is by definition a nonhegemonic minority language within a majority-language environment. Differences in the delineation of who is a heritage language speaker have considerable ramifications on data samples and thus on resulting conclusions, as several reviewers note. The variationist approach foregrounds the search for (inter- and intra-speaker) variation as evidence of linguistic change. Thus, the exclusion of speakers based on comparison to any standard or other group risks excluding innovative speakers showing exactly the type of data that is the target of sociolinguistic investigations of language change. It remains to be shown whether differences in speaker selection methods account for any or all of the differences in outcomes reported. 1.1. Previous analysis of null subjects Both experimental and variationist approaches have been applied to studies of subject pronoun variation, the systematic alternation between overt and null subject pronouns in finite clauses, in heritage language speakers. This

1 This method of defining heritage languages is critiqued in Putnam and Sánchez (2013), due to inadequacy of the concepts of incomplete acquisition and attrition, as a helpful reviewer noted.

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paper reports a comparative variationist study of null subject variation in three heritage languages. Its finding of very similar performance between groups of heritage and non-heritage speakers contrasts with previous experimental studies of the same variable, but coincides with reports in the variationist paradigm. As both approaches offer valuable insight, it is important that researchers in the field be aware of the differences in assumptions and methods. This choice of variables is not accidental: null subjects have long been at the forefront of linguistic theorizing and experimentation. Null subjects were one of the first patterns examined in generative language acquisition research (cf. Hyams and Wexler, 1993 for first language (L1) acquisition; White, 1985, 1986 for second language (L2) acquisition). In psycholinguistics, consistent generalizations have emerged from experimental paradigms showing that heritage language speakers treat null subjects differently than monolingual L1 and L2 learners (cf. Benmamoun et al., 2010; Montrul, 2008; Polinsky, 1997, 2006; Polinsky and Kagan, 2007; Sorace, 2004, 2011; Sorace and Serratrice, 2009). In sociolinguistics there is also a rich history of work on null subjects showing that monolingual, multilingual and heritage language speakers all exhibit systematic patterns of variation (cf. Bayley and Pease-Alvarez, 1997; Flores-Ferrán, 2004; Harvie, 1998; Heap and Nagy, 1998; Otheguy et al., 2007; Paredes Silva, 1993; Raña Risso, 2010; Silva-Corvalán, 1994; Torres Cacoullos and Travis, 2010). The works cited here are studies of Spanish with the exception of Harvie (1998) which examined English and Heap and Nagy’s (1998) study of Faetar. While both approaches have generated a wealth of data, their findings do not converge. Much of the research in the Experimental Approach has concluded that heritage language speakers, after periods of time isolated from their mother tongue community, do not perform identically to monolingual speakers of the mother tongue variety (cf. Benmamoun et al., 2010; Montrul, 2008, 2009; Polinsky, 1997, 2006, 2008; Polinsky and Kagan, 2007). These findings are often attributed to attrition and/or incomplete acquisition. The emerging picture in the Comparative Variationist field is quite different. Many sociolinguistic studies have been conducted of Spanish in contact with English in the United States. Most have not shown evidence of contact effects on the rate of null subjects (Bayley and Pease-Alvarez, 1996, 1997:364; Flores-Ferrán, 2004:50 and references therein; SilvaCorvalán, 1994; Torres Cacoullos and Travis, 2011:241; Travis, 2007:129). Two exceptions are Lapidus and Otheguy (2005), who show a correlation between null subject rate and length of time lived in New York City and Otheguy et al. (2007), who establish a correlation between rate of null subjects and immigrant generation. It is of note that neither of these studies supports their finding with a multivariate analysis that rules out the possibility that the effect is indirect -- i.e., the later generation may simply produce more tokens in contexts that favor overt subjects. The many variationist studies of Spanish in contact with English have failed to find contact effects on internal factors that condition the alternation between null and overt pronoun subjects (Bayley and Pease-Alvarez, 1996; Flores-Ferrán, 2004:64--65; Silva-Corvalán, 1994 (with one exceptional factor); Travis, 2007:114--116). In a similar vein, reports by Nagy et al. (2011), Hollett (2010) and Rumpf and DiVenanzio (2012), show that Heritage and monolingual speakers may exhibit the same patterns of usage -- no significant differences in the variable use of subject pronouns are evident in the conversational speech of first generation speakers (who immigrated from the Homeland as adults) as compared to second and third generation speakers (children and grandchildren of immigrants). Furthermore, by investigating monolingual homeland Russian speakers via the same methods, a difference between older and younger speakers was discovered (Pustovalova, unpublished ms.). This age effect is replicated in the Heritage data. Section 4.3 discusses these results in light of claims of incomplete acquisition and attrition. It is worth noting that acquisition studies using spontaneous speech, rather than an experimental paradigm, may also not produce evidence of contact effects. One such example is Liceras et al.’s (2012:89) study of bilingual (English-Spanish) twins growing up in Spain: ‘‘the production of overt subjects in Spanish by our bilingual twins does not provide evidence that there is influence from English.’’ 1.2. Previous analysis of Voice Onset Time Differences in outcomes according to method are not limited to the morphosyntactic null subject pattern. Voice Onset Time (VOT) is a continuous phonetic variable. VOT is the duration of the interval between the release of a stop and the onset of vocal fold vibration of the following vowel. Because this acoustic correlate of voicing varies considerably across languages (Lisker and Abramson, 1964), it has been much studied in language contact settings. English has long-lag voiceless stops, with VOT generally longer than 30 ms (60, 70, and 80 ms for /p, t, k/ respectively, Lisker and Abramson, 1964). These norms differ significantly from those of the homeland varieties of the three heritage languages examined here. Italian and Russian have short-lag voiceless stops: their mean VOT is less than 30 ms (Ringen and Kulikov, 2012; Sorianello, 1996).2

2

I am not aware of any published analysis of homeland Ukrainian VOT, but it is anticipated to be similar to Russian.

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In many experimental studies of VOT, an effect of language contact is found (cf. Antoniou et al., 2010; Caramazza and Yeni-Komshian, 1974; Chang, 2012; Flege, 1995; Fowler et al., 2008). Not all experimental research has arrived at this conclusion, however. For example, Magloire and Green (1999:175) found ‘‘little difference in the mean VOT values between the [early Spanish-English] bilinguals and the monolinguals [in both Spanish and English]’’ in a sample of university students. Knightly et al. (2003) report that heritage language speakers produce VOTs much like monolingual Mandarin speakers. Section 4.5 interprets the VOT results reported in Hrycyna et al. (2011) and Nagy and Kochetov (2013). This variable exhibits some effects that could be interpreted as resulting from incomplete acquisition or attrition, unlike the null subject variable, for two of the three languages examined. However, when patterns of language use, preference, and attitudes are considered, such interpretations are not supported even for those two languages. 2. The Heritage Language Variation and Change project: a comparative variationist model The Heritage Language Variation and Change project (Nagy, 2009, 2011) extends variationist methods that have more often been applied to better-documented languages into the heritage language domain. The project’s long-range goals are to address the following questions via multivariate analysis of conversational speech elicited from heritage language speakers in naturalistic contexts:  Are cross-linguistic generalizations possible about the types of features, structures, rules or constraints that are transferred earlier and more often? If so, what are they? Which ambient language(s) are they transferred from?  How are social factors relevant? Which ones?  Do the same (types of) speakers lead changes in both/all their languages? Or do speakers choose to use one language or the other for this social ‘‘work’’ (i.e., are the same factors relevant in majority and minority languages)? The project is a collaboration designed to develop a multilingual corpus for inter-generational, cross-linguistic, and diatopic (heritage vs. homeland varieties) comparisons. The research discussed in this paper comes from early stages of analysis, conducted while the corpus is still in development. When complete, the corpus will contain conversational data from 40 speakers, spanning three generations since immigration, of each of these heritage languages: Cantonese, Faetar, Korean, Italian, Russian, Ukrainian. To date, more than 200 speakers have been recorded and transcribed. The project adopts the methodology of Hoffman and Walker’s (2010) Contact in the City project, which examines English spoken in Toronto’s ethnic communities. We can thus compare parallel analyses of English as well as Heritage and Homeland varieties in order to avoid making unwarranted assumptions about input varieties. Where possible, the HLVC project examines patterns in both the Heritage and Homeland varieties with the same methods.3 Our comparisons are designed to elucidate generalizations about the types of variable features, structures or rules that are borrowed earlier and more often in contact contexts, using a consistent methodology across studies of different languages and variables. This interest in the possibility of variation and change within the system, as opposed to ‘‘error’’ at the level of the individual, parallels Pires (2011:116), who explores the potential divergences between the linguistic competence of bilingual and monolingual speakers under a different light, by making the direct argument that, at least in a subset of cases of child (heritage) bilingual acquisition, this divergence can be formally analyzed as a process of language change, differently from the perspective that is adopted in some of the recent literature on bilingual heritage language acquisition. The HLVC project investigates how social factors (language use, ethnic identity, and linguistic attitudes at the individual level, and demographics at the community level) relate to language variation and change. Our goal is to describe the empirically observed linguistic systems of heritage languages. Toronto is an ideal location for this type of research as it has many neighborhoods in which a particular heritage language is strongly represented. In 2011, Italian and Cantonese each represented the mother tongue of slightly more than three percent of the city’s population of 5.5 million people. These communities contrast in terms of their demographics in several ways: how long the group and their language has been in Toronto, how large the community is (in terms of mother tongue speakers and in terms of ethnic group membership), and how much of the community maintains the heritage language as a mother tongue. We expect analysis of these differences to enhance our understanding of the factors that contribute to different types of language contact effects. Demographic features of the heritage language communities in the HLVC project are given in Table 1.

3 Reports of work using the variationist approach are not available for all relevant Homeland varieties for either of these variables. Reports with the best-matching methodology available are used as sources of comparison.

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Table 1 Demographic profile of the HLVC heritage languages (in Toronto).a Language

Place of origin of participants (or their ancestors)

# mother tongue speakers

Cantonese Faetar Italian Korean Russian Ukrainian

Hong Kong Faeto, Celle Calabria Seoul St. Petersburg and Moscow Lviv

170,000+ <100? 166,000 51,000 78,000 26,000

< = < =  <

Ethnic population

Date established

537,000 <300? 466,000 55,000 59,000 122,000

1951 1950 1908 1967 1916 1913

Mother tongue figures are from Statistics Canada (2012). Mother tongue is defined by Statistics Canada as ‘‘the first language learned at home in childhood and still understood’’ (Statistics Canada, 2007b). By this definition, all speakers in our corpus are mother tongue speakers of their heritage language (a corpus selection criterion). Ethnic population estimates are from Statistics Canada (2007a). Faetar is represented in neither, since it is not a national language; the values given are estimates from community members. The discrepancy between the number of mother tongue speakers and the ethnic population listed for Cantonese arises from the fact that 157,000 speakers report ‘‘Chinese’’ as their mother tongue, an unknown number of whom speak Cantonese. Additionally, there is no ‘‘Cantonese’’ ethnicity option. The Russian ethnic population is smaller than the number of Russian mother tongue speakers due to the presence of non-Russians, primarily immigrants from other former Soviet republics, who are native Russian speakers. We have determined the date of establishment of each community according to the date of founding of the first church in Toronto operating in the relevant language. Further details are available in Nagy (2011). a

In addition to the heritage language speakers, there are nearly three million English (only4) mother tongue speakers in the Greater Toronto Area, constituting 54% of the population (Statistics Canada, 2012). These speakers’ English is represented in Hoffman and Walker’s (2010) Contact in the City Corpus, which also includes samples of the English produced by several of the communities listed in Table 1. Like L1 acquirers, heritage language speakers are exposed to the family language at home. Like in L2 acquisition, input in the family language is variable, at least in quantity, as noted by Putnam and Sánchez (2013:482). The age at which the majority language (English) is introduced to the speaker depends on family composition, linguistic and educational background of the family, time of immigration, and other sociolinguistic circumstances. Many other factors vary across speakers and their effects can be examined in quantitative analysis once sufficient speakers are recruited. Section 3 describes the methods that are feasible (and used) at this point in the project. 3. Methods Because the heritage languages examined here have been the subject of very little description based on empirical data, the methods of the HLVC project seek to describe the varieties and then progress to accounting for particular aspects of variation observed therein. Our multi-pronged efforts to collect and compare data for the heritage languages as well as their input languages (Homeland varieties and the ambient English) necessitate a unified method for examining all varieties. 3.1. Speakers Participants are defined in terms of generation since immigration. In this paper, ‘‘generation’’ reflects the distance between the speaker and their or their ancestors’ immigration from the Homeland to Toronto, it does not reflect age.  First generation speakers lived for at least the first 18 years of their lives in the Homeland. Subsequently, they have lived in Toronto for at least 20 years.  Second generation speakers have parents that qualify as first generation speakers and were born in Toronto or arrived prior to the age of six. (The parents are not necessarily in the study.)  Third generation speakers have parents that qualify as second generation speakers and were born in Toronto. For the second and third generation heritage language speakers, English may have been acquired simultaneously with the family language (simultaneous bilingualism) or later (sequential bilingualism). Within each generation, the HLVC Corpus strives for a sample stratified by age and balanced for sex. All participants consent to spend about an hour speaking in their heritage language with an HLVC interviewer. We consider this as evidence that they self-identify as

4

An additional 3% report both English and another language as mother tongues.

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proficient heritage language speakers. We avoid proficiency or fluency tests as inclusion/exclusion criteria, because we wish to cast a wide net in order to be able to describe the range of performance of all types of speakers who meet the Canadian government’s definition of a Heritage Speaker. 3.2. Data collection Each participant was invited to ‘‘talk about being Cantonese/Faetar/Italian/Korean/Russian/Ukrainian.’’ If they agreed, they were digitally recorded by the interviewer(s), university-student age fellow speakers of their heritage language and often members of the participants’ social network. To the extent possible, the same pair of interviewers interviewed all speakers of one heritage language. The primary content of each recording is a guided conversation where a range of topics are explored by means of question modules designed to quickly determine topics of interest to each participant (Labov, 1984; available on the HLVC website, Nagy, 2009). Relaxed interactions are sought and participants are encouraged to produce narratives as well as other genres of speech. Time-aligned transcriptions of these recordings were produced by native-speaker research assistants using ELAN software (http://tla.mpi.nl/tools/tla-tools/elan, Wittenburg et al., 2006). Information about exposure to the heritage language and to English, language usage patterns, attitudes toward the heritage language and to English, and their related cultures, was captured through an orally administered Ethnic Orientation Questionnaire. Our 37-part questionnaire is adapted from Keefe and Padilla’s (1987) study of Chicano ethnicity in the United States. It was designed to determine fairly precise ways of measuring cultural knowledge and ethnic identification, which would describe the ethnic population and its internal variation as well as accurately plot changes over time, especially from generation to generation (Keefe and Padilla, 1987:2). For this purpose, they constructed two scales, Cultural Awareness and Ethnic Loyalty. Their investigation was designed to understand: What kinds of variation in these patterns exist within the ethnic population? What factors contribute to the separation or assimilation of Chicanos in American life? Why does ethnic persistence and/or change occur?’’ (Keefe and Padilla, 1987:3) Over a five-year project, Keefe and Padilla winnowed down a much longer questionnaire to its essential components. From that, Hoffman and Walker (2010) extracted a 37-question questionnaire for use in their Contact in the City project. The HLVC Project has adapted this same questionnaire in order to compare results across these two Toronto projects. The one difference is that the HLVC interviewers administer this questionnaire in the heritage language rather than English. The questions relate to aspects of ethnic identity such as language use, make-up of social network, participation in community activities, attitudes toward cultural heritage, and discrimination. These questions are open-ended and reflect the self-reports of the individual speakers. The full text of the questionnaire is posted on the HLVC website (Nagy, 2009). In the studies reported here, in order to include the results of the Ethnic Orientation questionnaire in quantitative analysis of the linguistic variables, speakers’ responses to individual questions were assigned a score using a three point scale representing a greater orientation toward the English language and mainstream Canadian culture at one end (0 points) and greater involvement with the heritage language and heritage culture at the other (2 points). In this way, speakers’ responses position them along continua of orientation and practice. If linguistic patterns relate to degree of language usage or exposure, we would expect to find correlations between the linguistic variation and these scores. This method of reducing the open-ended questions to numerical scores was developed after in-depth consideration of the type and range of responses. Responses were grouped by topic: Participant’s Language Use, Family’s Language Use, Ethnic Identity of Participant and Family, Language Preferred for Reading and Writing, Cultural Environment (e.g., Are the participant’s neighbors/co-workers/childhood friends of the same ethnicity?), Cultural Choices (e.g., Does the participant wish to transmit the heritage language to the next generation?), and Experience of Ethnicity-related Discrimination. For the results presented below, each individual’s scores for the questions in each topic were averaged. Other uses of the original verbal answers are anticipated in future work. 3.3. Two dependent variables: Null subjects and VOT Two dependent variables are examined. The first is the presence or absence of subject pronouns in finite clauses. We analyzed data from Heritage Cantonese, Italian and Russian. The description and heritage language analysis presented here is drawn from Nagy et al. (2011). These heritage languages contrast with English in that English is prescriptively a non-pro-drop language: every finite clause requires an overt subject. However, Harvie (1998), Benallick (2010) and Please cite this article in press as: Nagy, N., A sociolinguistic view of null subjects and VOT in Toronto heritage languages. Lingua (2014), http://dx.doi.org/10.1016/j.lingua.2014.04.012

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Table 2 Two independent linguistic factors used to code null subjects, with examples. Factor group and factors (levels) Co-reference Subject has same referent as previous subject Subject has different referent from previous subject Clause type Main Conjoined a

Example from Tagliamonte’s (2003--2006) Toronto English Archive ‘‘It had the old red and gold F-W-Woolworth’s sign right on the corner, Ø [it] had those little creaky wood, hardwood floors.’’ (EXM37A) a ‘‘Ø [we] used to bring a lunch with us, sandwiches and stuff. Ø [I] remember we used to go with Darryl, and Gary, and Jack-G. and all of us.’’ (EXM47A) ‘‘By the time Ø [I] got to England it was getting close to summer.’’ (EXF49A) ‘‘He’sin the army and he goes to England three-or-four times a year.’’ (EXM44A)

Speaker codes that attribute each quote to its speaker are given in parentheses.

Marr (2011) report systematic variation between overt and null subjects in spoken English, at rates of 2--5% null. Cantonese, Italian and Russian allow null subjects at much higher rates,5 making null subjects a ‘‘conflict site’’ (Poplack and Meechan, 1998), that is, a variable in which functional, structural and/or quantitative differences in the grammar of the two languages can be used to detect inter-systemic differences and identify their source. Italian is a prototypical null subject language, allowing null subjects in all persons and numbers. Cantonese is a radical pro-drop language, sometimes defined instead as a topic-drop language. Russian is a partial pro-drop language, allowing null subjects only in certain contexts. Yet they exhibit many similarities in terms of the syntactic, morphological and pragmatic factors that condition their variation. Tokens, or clauses containing the site for the variable, i.e., finite verbs without nominal subjects, were extracted from the interview transcript of each participant. We began extraction at the 15-minute time point of the interview, allowing for a warm-up and relaxation period at the start of the interview. Contexts that are invariant in this corpus (e.g., imperatives and interrogatives, selected other language-specific contexts) were excluded, following standard variationist practice (Otheguy et al., 2007:775). Clauses with nouns as subjects were also excluded. 10--16 speakers were coded for each language, for a total of 6216 tokens. For each of these clauses, the presence or absence of an overt subject pronoun was coded as the dependent variable. The second sociolinguistic variable to be discussed is Voice Onset Time (VOT) in word-initial voiceless stops, drawing on Nagy and Kochetov (2013). We examined Heritage Italian, Russian and Ukrainian. We selected the first 75 word-initial voiceless stops (/p/, /t/, /k/), again starting at the 15-minute time point. To minimize extraneous variability, we restricted our investigation to onsets of stressed syllables with /a/ or /o/ nuclei. With 11--12 speakers per language (34 speakers), this produced 2550 tokens. Each token was segmented and coded in Praat (Boersma and Weenink, 2011). The following vowels’ quality and duration were marked. Unclear tokens were excluded as were repetitions of words beyond their first several occurrences. VOT and nucleus duration measurements were extracted by script. 3.4. Independent variable (predictor) coding The transcribed data were prepared for multivariate analysis by coding each token for the factors predicted to influence the production of the dependent variable. First, for both null subjects and VOT, each token was coded according to heritage language and generation of the speaker who produced it and for that speaker’s Ethnic Orientation scores.6 Second, each token was coded for the aspects of its linguistic context that previous studies have reported to influence that dependent variable. The levels of the independent linguistic factors for null subjects are defined in Tables 2 and 3, and for VOT in Table 4. The different variants of each independent variable are predicted to trigger different rates of overt vs. null subjects or different mean VOTs by context. Comparisons of relative rates per context, as well as the overall rate, calculated by logistic (for binary variables) or linear (for continuous variables) regression analysis, are the foundation of comparative variationist analysis. (For an overview of these methods, see Hay, 2011; Tagliamonte, 2007.)

5 While it would be useful to provide null rates for the non-contact varieties (or source varieties) of the heritage languages we investigate, null rates depend on a number of contextual variables, making cross-study comparison difficult. As rough guidelines, Pustovalova (unpublished ms.) reports overall null rates of 50% for Moscow Russian and Rumpf and DiVenanzio (2012) report 80% null for Southern (but not Calabrian) Italian, both in conversational corpora. We know of no published studies of pro-drop rates in homeland Cantonese. Suffice it to say that pro-drop rates in all languages considered are quite a bit higher than the 2% null rate reported for Anglo Canadian English. 6 Speakers’ age and sex have also been coded and analyzed and are discussed where relevant.

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Table 3 Additional independent linguistic factors coded for null subjects. Factor group

Variants (levels)

Person and Number of subject

Three persons and two numbers were distinguished, (based on context and verb form, in null-subject cases). Subsequently, these six levels were collapsed by person or number, according to their distribution in each language: the analysis presented below includes a division by person only for Cantonese, for number only for Italian, and by number and person for Russian. Common tense/aspect categories for each language were coded. Affirmative vs. negative clauses were coded for Russian. Presence vs. absence of a pre-verbal clitic was coded for Italian.

Tense/Aspect of verb Negation of verb Preverbal direct object

Table 4 Linguistic factors coded for VOT (with sample words for each language). Factor group Italian

Russian

Ukrainian

Place of articulation /p/ /t/ /k/

poco ‘little’ (I3M22B) tanti ‘so many’ (I3F21A) come ‘like’ (I3F21A)

пaрZ ‘pairs’ (R2F17A) тожe ‘also’ (R2F17A) кaк ‘because’ (R2M56B)

пaрa ‘pair’ (U3M24A) тaк ‘yes’ (U1F85A) кaжут’ ‘saying’ (U3M24A)

Following vowel /a/ /o/

tanti ‘so many’ (I3F21A) poco ‘little’ (I3M22B)

пaрZ ‘pairs’ (R2F17A) тожe ‘also’ (R2F17A)

пaрa ‘pair’ (U3M24A) потiм ‘later’ (U2F54A)

Table 2 provides examples of co-referential and non-coreferential subjects, and of main and conjoined clauses. These independent variables were used to code the three heritage languages, as well as a small sample of Toronto English. For ease of exposition, examples from English are used. In these examples, the token under consideration is bolded. The previous subject relevant for co-reference is underlined. For null subjects, the assumed interpretation follows in square brackets. Coding choices (levels), rather than examples, are provided in Table 3 for the more straightforward factors. The variants for these differed slightly across languages, as noted in the table. Specific levels for each language are listed in Table 5. Motivation, references and further description of these factors may be found in Nagy et al. (2011). The first factor listed in Table 2, co-reference, also referred to as Subject Continuity or Switch Reference, appears to have a universal effect: speakers produce more overt subject pronouns when they introduce a subject that differs from the subject of the preceding clause, and fewer when a subject has the same referent as the previous subject in virtually every null-subject study, regardless of language (cf. Travis, 2007:107). Controlling for this effect is thus key in order to discover what language-specific factors may also be influencing the choice between null and overt subject. The other factors exhibit different effects across languages and between English and the heritage languages, making them useful for considering the influence of English as a possible source of any observed variation. They are included in this analysis both to control for their conditioning effects and to allow for comparison of the potential influence from English across groups of speakers. Multivariate analysis, or simultaneous consideration of all factors hypothesized to condition the dependent variable, prevents us from mistakenly attributing a high (or low) rate of null subjects to a particular group of speakers, e.g., a particular generation, when, in fact, that rate occurs only because that group had a larger proportion of tokens in contexts that favor null subjects, such as subjects with the same referent as the previous subject. Table 4 indicates the smaller set of linguistic factors coded for VOT: given the greater frequency of voiceless stops, we are better able to control the contexts of extraction. The literature reveals other conditioning factors that might influence VOT: speech rate (de Jong, 2003), word length (number of syllables) and word frequency (Bybee, 2012) and preceding segment. These factors were explored in Blamire, Clare and Patience’s (unpublished results) extension of the Nagy and Kochetov (2013) study. They re-analyzed the same data but no significant effects emerged for these factors. 3.5. Analysis methods Once all tokens were coded for the dependent and independent variables, multivariate regression analyses were conducted. For null subjects, Mixed Effects Modeling was used with model comparisons determining which fixed effects (the linguistic factors listed in Tables 2 and 3, and the social factor of generation) significantly predicted the presence vs. absence of a null subject. A random effect for speaker was included so that any member of a particular generational group whose performance is dissimilar from her/his peers will not skew the distribution. Logistic models were produced using the Please cite this article in press as: Nagy, N., A sociolinguistic view of null subjects and VOT in Toronto heritage languages. Lingua (2014), http://dx.doi.org/10.1016/j.lingua.2014.04.012

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lme4 package in R (R Core Team). Comparisons to determine the optimal model were made using the Akaike Information Criterion (AIC). Following reporting practices in variationist sociolinguistics, outcomes of the logistic models are reported in terms of factor weights (Hay, 2011:207). Factor weights range from 0 to 1: the higher the value, the more that context favors the application value (here, null, rather than overt, subjects). A fixed effect of generation was included in the model. This was used to determine whether the overall likelihood of null subject realization differed across generations. Interaction terms, crossing the main effect of generation with each linguistic factor, were tested to search for changes in the conditioning factors across generation. This method compares rates across all cross-products of the conditions (independent variables). It, therefore, does not rely on a balanced sample, but rather provides results of greater significance for categories with more tokens, all else being equal. Because the null subject analysis focuses on a binary variable and has many conditioning factors, while VOT is a continuous variable conditioned by fewer factors, different analysis techniques are used. For the VOT study, I draw on an ANOVA analysis that examined main effects of generation, place of articulation, and following vowel, published previously (Nagy and Kochetov, 2013).7 Ratios of duration of the consonant to its following vowel were examined to rule out a possible effect of speech rate on duration measurements. Finally, correlations of the two dependent variables to Ethnic Orientation scores were conducted. To reduce the information provided from 37 Ethnic Orientation questions, scores were averaged across groups of questions to provide a score for each individual for each group of Ethnic Orientation questions (see section 3.2). Spearman’s rho was calculated for the correlation between an individual’s average score for each topic and the rate of null subjects, realized as the random effect calculated for the individual in the Mixed Effects Models discussed above. This was done using the 23 participants who responded to at least two-thirds of the Ethnic Orientation Questionnaire and were analyzed for null subjects. A similar approach was used to compare mean VOT to Ethnic Orientation scores. In addition to reporting the (complete lack of) correlation between the Ethnic Orientation scores and sociolinguistic variable measures, Tables 6 and 8 (below) also indicate the (low) degree of correlation among the different Ethnic Orientation scores. These latter calculations were conducted over all HLVC participants who responded to at least twothirds of the Ethnic Orientation questions, as part of an exercise to better understand how the questions might be related to each other. See Nagy et al. (2013) for details. 4. Results 4.1. Null subjects results Analyses of the proportion of null (vs. overt) subject pronouns for first vs. second/third generation speakers of Heritage Cantonese, Italian and Russian show little inter-generational difference, see Fig. 1. Second and third generation speakers [(Fig._1)TD$IG]

Fig. 1. Percent of tokens with null subjects across languages and generations (total N = 6216: English = 400, Russian = 3171, Cantonese = 1600, Italian = 1147; reproduced from Nagy et al., 2011). Error bars represent 95% confidence limits.

7

Analysis using Mixed Effects models appears in Nagy et al. (2013). These models incorporate the Ethnic Orientation information.

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are collapsed because, while the corpus is still under construction, there are not enough speakers to represent either generation alone. This makes the second/third generation sample size comparable to the first generation. Fig. 1 shows an inter-generational difference between the percentage of subjects that are null for Cantonese, though not for the other languages. This inter-generational difference exists when raw percentages of null subjects are compared. However, no inter-generational differences emerge in the multivariate analysis presented below (see Table 5), where the differing distributions by context are taken into account. That is, the difference in raw percentage rates is due to an unbalanced number of tokens across certain linguistic contexts that favor or disfavor null subjects. Specifically, the first generation of Cantonese speakers produced more tokens in contexts favoring null subjects, inflating their raw rate of null subjects. Comparing across identical linguistic contexts, we do not find inter-generational differences in the rate of null subjects. We next consider the possibility that, while maintaining constant overall rates of null subject use, the grammar, or set of factors conditioning the rate of null subjects in different grammatical contexts, may be undergoing change. This could be reflected three ways: in different sets of significant conditioning factors for different generations of speakers, different rankings (for degree of favoring null subject pronouns) for the different contexts (levels) of a conditioning factor, or different rankings (by effect size or range) of the conditioning factors. Multivariate regression analyses, based on 6216 tokens, again contrasting generations of speakers, show cross-generational stability, overall, both in rates of pronoun use and in most linguistic factors constraining the variation. The later generations of speakers do not diverge from the immigrant generation. Table 5 presents the results of a mixed-effects logistic regression model for each heritage language. In these models, Individual was included as a random intercept and was found significant for all three heritage languages. Factor weights for all significant linguistic factors are given. Higher factor weights indicate a higher probability of a null subject in that context. Non-significant factors are listed. The right-most column indicates the number of tokens that were extracted from the conversational transcriptions for each category (level). Generation is never selected as a significant main effect: the different generations do not differ in their overall rate of null subjects, once other conditioning factors are taken into account. For Cantonese and Italian, no interaction terms that cross generation with a linguistic main effect were selected: there is no difference between the first generation and later generation speakers with respect to the conditioning constraints. In Russian, however, there are two cross-generational differences. We see a significant interaction between generation and negation and between generation and grammatical person. Negated sentences favor null subjects for second-generation speakers, while affirmative sentences disfavor them. In the first generation, no effect is found. For person, the hierarchy of constraints is reordered. In the first generation, third person > second > first, while in the second generation, the relative order of favoring null subjects is second > first > third person. As these two factors did not have significant effects in our English sample (Nagy et al., 2011), these generational differences cannot be attributed to influence from English. The few small differences in conditioning factors that emerged between generations within each heritage language do not provide any evidence of English influence nor can they be interpreted as simplification of the system. 4.2. Ethnic Orientation and null subjects While the overall patterns are similar across generations, one might expect certain individuals’ grammars to show evidence of attrition or incomplete acquisition. However, given the range of null subject rates among native speakers (in studies conducted of other languages, cf. references in section 1) and the knowledge that such rates are very sensitive to context, it is inappropriate to simply consider any speaker whose null subject rate appears to be an outlier as non-proficient. Rather, we must look for patterns or trends. It is reasonable to expect that speakers who report using the heritage language less often, or report that their family does so, or report negative attitudes or experiences with the heritage language, be the ones who might undergo attrition or incomplete acquisition. To investigate this possibility, we turn to the Ethnic Orientation correlation results. Table 6 shows that, although there are some significant correlations among the Ethnic Orientation Questionnaire topics (calculated over the HLVC Corpus as a whole), there are no significant correlations between any Ethnic Orientation Questionnaire topic and rate of null subjects (in bold). That is, we do not find evidence of a higher rate of null subject use among speakers with higher (more heritage language/culture oriented) scores for any of these measures. To summarize, the heritage language null subject data provides no sign of evolution in the heritage language grammars related to null subjects: the generations exhibit the same rate of null subjects and, for the most part, the same conditioning factors. They do not show evidence of English influence in any generation, nor do patterns of language use/ exposure correlate to the rates of null subject usage.

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Table 5 Mixed effects models for null-subjects; factor weights for fixed effects (application value is null subjects). Factor weight Heritage Cantonese (N = 1581, input = 0.20) Co-reference Same referent Different referent Range

n

.64 .36 28

966 615

Grammatical person

First Third Second Range

.64 .58 .29 26

1017 434 130

Clause type

Main Conjoined Range

.60 .40 20

1500 81

Non-significant factor groups for Cantonese: generation, generation  co-reference, generation  grammatical person, generation  clause type, tense Heritage Italian (N = 1047, input = 0.90) Co-reference Same referent Different referent Range

.63 .37 26

519 528

Grammatical number

Plural Singular Range

.63 .37 26

351 696

Preverbal direct object

Direct object None Range

.65 .35 30

43 1004

Tense

Past perfect Present Past imperfect Range

.60 .46 .43 17

261 547 239

Non-significant factor groups for Italian: generation, generation  clause type, generation  co-reference, generation  grammatical number, generation  direct object, generation  tense, clause type Heritage Russian (N = 2507, input = 0.31) Co-reference Same referent Different referent Range

.59 .41 18

1014 1493

.63 .37 26

2223 284

Clause type

Main Conjoined Range

Generation  negation

Generation Generation Generation Generation Range

2  negative 2  affirmative 1  negative 1  affirmative

.77 .45 .38 .38 39

220 1205 122 960

Generation  person

Generation Generation Generation Generation Generation Generation Range

2  third 2  second 2  first 1  third 1  second 1  first

.57 .67 .64 .54 .47 .38 29

428 166 831 381 109 592

Non-significant factor groups for Russian: generation  co-reference, generation  clause type, tense

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Table 6 Correlation (Spearman’s rho) of individuals’ null subject rates to measures of Ethnic Orientation. Family language Language use Family language Ethnic identity Read/write Discrimination *

0.60

*

Ethnic identity 0.26 0.23

Read/write 0.45 0.50 0.39

*

Discrimination 0.34 0.31 0.34 0.01

Ø-subject 0.26 0.28 0.26 0.33 S0.17

Significant correlation between Ethnic Orientation measures, in the HLVC Corpus

4.3. A change in progress in Russian? The comparative variationist approach allows for further comparison of the Heritage Russian data to data from Homeland (Moscow) monolingual speakers. In this section, Hollett’s (2010) Heritage Russian study is compared to Pustovalova’s (unpublished) Homeland Russian study, which use methods identical to those presented above. When we contrast the patterns of speakers of different ages and between males and females, an interesting wrinkle emerges, highlighting a contribution of comparative variationist work. The Homeland analysis, based on a sample of nearly 1400 tokens from 14 speakers, showed clear effects of age and sex: younger Russian speakers and males show lower rates of null subjects than older speakers and females. Hollett’s (2010:67--68) logistic regression analysis of the Heritage Russian data also found significant effects for age and sex in Heritage Russian. Their results are compared in Fig. 2. Based on much previous sociolinguistic work, encapsulated in Labov’s (1990) findings that females often lead in ongoing change, these age and sex differences might be interpreted as evidence of a change in progress: younger speakers use fewer null subjects than older speakers. However, males use fewer null subjects than females, in the Homeland data where age peers can be compared. If it were not for the clear age trend in the Homeland data, we might be tempted to interpret the lower rate of null subjects in the Heritage data as indicating incomplete acquisition. And we might attribute it to influence from English’s low rate of null subjects. However, comparison to the Homeland data indicates that this interpretation is unwarranted: the Homeland speakers show the same type of age stratification in null subject rates that are emerging in the (admittedly incomplete) Heritage sample. Although this trend must remain speculative at the present stage of our project, it suggests that studies that compare younger Heritage speakers to older monolingual baseline data (either collected earlier in time or collected from older speakers) might erroneously conclude that Heritage speakers are not performing in a native-like way if patterns of age variation, possibly indicative of changes in progress, are not taken into account. While comparable data for variationist analysis is not available for Homeland (Hong Kong) Cantonese or Calabrian Italian, Rumpf and DiVenanzio (2012) reported the overall null subject rate for a different southern Italian variety to be just over 80%. This number is extremely close to the Heritage Italian rate for the Toronto speakers (see Fig. 1), suggesting that here there is no difference between the Homeland and Heritage grammars.

[(Fig._2)TD$IG]

Fig. 2. Null subjects rates by age and sex in Homeland and Heritage Russian.

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Table 7 Average VOT (in ms) by generation for three heritage languages, /p/, t/, and/k/combined, Homeland comparators, and English. Language

Generation 1

Russian Ukrainian Italian

26 26 32

English

Generation 2 <* >*

32 38 27

<*

Generation 3

Homeland

51 43 27

25 19 38 69

St. Petersburg Not available Cosenza dialect Regional Italian Montreal

4.4. Voice Onset Time results Analysis of Voice Onset Time (VOT) for three Toronto heritage languages was reported in Nagy and Kochetov (2013), showing different outcomes for the three languages examined, summarized in Table 7. Significant inter-generational differences are marked by ‘‘*’’. Comparative values for Homeland varieties (Ringen and Kulikov, 2012; Sorianello, 1996) and Montreal English (estimated from Fowler et al., 2008: Fig. 1) are also shown. For Heritage Russian, the first and second generation speakers do not differ significantly from each other and their range of VOTs is well within the range established for Homeland (St. Petersburg) Russian by Ringen and Kulikov (2012). Thus, there is no evidence of attrition in the Generation 1 speakers, who have been separated from their monolingual Homeland environment for at least 20 years. Generation 3 exhibits significantly longer VOTs than the first two generations, drifting toward, but not entering, the range for Canadian (Montreal) English established in Fowler et al. (2008). We lack data for a Homeland Ukrainian comparison. However, Generations 1--3 of Heritage Ukrainian speakers have VOTs in the same range as Russian Generation 1 and 2 speakers. If we assume that Homeland Ukrainian VOT resembles Homeland Russian VOT, then Heritage Ukrainian speakers do not exhibit mean VOTs that fall outside of the Homeland range. Although there is a gradual rise across generations, none reach English norms. With Heritage Italian speakers, a different picture emerges. All three generations produce VOTs near the range established for Calabrian Italian by Sorianello (1996) and none approach the English range. Interestingly, Generation 1 has the longest mean VOT, significantly longer (more English-like) than the later generations. 4.5. Ethnic Orientation and VOT One might interpret the Heritage Russian and Ukrainian VOT patterns as suggesting incomplete acquisition of Homeland patterns in the later generations, and, likewise, the slightly more English-like pattern of the Generation 1 Italians as evidence of attrition. But it is equally possible to see these as language-internal variation, particularly given the inconsistency across languages. We can better discriminate the two possibilities by again turning to the social variables related to Ethnic Orientation. Strong correlation of VOT and the Ethnic Orientation Questionnaire measures which reflect the amount of contact and/or use of English vs. the heritage language could provide support for interpretations involving incomplete acquisition or attrition. Speakers with lower exposure to or use of the heritage language, or more negative attitudes toward the heritage language or culture, might be expected to exhibit less Homeland-like patterns. However, as we saw above for null subjects (Table 6), there are again virtually no significant correlations between Ethnic Orientation scores and VOT. For the comparison of VOT and Ethnic Orientation scores, we used slightly different sets of Ethnic Orientation questions than those discussed above for null subjects.8 Ethnic Identity, Language Choice and Discrimination are as in Table 6; Cultural Environment reflects a shared ethnicity with friends, neighbors, co-workers and schoolmates; Language Use reflects language preferences for speaking, reading and writing, and media; and Cultural Choice reflects whether the participant wishes to maintain their Heritage Culture in the community. These correlations, in bold in Table 8, are for the sixteen speakers for whom VOT data and responses to at least two-thirds of the Ethnic Orientation Questionnaire are available. Other means of interpreting the Ethnic Orientation Questionnaire scores and their relationship to linguistic variation are explored in Nagy et al. (2013), but none are more revealing of evidence to support attrition or incomplete acquisition.

8 The different question sets were necessitated by inadequate response rates to different questions between the participants in the null subject study and those in the VOT study.

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Table 8 Correlation (Spearman’s rho) of individuals’ VOT rates to measures of Ethnic Orientation.

Ethnic identity Language choice Cultural environment Language use Cultural choice Discrimination *

Language choice

Cultural environment

Language use

Cultural choices

0.23

0.10 0.81 *

0.30 0.21 0.25

0.29 0.20 0.12 0.10

Discrimination 0.01 0.11 0.17 0.02 0.09

VOT S0.35 0.22 0.36 0.08 0.27 0.07

Significant correlation between Ethnic Orientation measures, for the HLVC Corpus.

5. Discussion In bilingual acquisition, both languages may be acquired differently than their monolingual counterparts (Meisel, 2009, 2011). Such acquisition has been proposed to lead to a different grammar than that of a monolingual. This situation is commonly reported in the Experimental literature on heritage languages. In contrast, we have seen that the application of the Comparative Variationist approach to null subjects provides no indication of differences between monolingual and multilingual speakers on the individual level: speakers who long ago moved away from the Homeland have the same pattern of null subject use as speakers in the Homeland, including, in one language, the social variation indicative of a change in progress. We also find no sign of attrition on the community level for null subjects: first generation (immigrant) heritage language speakers exhibit the same performance as second and third generation heritage language speakers in all languages.9 While these findings are based on relatively small numbers of speakers, the sample size is large enough to provide statistically robust results. These trends are replicated in work on Mandarin speakers in the USA (Acrisio Pires, personal communication), Heritage Italian speakers in Germany (Rumpf and DiVenanzio, 2012), and the many studies of Heritage Spanish in the US, discussed in section 1.1. The same stable situation emerges from Comparative Variationist analysis of Italian for VOT. Heritage Italian speakers of three generations produce VOTs similar to those established for Homeland Calabrian Italian. For these speakers, there is no drift toward English-like patterns. In contrast, the later generations of Russian and Ukrainian speakers do exhibit increased VOT from one generation to the next. Of all the data explored in this paper, only this very last pattern might be interpreted as evidence of incomplete acquisition. However, it may also be interpreted as internal change, a feature common to all languages and regularly attributed as a cause of variation among monolingual speakers (cf. Pires, 2011). In contrast, conclusions of attrition or incomplete acquisition would need support from evidence that individuals with less exposure to the heritage language have less Homeland-like production patterns. Such trends are not evident in these data (section 4.5). The successful inter-generational transmission of the variable grammar that constrains pronoun realization in Heritage Russian, Italian and Cantonese contrasts with the outcomes of studies in the Experimental approach that conclude incomplete acquisition or attrition for null subjects in heritage language speakers (summarized in Benmamoun et al., 2010:34--35). Sections 5.1--5.4 discuss four possible accounts for the differences that emerge from the two approaches. 5.1. Are we too late in Toronto? One possible explanation is that change took place in the Toronto Heritage varieties earlier than can be captured by the first generation recorded in our sample. That is, the parity across our generations exists because they all have an incompletely acquired (or attrited) system. For Heritage Italian and Russian, spoken for over 100 years in Toronto, this is a possibility. For Cantonese, with its more recent establishment as a community in Toronto (see Table 1), it seems less likely. This account, however, is untenable in the instances where we are able to compare Heritage and Homeland performance. We see that the Heritage variety of Russian mirrors much of the pattern of linguistic and social constraints on null subjects in the Homeland variety. The Homeland Italian data provided by Rumpf and DiVenanzio (2012) provides a first indication that we will also find consistency between Homeland and Heritage varieties when we are able to make a comparison to a Calabrian Italian Homeland corpus. We anticipate future work that will allow for comparisons with Homeland Italian and Cantonese. We might equally well ask the reverse: are we too early? Are conditions in Toronto supportive enough of heritage language maintenance that change has not yet occurred in ways that have been documented in other cities? This leads us

9 We leave aside here the minor inter-generational differences in conditioning environments noted above for Russian, as these do not lend themselves to interpretation as English-influenced patterns.

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Table 9 Null subjects per 10,000 words for Toronto English (from Marr, 2011). Ethnic group

Generation 1

Generation 2

Anglo Chinese (Cantonese) Italian (Calabrian)

11 6 13

15 5 11

to now turn from factors that distinguish individuals and toward group-level factors. As noted in section 1, the HLVC project seeks generalizations about what community level factors are relevant in language contact situations. We selected a set of heritage languages that differ along several dimensions, reflected in Table 1. Do these dimensions influence the type of linguistic pattern found in each language? When we consider the length of time that a community has been established in Toronto, Cantonese stands out as about half as old as Italian, Russian and Ukrainian. No sociolinguistic patterns examined so far have singled out Cantonese as different. If we consider the rate of retention of the heritage language (the ratio of mother tongue speakers to ethnic community members), then Ukrainian stands out as lower than the others. Yet, no patterns have singled out Ukrainian as distinctive. Finally, when we consider the size of the community, Italian and Cantonese are the largest, and Russian and Ukrainian are smaller. While we have found no sociolinguistic patterns in which Italian and Cantonese group together, Russian and Ukrainian do behave similarly, and unlike Italian, in terms of how VOT is evolving. Only when we are able to compare many more linguistic variables across all the languages in the HLVC Corpus can we hope to truly understand the effects of these community-level factors. 5.2. Have the Heritage varieties changed Toronto English? A second option to consider is that the English spoken in Toronto’s heritage language communities has itself been influenced by the heritage languages. If the ambient English had taken on the grammar of a heritage language (regarding null subjects), and had much higher rates of null subjects than other varieties of English that have been studied, then it might not create a conflict site. That is, if the ambient English has evolved to have null rates as high as the heritage languages, rather than the 2% null rate reported for a small sample (N = 400) of Anglo Torontonians in Nagy et al. (2011), it would not be in a position to exert a downward influence on the heritage languages’ null subject rates. Marr’s (2011) unpublished MA thesis, using English data from Hoffman and Walker’s (2010) Contact in the City corpus, investigated exactly this. She compared the rate of null subjects in six groups: two generations each for Chinese (speakers or their families from Cantonese-speaking Hong Kong), Italian (speakers or their families from Calabria, Italy), and Anglo (British or Irish ancestry, English mother tongue for at least three generations).10 Null subject rates were estimated for 70 speakers by comparing the number of null subject tokens extracted to the total number of words in the transcript of each speaker’s sociolinguistic interview.11 Measures were normalized to estimate the number of null subjects per 10,000 words for each speaker, which corresponds to roughly an hour of speech. Her findings are in Table 9. (Note: This measure, for the purpose of a quick comparable estimate, is the number of null subjects per 10,000 words. Previous discussions used the percentage of null subjects by clause.) Two sample unequal variance t-tests were performed to test for significant differences in rate of null subjects between groups. There is a significant difference between the Cantonese and the Anglo group ( p < 0.01) and between the Cantonese and the Italian group ( p < 0.01). The Italians and the Anglos do not differ significantly: the ambient English in the Italian community has not been influenced by the much higher rate of null subjects in Italian. While the rate for null subjects in the English in the Cantonese community is significantly different from the Anglo rate, it is, in fact, lower -- it is not reflecting the higher null rate used in Cantonese than monolingual English (Hoffman and Walker, 2010). Marr (2011) also reported logistic regression analyses examining the effects of linguistic and social factors on null subject usage. There are no statistically significant differences across generations within any ethnic group, indicating no ongoing change in English null subject rates in these communities. While the First Generation Cantonese and Italian did differ some from the Anglos (with respect to the conditioning effects of Verb Category and Tense, respectively), their grammar overall resembled that of native English speakers. Furthermore, the Second Generation speakers had all converged on the same grammar as the native English speakers. The lack of evidence of incomplete acquisition or attrition in the Heritage varieties’ null subject systems cannot be attributed to influence in the opposite direction (of the heritage languages on English).

10

The Anglo generations were age-matched to the heritage groups, as immigration status was irrelevant. For 21 of these speakers whose interviews had not yet been transcribed, a word count was conducted on three minutes of speech from about 20 minutes into the interview to estimate the length of the interview in words. 11

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Fig. 3. Language choice, speech rate and generation in HLVC (Brook and Nagy, 2012).

5.3. Do different types of speakers participate in different types of studies? A third possible explanation of the disparity between typical outcomes of Variationist and Experimentalist studies of null subjects is that the types of speakers who volunteer for research projects conducted by Comparative Variationists differ from those in Experimentalist studies. Differences are of at least three types. Experimental studies often focus on children and adolescents in school, so they have a built-in bias for students with recent test-taking experiences. The Variationist studies reported here include speakers ranging in age from 16 to 85 (mean: 48 years). Relatedly, experimental studies often draw participants from (heritage) language classes, while the recruitment methods for this study did not operate through a school (or any single institution), but rather aimed to recruit a broad sample of the community. Some experimental studies define heritage language speakers with reference to their abilities (only non-native-like speakers are classified as heritage language speakers in some studies, cf. Montrul, 2008; Polinsky, 1995, 2011b), while the HLVC project selects and categorizes speakers only with reference to their linguistic autobiography. To bridge this divide, several HLVC reports have been met with requests for additional information about the speakers, particularly some measure of fluency. In response, we consider speech rate, which has been proposed as ‘‘one of the most sensitive measures reflecting the level of proficiency of a heritage speaker’’ (Polinsky, 2008). A pilot investigation suggests that this would not provide much additional differentiation of speakers in our study: Language Choice Scores (part of the Ethnic Orientation Questionnaire) are well correlated to speech rate (Pearson’s r = 0.62, p = 0.03) and both of these measures clearly reflect generational differences. This is illustrated, for a sample of eight Italian and four Russian speakers, in Fig. 3 from Brook and Nagy (2012). People who claim a strong preference for speaking the heritage language (vs. the majority language) speak more quickly and tend to be of the first generation, while speakers with a preference for speaking English speak their heritage language more slowly, and are not in the first generation. Tables 6 and 8 indicate that Ethnic Orientation scores do not correlate to the linguistic variables (null subject, VOT), making it unlikely that speech rate, which is closely correlated to the Ethnic Orientation scores, would correlate. 5.4. Do different methods produce different outcomes? Experimental tasks target exactly the contexts where differential performance is anticipated. Data collected by experimental tasks such as grammaticality judgments, picture manipulation, and controlled elicitation can be contrasted with data collected via naturalistic conversational recordings. These data types differ along several axes. In the following list, the prevailing Experimental tendency is listed first and the Comparative Variationist tendency is second. a. unfamiliar tasks vs. typical everyday conversational behavior b. comprehension/judgment/manipulation tasks vs. open-ended conversation c. researchers who ‘‘test’’ the speakers are not often reported to be Heritage-Language speaking community members vs. interactions among speakers with the same native (Heritage) variety and from the same community d. associations of ‘‘test-taking’’ and ‘‘right or wrong’’ answers to the university lab or classroom setting where much experimental data is collected vs. conversation with communicative intent, in a familiar setting, with interviewers making efforts to create a casual social setting. Benmamoun et al. (2010:25) note that, typically, participants in the Please cite this article in press as: Nagy, N., A sociolinguistic view of null subjects and VOT in Toronto heritage languages. Lingua (2014), http://dx.doi.org/10.1016/j.lingua.2014.04.012

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experimental approach are ‘‘undergraduates who have been trained to take various tests and make choices, and thus their responses might be colored by this training.’’ e. requirement to choose a single answer, structure or form vs. options to avoid a particular structure by circumlocution or changing the conversational topic. Any or all of these differences might account for the differences in outcomes. Until we conduct research using both methods on the same speakers, this possibility remains. 6. Where we are and where to go next The investigation of conversational speech of Toronto speakers of Heritage Cantonese, Italian, Russian and Ukrainian has yielded data indicating that different generations of Heritage speakers may differ little from each other nor, when comparison is feasible, from monolingual Homeland speakers. This is the case for the null subject variation analyzed in all three languages and for at least the Italian VOT data. Even in cases of inter-generational VOT differences that might suggest more English influence in later generations of speakers, strong support is lacking: correlation is not found between linguistic performance and measures of reported language exposure, use or preference. This finding converges with other variationist analyses of heritage language (primarily Spanish) null subject variation, discussed in section 1.1. To try to make sense of these findings, which differ from many Experimental reports of the same dependent variables, methodological differences have been considered. Such differences, whether circumstantial or by design, may have important ramifications. The extent to which any of these methodological differences account for the discrepancies in outcomes in the two fields has not yet been empirically verified. It remains to be seen whether Experimental and Comparative Variationist approaches, with their different methods for selecting participants, collecting and analyzing data, will reach the same outcomes if they examine the same pool of speakers. We are not yet in a position to clearly determine whether it is the choice of participants or the methodology more broadly that accounts for these differences. The different patterns found for different heritage languages and between the null subject and VOT linguistic variables underscore the importance of examining multiple variables in multiple languages, and examining multiple facets of multilinguals’ performance before drawing conclusions about what constitutes the performance of a heritage language speaker. This includes both examining different parts of the grammar and different language tasks. The papers in this issue make an important step in this direction. 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