The Uniformity of the Matrix Language in Classic Code-switching

1. The Uniformity of the Matrix Language in Classic Code-switching Alberto Rosignoli ESRC Centre for Research on Bilingualism Seminar Series Bangor 6th April 2009

2. A definition CODE-SWITCHING • The alternation of two languages within a single discourse, sentence or costituent (Poplack 1980, 2000)

3. The concept of Asymmetry • The languages involved in CS do not contribute equally to form bilingual utterances. • The language source of different types of morphemes is constrained. • ! Not a universal feature of CS theories.

4. Early work: Joshi 1985 • “Despite extensive intrasentential switching speakers and hearers usually agree on which language the mixed sentence is “coming from”. • Matrix Language vs Embedded Language Existence of a control structure which allows shift from the ML to the EL . • Nonswitchability of closed-class items.

5. The Matrix Language Frame Model • Myers-Scotton (1993, 1997, 2002) • Framework for the analysis of intrasentential CS • A model of bilingual production • Based on Levelt’s 1989 Speaking Model

6. Asymmetry in the MLF Asymmetry in the degree of participation of the languages involved Matrix Language (ML) Embedded Language (EL) Asymmetry in the retrieval procedures of morphemes Content morphemes System morphemes

7. 4-M Model

8. The MLF Unit of Analysis • In 1993: the discourse as a whole • After 1997: rejection of the discourse in favour of the CP (projection of complementiser) ≅clause

9. The Matrix Language Principle There is always an analyzable or resolvable frame structuring the morphosyntax of any CP. This frame is called the Matrix Language. In bilingual speech, the participating languages never participate equally as the source of the Matrix Language. (Myers-Scotton, 2002: 8)

10. Classic CS • In Classic CS only one of the participating languages is the source of the abstract morpho-syntactic frame of the bilingual CP. • In other types of CS, both languages may contribute abstract structure. Ex. Mi oedddrwsnesapoblyngwneudsloe gin PRT be.3s.past door next people PRT do.nonfin sloe gin ‘The next-door people made sloe gin’ (Deuchar and Davies, 2009)

11. Identifying the ML: criteria Morpheme Order Criterion In Matrix Language + Embedded Language constituents consisting of singly occurring Embedded Language lexemes and any number of Matrix Language morphemes, surface morpheme order (reflecting surface syntactic relations) will be that of the Matrix Language. (Myers-Scotton, 1993a: 83; 2002: 59) Extiangenwneudfath-a rhedeg exercise you need.NONFINdo.NONFIN like run.NONFIN exercise “You need to do, like, running exercise” (Deuchar, 2006)

12. Identifying the ML: criteria • System Morpheme Criterion • In Matrix Language + Embedded Language constituents, all system morphemes which have grammatical relations external to their head constituent […] will come from the Matrix Language. • (Myers-Scotton, 1993a:83; 2002: 59) • Ex He sells me their prenotazioni for their seats but not my ticket. • reservations

13. A Critique of the MLF (MacSwan 2000, 2005a, b) “Nothing constrains code switching apart from the requirements of the mixed grammars.” • CS is the union of two lexicons • No constraints specific to bilingual speech (no ML). • Grammaticality of mixed utterances can be ascertained through checking of features.

14. Feature-checking • The case of Spanish-English DPs (Moro 2001) • D, phi = {person, number, gender} N, phi ={person, number, gender} la casa • D, phi = {person, number} N, phi ={person, number} the house • D, phi = {person, number, gender} N, phi ={person, number} la house • D, phi = {person, number} N, phi ={person, number, gender} * the casa

15. A comparison Matrix Language Frame Minimalist Program • Asymmetry between participating languages. • In bilingual CPs where Spanish is the ML DETs will come from Spanish. • English DETs will occur in bilingual DPs where English is the ML. • No asymmetry between participating languages. • In bilingual CPs DETs will always come from Spanish (see feature mismatch). • English DETs will not occur in bilingual DPs.

16. Feature checking cont. • The non-occurrence of NPs of the type the casa in available data could be due to factors other than feature mismatch. • The argument relies partially on grammaticality judgments by simultaneous bilinguals.

17. A MLF case study: Smith 2006 • Spanish-English community in the US • 56 speakers (10-20 mins per conversation) • ‘The asymmetry between the ML and the EL in a single utterance is replicated in the speech of an entire community in which the community ML is […] Spanish and the community EL is English.’

18. Results

19. E> Sinsert • maestro y a ónde vamos a ir al swimmin’ onde onde? teacher and to where go.1.pl.pres to go to+the swimming where where ‘Teacher, and where are we going to go swimming where where?’ S> Einsert • I don’t want those (NO’S?/NOSE?)* comothree horns ‘I don’t want those (no’s?/nose?) like three horns’

20. The ML as a dynamic construct Because the ML is defined at the level of the CP, it is assumed that the language providing the source of the ML could change (as an extreme case) even within the same sentence, from one CP to the following. This, however, rarely seems to be the case in the available data Myers-Scotton 1993 (Swahili-English) Finlayson et al 1998 (Zulu-Sotho-English) Boussofara Omar 2003 (Standard/Tunisian Arabic) Owens 2005 (Standard/Nigerian Arabic-Hausa-English) Smith 2006 (Spanish-English) Deuchar 2006 (Welsh-English)

21. Extended use of the ML Myers-Scotton (2002) “ML of the discourse” Smith (2006) “Community ML” ML is the same for every CP ML changesateverysuccessiveCP Not accounted for in the MLF Most data show far less variability as regards the source of the ML than the model allows.

22. Problems with the MLF The ML as a dynamic construct The CP as the unit of analysis Analysis of well-formed CPs !Uniformity of the ML !ML beyond the CP !Naturalistic data

23. A shift of perspective? • Uniformity in ML assignment in bilingual CPs is the factor that justifies the extended use of the ML construct. • Rather than imprecise applications, these uses are capturing a generalisation that the model does not explain. • Motivation is normally found within a sociolinguistic framework (e.g. ‘Markedness’)

24. CS studies on a continuum Micro-level (syntax) Macro-level (sociolinguistics) Conversational structure?

25. A conversation analysis perspective • Interest in the issue of the ‘base language of the conversation • Part of the overall organisationof the discourse • Different coverage of naturalistic data • No well-formedness requirements • Problematising the notion of ‘code’ in language alternation • What counts as a ‘code’ for participants?

26. A typology of code-alternation (Auer) Change of the base language

27. *SAR: vabbé no ioè un po’ che non vado al cinema . (well no I haven’t been to the cinema in a while) *ANT: hmm@ 0 [>] . *SAR: però [<] # come sai non ho tempo &=sigh di fare niente xxx [>] . (but as you know I haven’t got time to do anything) *ANT: <come vailphd> [<] ? (how’s the PhD going?) gonna [: going to] go finish it ? *SAR: ah PhD eh ho avuto un momentobrutto # mercoledì [>] . (ah PhD I had a bad moment on Wednesday) *ANT: perché [<] ? (why?) *SAR: perché: Laura Layton era incazzata con tuttimercoledì . (because Laura Layton was pissed off with everyone on Wednesday) &e: hmm &e: stava per scoppiare. (hmm uuh and she was about to burst)

28. infatti ieri ho parlato con altra gente mi fan+"/. (actually yesterday I spoke to some others and they were like) +"/ è arrivata a un punto che neanche lei non ne può più . (she’s come to the stage where she herself can’t take it anymore) *ANT: in che senso [>] ? (how do you mean?) *SAR: perché ha le sue deadline per <la fine del> [<] mese . (because she’s got her own deadlines at the end of the month) *ANT: hmm . *SAR: e: ha tutti (que)sti studenti # ehm dieci st(udenti) [//] dieci PhD students # e: [>1] . (and she has all these students ehm ten st(udents) ten PhD students) *ANT: <non ce la fa più> [<1] <anche lei> [>2] . (she too can’t take it anymore) *SAR: e non ce la fa più perché ognuno ha unproblema . (she can’t take it anymore because everyone has got a problem)

29. *SAR: ealloragli ho dettocheappunto <ho inv(itato)> [//] avevoricevutoquestoinvitoda Catherine . (so I told him right that I inv(ited) that I received this invitation from Catherine) Catherine <era la:> [/] era la supervisordi: ehm Paul [>] . (Catherine was Paul’s supervisor) *ANT: ah [<] sìsì . (ah yes yes) *SAR: hmm. cheabita qua intorno [>] . (who lives around here) *ANT: hmm [<] . *SAR: eallorafa: (so he goes like) +”/ma ha dettoche ha [//] failcompleannoperché ha raggiunto: quell'età in cui c'èzero no . (so she said she’s having her birthday because she got to that age in which there is zero, right)

30. *ANT: mhmm <# zero> [>] ? *SAR: <e: allorafa> [<] +”/. (so she goes like) *SAR: +”/ zero # c'è lo z(ero) [/] zero in it . (zero # there’s zero in it) *SAR e: eallora [>] . (and and then) *ANT: forty . [<] *SAR: four # eallora <mi faperò> [?] +"/. (four # and so she goes but) +"/ you have to guess [>] . *ANT: hmm [<] . *SAR: mi ha detto +"/. (she said to me) +"/ e: you have to guess ehmquantianni ho . (uuh you have to guess uhm what my age is) ehm: allora ho pensatoio +"/. (uhm and so I thought) +"/ saràquaranta . (she must be forty) *ANT: hmm [>] . *SAR: non [<] pensoche ne abbiacinquanta # eneanchetrenta . (I don’t think she’s fifty or even thirty)

31. The future… • Comparing the two frameworks, with particular reference to data covered by both (using English-Italian data) • Assess whether the contribution of a CA-type approach can offer a satisfactory explanation for the regularities encountered in CS that the MLF cannot readily account for. • Can a CA approach reveal whether a switched item counts as such for participants themselves?

32. Thanks to Present (and past) members of the ESRC Bilingualism Centre Corpus Based Research Group and AHRC project Margaret Deuchar Maria del Carmen ParafitaCouto Dirk Bury Peredur Davies Jon Herring Sian Lloyd Elen Robert Jonathan Stammers

33. GrazieDiolchThank you