1 Andrej A. Kibrik Olga B. Markus Local discourse structure in Upper Kuskokwim Athabaskan SSILA Conference Berkeley, July 2009

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3 Basic information about Upper Kuskokwim Athabaskan (UKA)  About 30 speakers left out of the population of about 200  Most speakers reside in the village of Nikolai  Actual use of UKA – in two or three households  Prior work – Collins and Petruska 1979  Kibrik’s field trips in 1997 and 2001  As in other Athabaskan:  polysynthesis  highly complex verb morphology and morphophonemics

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5 Data  Natural discourse recordings (transcribed)  Folk stories  Personal stories  Conversation (pre-arranged)  Interview at school  In all – 3 hours 20 minutes of talk

6 Lena Petruska, the oldest speaker

7 Theory  Local discourse structure: Elementary discourse units (EDUs)  EDUs are elementary behavioral acts of discourse processing  EDUs are identified on the basis of a cluster of prosodic features:  Tonal contour  Central accent  Tempo pattern  Loudness pattern  Pausing

8 Example (1): tonal contours abcdfe

9 Example (1b): tempo pattern abcdfe  sighwdla 720ms / 3 = 240 ms per syllable  todoltsitł’ ts'e 1800 ms / 4 = 450 ms per syllable

10 Example (1): pausing abcdfe

11 Properties of EDUs  Prosodically identified EDUs display interesting content-related properties  Cognitively: manifest a focus of consciousness (Chafe)  Semantically: typically report event/state  Grammatically: often coincide with clauses

12 EDUs and clauses  Clausal EDUs  Short EDUs (less than one canonical clause)  Long EDUs (more than one canonical clause)

13 EDU types in example (1)  Clausal: b, c, f  Short:  aregulatory (discourse marker)  dsubclausal (topic)  efragmentary (false start)

14 Quantitative data: an overview  965 EDUs in the data set  Clausal EDUs – 70.8%  Short EDUs – 14.8%  Long EDUs – 14.4%

15 Clausal EDUs (683 = 100%)  Headed by a lexical verb – 84%(1b, c)  Headed by a verb of being – 6%(1f)  Non-verbal – 10%(2)

16 Non-verbal clausal EDU (2) ‘(There was) also lots of marten skins’

17 Short EDUs (143 = 100%)  Regulatory – 13% (1a)  Fragmentary – 20%(1e)  Nominalized – 7%  Subclausal – 50%  Prospective – 42%(1d)  Retrospective – 18%(3)

18 Retrospective subclausal EDUs Increment: (3) ‘That is why that happened to me then, because of the icon’

19 Long EDUs (139 = 100%)  Concatenation – 19%(4)  Adverbial – 0%  Relative clause + main clause – 2%  Non-quotative complement clause + main clause – 42%  Quotative clause + main clause – 37%(5)

20 Concatenation (4) ‘He went inside and lay down’  danaediyo 150 ms  naztanh 385 ms

21 Quotative clause + main clause (5) ‘You should also come slide with me, I told her’

22 EDUs and clauses in a typological perspective LanguagePercentage of clausal EDUs English (Chafe 1994)60% Mandarin (Iwasaki and Tao 1993)39.8% Sasak (Wouk 2008)51.7% Japanese (Matsumoto 2000)68% Russian (Kibrik and Podlesskaya 2009)68.6% Upper Kuskokwim70.8%

23 A possible explanation  Percentage of clausal EDUs is correlated with the degree of a language’s:  degree of morphological complexity  grammatically marked distinction of inflected verbs from other predicate types  Probably the languages overtly marking verbs as dedicated predicative elements more strongly correlate clauses with EDUs

24 Conclusions  EDUs as universal building blocks of local discourse structure are perfectly well identifiable in a polysynthetic language  EDUs display a high correlation with clauses  Short and long EDU types, as known in other languages, are also found in Upper Kuskokwim  An account of EDUs and their types is a necessary component of a grammatical description of any language, less studied and endangered languages not excluded

25 Some directions for further research  Different intonation contours – their discourse semantics  Interaction of discourse prosody with lexical tone, vestigially present in some idiolects

26 Tsenan!  Thanks to all speakers of Upper Kuskokwim, both mentioned and unmentioned above  Thanks to many individuals and organizations that helped to collect and process the data, in chronological order:  Michael Krauss  James Kari  Raymond Collins  Alaska Native Language Center  Fulbright Program  Endangered Language Fund  Bernard Comrie  MPI for Evolutionary Anthropology, Leipzig  Russian Foundation for the Humanities  National Science Foundation

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30 Welcome to Nikolai

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