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Dialect loss in the Russian North: Modeling change across variables

Published online by Cambridge University Press:  21 February 2020

Michael Daniel
Affiliation:
HSE University, Russian Federation
Ruprecht von Waldenfels
Affiliation:
Friedrich Schiller University Jena
Aleksandra Ter-Avanesova
Affiliation:
V.V. Vinogradov Russian Language Institute of the Russian Academy of Sciences
Polina Kazakova
Affiliation:
HSE University, Russian Federation
Ilya Schurov
Affiliation:
HSE University, Russian Federation
Ekaterina Gerasimenko
Affiliation:
HSE University, Russian Federation
Daria Ignatenko
Affiliation:
HSE University, Russian Federation
Ekaterina Makhlina
Affiliation:
HSE University, Russian Federation
Maria Tsfasman
Affiliation:
HSE University, Russian Federation
Samira Verhees
Affiliation:
HSE University, Russian Federation
Aleksei Vinyar
Affiliation:
HSE University, Russian Federation
Vasilisa Zhigulaskaja
Affiliation:
HSE University, Russian Federation
Maria Ovsjannikova
Affiliation:
Institute for Linguistic Studies, Russian Academy of Sciences
Sergey Say
Affiliation:
Institute for Linguistic Studies, Russian Academy of Sciences
Nina Dobrushina
Affiliation:
HSE University, Russian Federation

Abstract

We analyze the dynamics of dialect loss in a cluster of villages in rural northern Russia based on a corpus of transcribed interviews, the Ustja River Basin Corpus. Eleven phonological and morphological variables are analyzed across 33 speakers born between 1922 and 1996 in a series of logistic regression models. We propose three characteristics for a comparison of the rate of loss of different variables: initial level, steepness, and turning point. We show that the dynamics of loss differs significantly across variables and discuss possible reasons for such differences, including perceptual salience, initial variation in the dialect, and convergence with regionally or socially defined varieties of Russian. In conclusion, we discuss the pros and cons of logistic regression as an approach to quantitative modeling of dialect loss. Our paper contributes to the study and documentation of Russian dialects, most of which are on the verge of extinction.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2020

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Footnotes

The article was prepared within the HSE University Basic Research Program and funded by the Russian Academic Excellence Project ‘5–100.’ We wish to thank the community in Mikhalevskaja, who welcomed us and shared their stories with us. Some of our consultants are not among the living anymore, and we honor their memory. We also thank all other consultants and friends, and are deeply grateful to Svetlana and Nikolai Pushkin who hosted us during our first stays and immensely helped us with the organization of all aspects of our fieldwork.

The main contributors to the text of the paper are Michael Daniel and Ruprecht von Waldenfels, and then, in order of appearance, Nina Dobrushina and Aleksandra Ter-Avanesova. Polina Kazakova and Ilya Schurov provided all plots and coded statistical models in R (R Core Development Team, 2009). Ekaterina Gerasimenko, Daria Ignatenko, Polina Kazakova, Ekaterina Makhlina, Maria Ovsjannikova, Sergey Say, Maria Tsfasman, Samira Verhees, Aleksei Vinyar, and Vasilisa Zhigulskaja interpreted and coded linguistic variables. Nina Dobrushina, Ruprecht von Waldenfels, and Michael Daniel are supervising the Ustja River Basin corpus project. Nina Dobrushina and Aleksandra Ter-Avanesova supervised the transcription of the interviews and the coding of the variables. Ruprecht von Waldenfels and Ekaterina Gerasimenko provided all technical infrastructure for the Ustja River Basin corpus. All authors participated in data collection and transcription. Scripts, data and additional materials are available at https://github.com/LingConLab/Ustja_dialect_loss.

References

Baayen, R. Harald. (2008). Analyzing linguistic data. A Practical introduction to statistics using R. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Bates, Douglas, Maechler, Martin, Bolker, Ben, & Walker, Steve. (2015). Fitting linear mixed-effects models using lme4. In Journal of Statistical Software, 67(1): 148.CrossRefGoogle Scholar
Bowie, David, & Yaeger-Dror, Malcah. (2014). Phonological change in real time. In Honeybone, P. & Salmons, J. (Eds.), The Oxford handbook of historical phonology. Oxford: Oxford University Press. 603–18.Google Scholar
Bromley, Sofja V. (2002). Obrazovanie nesoglasuemoj formy i istorija člennyh form sravnitelʹnoj stepeni v russkom jazyke (po pamjatnikam pisʹmennosti XI-XVII vv.). In Bromley, Sofja V.Problemy dialektologii, lingvogeografii i istorii russkogo jazyka. In Russian. [Morphology of non-agreeing comparative form and the history of full comparative forms in Russian, data from XI-XVII century manuscripts]. Moskva: Azbukovnik. 543621.Google Scholar
Bubrikh, Dmitri V. (1914). Foneticheskie osobennosti govora Pustoshej Jagodinskoj vol. Sudogodskogo ujezda Vladimirskoj gub. In Izvestija Otdelenija russkogo jazyka i slovesnosti Imperatorskoj Akademii nauk, 1913, 18, kniga (issue) 1. In Russian. [Phonetic peculiarities of the dialect of Pustosha (Jagodina volost, Sudogda ujezd, Vladimir gubernija)]. Saint Petersburg.Google Scholar
Chambers, Jack K., & Trudgill, Peter. (1998). Dialectology. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
DARJА: Dialektologicheskiy atlas russkogo jazyka. Centr evropejskoy chasti SSSR. Vypusk I. Fonetika. 1986. Vypusk II. Morfologija. 1989. Vypusk III, chast’ 1. Leksika. 1997. chast’ 2. Sintaksis i leksika. 2004. Avanesov R. I., Bromlej S. V., Kuzmina I. B., Morakhovskaya O. N. (Eds.), In Russian. [Dialectological Atlas of Russian. Central European Part of the USSR. Issue I. Phonetics. Issue II. Morphology. Issue III. Part 1. Lexicon. Part 2. Lexicon and Syntax], Moscow.Google Scholar
Dorian, Nancy C. (1994). Varieties of variation in a very small place: Social homogeneity, prestige norms, and linguistic variation. Language 70(4): 631–96.CrossRefGoogle Scholar
Erofeeva, Elena V. (2005). Verojatnostnaja struktura idiomov: sociolingvisticheskij aspekt. In Russian. [Probability structure of idioms: a sociolinguistic perspective]. Perm’: Izdatelstvo Permskogo Universiteta.Google Scholar
Fruehwald, Joseph. (2017). Generations, lifespans, and the zeitgeist. Language Variation and Change 29(1): 127.CrossRefGoogle Scholar
Gecova, Oksana G. (1997). Dialektnye različija russkix arxangelʹskix govorov i ix lingvogeografičeskaja xarakteristika. In Voprosy russkogo jazykoznanija. VII. Russkie dialekty: istorija i sovremennostʹ. In Russian. [Distinctive properties of Arkhangelsk dialects and their linguogeographic characteristics]. Moscow: Izdatelʹstvo MGU. 138–97.Google Scholar
Grinkova, Nadezhda P. (1947). K izucheniju oloneсkih dialektov. In Obnorskij, S.P. (Ed.). Akademik A.A. Šaxmatov. Sbornik statej i materialov. In Russian. [A contribution to the study of Olonec dialects]. Leningrad (Saint Petersburg): AN SSSR. 365–91.Google Scholar
Hosmer, David W., & Lemeshow, Stanley. (2000). Applied logistic regression. New York: John Wiley and Sons.CrossRefGoogle Scholar
Ignatenko, Daria. (2015). Realizacija zvuka na meste literaturnogo [ʃ’:] v govore derevni Mixalevskaja Ustjanskogo rajona Arxangelskoj oblasti. In Aktualnyje problemy russkoj dialektologii. K 100-letiju izdanija Dialektologicheskoj karty russkogo jazyka v Evrope. In Russian. [The reflex of the standard [ʃ’:] in the dialect of Mikhalevskaja, Ustja district]. Moscow. Vinogradov Russian Language Institute, Russian Academy of Sciences. 75–8.Google Scholar
Kerswill, Paul, & Williams, Ann. (2005). New towns and koineization: linguistic and social correlates. Linguistics 43(5): 1023–48.CrossRefGoogle Scholar
Kochetov, Alexei. (2006). The role of social factors in the dynamics of sound change: A case study of a Russian dialect. Language Variation and Change 18(01): 99119.CrossRefGoogle Scholar
Labov, William. (1963). The social motivation of a sound change. Word 19(3): 273309.CrossRefGoogle Scholar
Labov, William. (1972). Sociolinguistic patterns. Oxford: Blackwell.Google Scholar
Labov, William. (2001). Principles of linguistic change. Vol. 2. Social factors. Language in Society. Oxford: Blackwell.Google Scholar
Labov, William, Rosenfelder, Ingrid, & Fruehwald, Josef. (2013). One hundred years of sound change in Philadelphia: Linear incrementation, reversal, and reanalysis. Language 89(1): 3065.CrossRefGoogle Scholar
Lippi-Green, Rosina L. (1989). Social network integration and language change in progress in a rural alpine village. In Language in Society 18(2): 213–34.CrossRefGoogle Scholar
Milroy, Lesley. (1987). Language and social networks. Oxford: Basil Blackwell.Google Scholar
Nahkola, Kari, & Saanilahti, Marja. (2004). Mapping language changes in real time: A panel study on Finnish. Language Variation and Change 16(02): 7592.CrossRefGoogle Scholar
Orlova, Varvara G. (1970). Javlenija-innovacii Rostovo-Suzdalskogo proisxozhdenija. In Orlova, V.G. (Ed.), Obrazovaniye severnorusskogo narechiya i srednerusskih govorov. In Rus. [Formation of the North and Middle Russian dialects]. Moscow: Nauka.Google Scholar
R Development Core Team. (2009). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna.Google Scholar
Rickford, John R. (2002). Implicational scales. In Chambers, J.K., Trudgill, P., Schilling, N. (Eds.), The Handbook of Language Variation and Change. 142–67.Google Scholar
Sankoff, Gillian, & Blondeau, Hélène. (2007). Language change across the lifespan: /r/ in Montreal French. Language 83(3): 560–88.CrossRefGoogle Scholar
Sologub, Anna I. (1970). Vologodskaja gruppa govorov. In Orlova, V.G. (Ed.), Obrazovaniye severnorusskogo narechiya i srednerusskih govorov, in Rus. [Formation of the North and Middle Russian dialects]. Moscow: Nauka.Google Scholar
Sundgren, Eva. (2009). The varying influence of social and linguistic factors on language stability and change: The case of Eskilstuna. In Language Variation and Change 21(1): 97133.CrossRefGoogle Scholar
Trudgill, Peter. (1974). The social differentiation of English in Norwich. Cambridge: Cambridge University Press.Google Scholar
Trudgill, Peter. (1986). Dialects in contact. Oxford: Blackwell.Google Scholar
von Waldenfels, Ruprecht, Daniel, Michael, & Dobrushina, Nina (2014). Why standard orthography? Building the Ustya River Basin Corpus, an online corpus of a Russian dialect. In Komp'juternaja lingvistika i intellektual'nye technologii: Po materialam ežegodnoj Meždunarodnoj konferencii «Dialog». 13(20). Moscow: RGGU.Google Scholar
Wickham, Hadley. (2016). ggplot2: Elegant Graphics for Data Analysis. New York: Springer.CrossRefGoogle Scholar
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