Non-Standard Allomorphy in Russian Prefixes: Corpus, Experimental, and Statistical Explorationdoi:10.18710/FKJAJRDataverseNO2014-08-181Endresen, Anna, 2014, "Non-Standard Allomorphy in Russian Prefixes: Corpus, Experimental, and Statistical Exploration", https://doi.org/10.18710/FKJAJR, DataverseNO, V1Non-Standard Allomorphy in Russian Prefixes: Corpus, Experimental, and Statistical Explorationdoi:10.18710/FKJAJREndresen, AnnaUiT The Arctic University of Norway2014DataverseNOThe Tromsø Repository of Language and Linguistics (TROLLing)Endresen, Anna2014-08-15Arts and HumanitiesprefixesRussianverbsallomorphyField: MorphologyField: SemanticsTime-depth: synchronicTopic: affixesAbstract: This dissertation challenges the traditional idealized model of allomorphy by confronting it with comprehensive data on 15 Russian aspectual prefixes (RAZ-, RAS-, RAZO-, S-, SO-, PERE-, PRE-, VZ-, VOZ-, O-, OB-, OBO-, U-, VY-, IZ-) collected from corpus and linguistic experiments. The traditional definition narrows allomorphy down to a mere variation of form where the meaning remains constant and variants are distributed complementarily. My findings show that submorphemic semantic differences and distributional overlap are not uncommon properties of morpheme variants. I suggest that allomorphy is a broader phenomenon that goes beyond the axioms of complementary distribution and identical meaning. I examine non-trivial cases of prefix polysemy and multifactorial conditioning of prefix distribution that make it difficult to assess the traditional criteria for allomorphy. Moreover, I present studies of semantic dissimilation of allomorphs and overlap in distribution that violate the absolute criteria for allomorphic relationship. I take the perspective of Cognitive Linguistics and propose an alternative usage-based model of allomorphy that is flexible enough to capture both standard exemplars and non-standard deviations. This model offers detailed applications of several advanced statistical models that optimize the criteria of both semantic “sameness” and distributional complementarity. According to this model, allomorphy is a scalar relationship between morpheme variants – a relationship that can vary in terms of closeness and regularity. Statistical modeling turns the concept of allomorphy into a measurable and verifiable correspondence of form-meaning variation. This makes it possible to measure semantic simi larity and divergence and distinguish robust patterns of distribution from random effects.The set of files includes tagged databases, their versions used in statistical analyses and R codes for the statistical analyses described in the dissertation.RussiaRussiacorpus<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>Endresen, Anna. Non-Standard Allomorphy in Russian Prefixes: Corpus, Experimental, and Statistical Exploration. PhD Thesis. UiT The Arctic University of Norway. https://hdl.handle.net/10037/7098.10037/7098Endresen, Anna. Non-Standard Allomorphy in Russian Prefixes: Corpus, Experimental, and Statistical Exploration. PhD Thesis. UiT The Arctic University of Norway. https://hdl.handle.net/10037/7098.ALL PREFIXES CORPUS FACTITIVE VERBS.xlsxA corpus-based collection of factitive verbs formed by different prefixes (O-, U-, ZA-, RAZ-, etc.) and from different types of bases (adjectival, nominal, pronominal, adverbial, etc.)application/octet-streamDataOU.csvThis is a reduced version of the database for the purposes of the statistical analysis of the corpus data (155 verbs in O- and U-).text/plain; charset=US-ASCIIdatOB.csvThis is the database of subjects responses for the Linear Regression Mixed Effects Modeltext/plain; charset=US-ASCIIObCorpus.csvThis is the database for the statistical analysis of the corpus data on O-, OB-, and OBO-. It excludes deetymologized verbs.text/plain; charset=US-ASCIIObExperimentRandomForestData.csvThis is the database of subjects responses for the Classification Tree & Random Forests modeltext/plain; charset=US-ASCIIObExperimentSubjects.csvThis spreadsheet contains anonymous sociolinguistic information about the subjects who participated in the experiment.text/plain; charset=US-ASCIIO OB DATABASE CORPUS.xlsxThis database contains 1037 verbs in O-, OB-, and OBO- collected from the Russian National Corpus.application/octet-streamO U CORPUS DATA.xlsxThis database contains 155 factitive (change-of-state) verbs in O- and U- collected from the Russian National Corpus.application/octet-streamO U EXPERIMENTAL DATA.xlsxAcceptability scores elicited from 121 subjects in the experiment on Russian factitive verbs in O- and U-.application/octet-streamPERE PRE DATABASE.xlsxThis database contains 945 verbs prefixed in PERE- and PRE- collected from the Russian National Corpus.application/octet-streamRAZ DATABASE.xlsxThis database contains 210 perfective Russian verbs formed by the prefixes RAZ-, RAS-, and RAZO- 'apart'. These prefixes represent a case of Standard Allomorphy conditioned by phonological and morphophonological factors. Two phenomena are at work here: voicing assimilation across a prefix-root boundary (prefixes RAZ- ~ RAS- 'apart') and vocalization of consonant-final Russian prefixes (RAZ- ~ RAZO- 'apart').application/octet-streamRAZ_RAS.csvThis is a csv version of the database designed for the purposes of the statistical analysis documented in the R code.text/plain; charset=US-ASCIIRAZ_RAS_RAZO.csvThis is a csv version of the database designed for the purposes of the statistical analysis documented in the R code.text/plain; charset=US-ASCIIR script O OB CORPUS.RThis is the code for the statistical analysis of the corpus data on the prefixes O-, OB-, and OBO-.text/plain; charset=US-ASCIIR script O OB EXPERIMENT.RThis is the R code for both statistical models for the experimental data on the prefixes O-, OB-, and OBO-.text/plain; charset=US-ASCIIR script O U CORPUS DATA.RR code for the statistical analysis of 155 factitive verbs in O- and U-text/plain; charset=US-ASCIIR script O U EXPERIMENT ALL MODELS.RThis is the R code for all statistical models applied to the experimental data on O- and U- in factitive verbs.text/plain; charset=UTF-8R script PERE PRE.RThis is the R code for several statistical tests discussed in Chapter 6.text/plain; charset=US-ASCIIR script RAZ.RThis is the R code for the statistical analysis. The statistical analysis models the distribution of these polysemous but standard allomorphs and evaluates the relative impact of each factor.text/plain; charset=US-ASCIIR script S SO.RThis is the R code for the statistical analysis discussed in Chapter 4.text/plain; charset=US-ASCIIR script VY IZ.RThis R code documents the statistical tests discussed in Chapter 8.text/plain; charset=US-ASCIIR script VZ VOZ.RThis R code documents the statistical test discussed in Chapter 7.text/plain; charset=US-ASCIIScoresForStatistics.csvThis is the database for the statistical analysis.text/plain; charset=US-ASCIIS SO MODERN RUSSIAN.xlsxThis database contains 998 Modern Russian verbs in S- and SO- collected from the Russian National Corpus. Each verb is assigned a number of tags and is illustrated with examples from the corpus.application/octet-streamVY IZ DATABASE.xlsxThis database contains 989 verbs in VY- and IZ- attested in the Russian National Corpus.application/octet-streamVZ VOZ DATABASE.xlsThis database contains 384 verbs in VZ- and VOZ- collected from the Russian National Corpus.application/vnd.ms-excel