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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Correspondence Analysis of the Natural and Specialized Perfectives of the Russian verb putat’ |
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Identification Number: |
doi:10.18710/TZYDNQ |
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Distributor: |
DataverseNO |
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Date of Distribution: |
2017-05-23 |
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Version: |
1 |
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Bibliographic Citation: |
Nordrum, Maria, 2017, "Replication Data for: Correspondence Analysis of the Natural and Specialized Perfectives of the Russian verb putat’", https://doi.org/10.18710/TZYDNQ, DataverseNO, V1, UNF:6:IIcqQd/NhX1Ce83PxjZP5A== [fileUNF] |
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Citation |
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Title: |
Replication Data for: Correspondence Analysis of the Natural and Specialized Perfectives of the Russian verb putat’ |
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Identification Number: |
doi:10.18710/TZYDNQ |
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Authoring Entity: |
Nordrum, Maria (UiT The Arctic University of Norway) |
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Producer: |
UiT The Arctic University of Norway |
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Distributor: |
DataverseNO |
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Distributor: |
The Tromsø Repository of Language and Linguistics (TROLLing) |
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Access Authority: |
Nordrum, Maria |
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Depositor: |
Nordrum, Maria |
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Date of Deposit: |
2017-05-19 |
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Holdings Information: |
https://doi.org/10.18710/TZYDNQ |
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Study Scope |
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Keywords: |
Arts and Humanities, Correspondence Analysis, Russian aspect, Natural Perfectives, Specialized Perfectives, Synchrony vs. diachrony |
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Abstract: |
This dataset contains the database and statistical code used for a term paper in HIF-3082 Quantitative Methods in Linguistics, spring 2017. It includes two datasets (I and II). Dataset I is used for a synchronic analysis of the verb cluster putat’ ‘mix up, mess up, confuse, tangle’ in Russian. There are seven verbs in the analysis: the simplex imperfective putat’ and six of its perfectives. Dataset I involves 1400 examples from the Russian National Corpus (years 1950-2016) that are tagged with semantic category of the verbs’ patients. Based on these semantic categories, I run a Correspondence Analysis to explore the relationship between verb and type of patient. Dataset II involves 295 examples from the Russian National Corpus (years 1800-1849) of the same verbs. The examples are tagged with the same semantic categories of patients as the examples in Dataset I. I use Correspondence Analysis to see whether the behavior of the verbs have changed over 200 years, and with that, the relationships within the verb cluster. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a> |
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Other Study Description Materials |
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File Description--f1469 |
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File: Database_TermPaper.tab |
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Notes: |
UNF:6:Q5aGFj7k75vu0BwcfEGf3w== |
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Database used in the study. |
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File Description--f1471 |
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File: Dataset1.tab |
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Notes: |
UNF:6:FhQFE+F2AcZQTllrOYBNHA== |
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Frequency distribution of the semantic categories in Dataset I: 1800-1849 (relative frequency). |
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File Description--f1475 |
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File: Dataset2.tab |
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Notes: |
UNF:6:SwYcmqP5d/72X7X2WutRMw== |
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Frequency distribution of the semantic categories in Dataset II: 1950-2016 (relative frequency). |
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List of Variables: |
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Variables |
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f1469 Location: |
Variable Format: character Notes: UNF:6:Q5aGFj7k75vu0BwcfEGf3w== |
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Verb;Abstract;Animate;Knots;Locations;LongThin;Networks;NonSpecific;PhysObjects;Omitted |
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f1471 Location: |
Variable Format: character Notes: UNF:6:FhQFE+F2AcZQTllrOYBNHA== |
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Verb;Abstract;Animate;Knots;Locations;LongThin;Networks;NonSpecific;PhysObjects;Omitted |
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f1475 Location: |
Variable Format: character Notes: UNF:6:SwYcmqP5d/72X7X2WutRMw== |
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Label: |
README.txt |
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Notes: |
text/plain |
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Label: |
R_code.txt |
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Notes: |
text/plain |