Defounding the Effects of Competition and Attrition on Dialect - PowerPoint PPT Presentation

Defounding the Effects of Competition and Attrition on Dialect Across the Lifespan Karen V. Beaman, R. Harald Baayen, & Michael Ramscar Eberhard Karls Universität Tübingen Corpora for Language and Aging Research (CLARe 4) University of Helsinki, Finland February 27 – March 1, 2019 Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 1

Hypotheses 1) rather than lose dialect, speakers gain a massive amount of new lexical knowledge that is not spoken about in the dialect, which exerts a cumulative and competitive influence on their vocabularies and cognitive processing abilities; and 2) speakers are more likely to retain dialect forms when frequencies are high and words are drawn from early experiences, and to lose dialect forms when frequencies are low and words are more relevant to later life experiences. Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 2

Swabian Swabian or Schwäbisch is a High German dialect, belonging to the Alemannic family, spoken by just over 800,000 people. Two communities: • Stuttgart area • Schwäbisch Gmünd Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 3

Two Speech Communities Stuttgart Schwäbisch Gmünd Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 4

Some Swabian Features Palatalization of coda -st Front Rounded Vowels machst ~ machsch ‘do/make’ möglich ~ meeglich ‘possible’ gehst ~ gehsch ‘go’ schön ~ schee ‘pretty’ darfst ~ darfsch ‘may’ Bäume ~ Baim ‘trees’ nächst ~ nächscht ‘next’ Freund ~ Fraind ‘friend’ letzt ~ letscht ‘last’ Küche ~ Kiche ‘kitchen’ meistens ~ meischtens ‘most’ müde ~ mide ‘tired’ Diphthong Shift Irregular Verb Formation kein ~ kôi ‘none’ gehen ~ gange ‘go’ gleich ~ glôi ‘same’ verstehe ~ verstâh ‘understand’ allein ~ allôi ‘alone’ stehen ~ stande ‘stand’ daheim ~ dahôim ‘at home’ wollen ~ welle ‘want’ weiß ~ wôiß ‘I know’ haben ~ hen han khet ‘have’ nein ~ nôi ‘no’ tun ~ doe ‘do/make’ Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 5

Swabian: Loved or Loathed wenn i Urschwâbe hör, also die mã gar ned versteht, des denkt mã immer, des isch e Fremdsprache ja, … muss mã halt manchmal de Kopf schüttle, aber so find i des … kôi schlimme Sprach … i find e Dialekt isch nie schlecht ‘if I hear really old-Swabian , that you can‘t even understand, then you always think, that’s a foreign language, yeah, … sometimes you just have to shake your head, but I don‘t think it‘s a bad language … I think a dialect is never bad.’ (Bertha-82) meine Kinder schämen sich sogar heutzutage Schwäbisch, also die verbinden Schwäbisch mit irgendwas, was sie nicht möchten .… dieser dörfliche Zusammenhalt stoßen die eher ab. ‘nowadays my children are actually ashamed of Swabian, well they associate Swabian with something they don’t like…. they reject this village solidarity’ (Helmut-17) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 6

Methods • Sociolinguistic Interviews ― Labovian-style, casual interview questions, ca. one hour ― Native Swabian- speaking interviewers, “ friend-of- friend” ― Same interview instrument and same topics discussed in 1982 and 2017 • Transcription/Annotation ― Completed in ELAN, native German speakers, Swabian orthography ― Words tagged as: o Standard, e.g., habe ‘have’ o Vernacular, e.g., hab ‘have Dialect o Swabian, e.g., han ‘have Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 7

Corpus: Panel Study 1982 2017 20 Panel Speakers: Pseudonym Community Gender Abitur Age SOI Age SOI Angela Gmünd W Yes 18 4.5 52 4.2 − 1982 & 2017 Annelise Gmünd W Yes 21 3.5 56 3.6 Berdine Gmünd W Yes 21 3.9 56 3.3 Bertha Stuttgart W No 18 3.6 53 3.3 2 Communities: Egbert Stuttgart M Yes 24 4.0 59 3.6 − 7 from Stuttgart Elke Gmünd W No 22 4.2 57 4.3 Ema Stuttgart W No 48 4.2 83 4.2 − 13 from Gmünd Helmut Stuttgart M Yes 22 3.3 57 2.0 Herbert Gmünd M No 51 4.2 86 4.2 Jurgen Gmünd M Yes 19 3.8 55 3.3 2 Genders: Louise Gmünd W No 53 4.3 88 4.0 − 11 men Manni Stuttgart M Yes 23 3.7 59 2.8 Markus Gmünd M Yes 22 4.3 56 2.8 − 9 women Myles Gmünd M Yes 23 4.5 58 4.2 Pepin Stuttgart M Yes 25 3.4 60 3.8 2 Education levels: Rachael Gmünd W No 47 4.4 83 4.3 Ricarda Stuttgart W Yes 18 3.5 53 2.1 − 14 with Abitur Rupert Gmünd M Yes 23 4.0 58 2.6 Siegfried Gmünd M Yes 21 4.2 57 4.8 − 6 without Abitur Theo Gmünd M Yes 18 4.0 53 3.7 Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 8

Swabian Orientation Index (SOI) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 9

Types and Tokens ‘ THE CAT IS ON THE MAT ’ • WORD TYPE – a unique letter string • WORD TOKEN – a specific instance of a WORD TYPE • TEXT LENGTH is measured by the number of WORD TOKENS • VOCABULARY SIZE is measured by the number of WORD TYPES DATASET 1982 2017 TOKENS 1982 2017 TYPES 17,707 17,134 DIALECT 22,401 20,795 TOKENS 72,560 90,414 STANDARD 50,149 69,619 Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 10

Lexical Productivity • Challenges in lexical productivity analysis: ― VOCABULARY SIZE increases with TEXT LENGTH ― intrinsic order in aggregate data could skew the results • VOCABULARY GROWTH CURVE is calculated by counting the number of TOKENS within equally spaced measurement points throughout the text and graphing the corresponding count of each WORD TYPE . • RANDOMISATION WINDOW performs Monte Carlo-like permutations on subsections of the text at predefined measurement points Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 11

Vocabulary Growth Curves Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 12

Community and Education (1 of 2) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 13

Community and Education (2 of 2) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 14

Swabian Orientation Index (SOI) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 15

Dialect Vocabulary and Orientation Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 16

Individual Patterns of Change Dialect Manni Rupert Siegfried Helmut Theo Angela Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 17

Individual Patterns of Change Standard Dialect LIFESPAN CHANGE STABILITY RETROGRADE Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 18

Frequency Effects Dialect and Standard 2017 log word frequency (+1) 1982 log word frequency (+1) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 19

Frequency Effects Dialect and Standard Standard only 2017 log word frequency (+1) 2017 log word frequency (+1) 1982 log word frequency (+1) 1982 log word frequency (+1) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 20

Frequency Effects Dialect and Standard Standard only Standard-Dialect Difference difference in log word frequency (+1) 2017 log word frequency (+1) 2017 log word frequency (+1) 1982 log word frequency (+1) 1982 log word frequency (+1) 1982 log word frequency (+1) Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 21

In Summary • Vocabulary size increases with age and experience • Later life experiences come in the form of the standard language • Swabian is not in decline, rather restricted to specific domains of use • Swabian Orientations influence levels of dialect usage • Low frequency dialect words have become slightly more frequent • Age of acquisition suggests early acquired words are more accessible Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 22

Thank you! CORRESPONDING AUTHOR : Karen V. Beaman Queen Mary, University of London Eberhard Karls University of Tübingen karenbeamanvslx@gmail.com Beaman, Baayen, and Ramscar – CLARe4 Helsinki – February 2019 Page 23