Testing the predictions of usage-based models on language ...laurelmackenzie.com/presentations/MacKenzie_NWAV43...October 26, 2014 Laurel MacKenzie (U of Manchester) NWAV 43 1 / 24

Testing the predictions of usage-based models onlanguage change across the lifespan

Laurel MacKenzie

University of Manchester

New Ways of Analyzing Variation 43October 26, 2014

Laurel MacKenzie (U of Manchester) NWAV 43 1 / 24

http://personalpages.manchester.ac.uk/staff/laurel.mackenzie/


Today’s talkUniting two strands of research in sociolinguistics:

1. Usage-based models

2. Intra-speaker longitudinal change



A testing groundLifespan change (Sanko�, 2005)

I The participation of individual speakers in ongoing communitychanges in progress

I Harrington et al. (2000), a.o.: Queen Elizabeth II shows vowel shifttoward Standard Southern British English of 1980s

I Raumolin-Brunberg (2005): individual speakers of Early ModernEnglish follow community shift from 3rd singular -th to -s

I Sanko� and Blondeau (2007): individual speakers of Quebec Frenchfollow community shift from apical [r] to dorsal [R]





Connecting lifespan change to usage-based models of grammar





Connecting lifespan change to usage-based models of grammarI Individual receives linguistic input from surrounding community

members





Connecting lifespan change to usage-based models of grammarI Community members display the change in progress





Connecting lifespan change to usage-based models of grammarI Individual hears high-frequency words from these community members

more often than other words





Connecting lifespan change to usage-based models of grammarI Individual’s mental representations of high-frequency words pick up

the change before words he hears less often





Connecting lifespan change to usage-based models of grammarI Therefore, frequent words should lead lifespan change



The question that prompted this study

Does individual participation in community-level change show frequencye�ects as predicted under a theory in which input gradually shapes

production?



Previous work related to this questionAcquisition of new variants in a dialect contact situation

I Sanko� (2004): Northern English speakers learning FOOT/STRUTdistinction

I ‘Word-by-word learning vs. blanket but variable unrounding across thevocabulary[? . . . ] variability is the order of the day.’

I Nycz (2013): Canadians in NYC unlearning Canadian Raising &LOT-THOUGHT merger

I Canadian features retained in v. frequent words (stylistic e�ect?), butother words show accommodation mediated by frequency



Table of Contents

1 Introduction

2 The current study

3 Discussion



The individualSir David Attenborough

I Born 1926, LondonI Educated at CambridgeI Narrator of nature documentaries beginning with Zoo Quest (1954),

most recently Life Story (airing now)I Speaker of Received Pronunciation


The community changeThe decline of [R]

I In traditional RP, [R] found intervocalically after a stressed vowel(Wells, 1982; Cruttenden, 2014)

I word-internally, e.g. squirrels

I in hiatus (‘linking’) position, e.g. all our equipment

I ‘Among the changes almost complete in British English [is that] /r/ isrealized as a post-alveolar approximant in all positions’

(Cruttenden, 2014, 83)

Research questions:

I Does Attenborough participate in this community change over time?I If so, is his change frequency-driven?


Data

Zoo Quest for a Dragon, 1956 Planet Earth, 2006(age 30) (age 80)

62 minutes of speech 108 minutes of speech

transcribed & aligned using FAVE-align

Tokens of underlying /r/ after stressed vowels coded auditorilytap | approximant


ModelingFixed-e�ect predictors:

IDecade 1950s | 2000s

IMorphosyntactic level of /r/ internal (forest, near-est) |

linking (here is)I

Borrowing yes (saguaro, Sahara) | noI

Realization of previous token tap | approximantI

Time in recording (continuous)I

Word / bigram frequency (continuous)I 201.7-million word SUBTLEX-UK corpus (van Heuven et al., 2014)I subtitles collected from 45,099 BBC programsI does a better of job of predicting lexical decision times than frequencies

from BNC, CELEX, or SUBTLEX-US


ModelingFixed-e�ect predictors:

IDecade 1950s | 2000s

IMorphosyntactic level of /r/ internal (forest, near-est) |

linking (here is)I

Borrowing yes (saguaro, Sahara) | noI

Realization of previous token tap | approximantI

Time in recording (continuous)I

Word / bigram frequency (continuous)

Random-e�ect predictors:I

Word

IEpisode


Controlling for style in Zoo Quest


Participation in community change?


Domain-specific retrograde change


On retrograde lifespan changeWagner and Sanko� (2011)

‘IF is perhaps a marker of adult speech, appropriate to the more formal discoursecharacteristic of this life stage’ (299)

’[I]t is possible that stylistic di�erences will prove to be a strongly conditioningfactor’ (305)


Style data

careful casual1950s Zoo Quest narration Zoo Quest onscreen2000s Planet Earth narration oral history (77 min.)


Style-shifting


Word/bigram frequency

No significant e�ect in either decade


Who serves as the model in longitudinal change?

‘In their middle years, do people look to the models from older speakersthat they neglected when they were young? To what extent does inputfrom older speakers provide conservative forms to language learners?’

(Wagner and Sanko�, 2011, 305)


How much of a role does community input play?I ‘. . . virtually all of the evidence for ongoing linguistic change in

adulthood derives from an increase in frequency of forms’(Tagliamonte and D’Arcy, 2009, 62–63)

I In other words, longitudinal change tends to take the shape ofindividuals manipulating their rate of use of variants they alreadycommand, rather than learning (or unlearning) a variant entirely.

I e.g. Nahkola and Saanilahti (2004); Raumolin-Brunberg (2005);Sanko� and Blondeau (2007)

I A theory in which community usage shapes individual languageproduction needs to account for the fact that individuals don’t(can’t?) simply pick up whatever they hear


In sum. . .I Usage-based models raise important questions about individual

language production vis-à-vis community usageI Such theories need to make provisions for the fact that individuals can

change away from their received input. . .I (though it’s worth acknowledging that we don’t always have a firm

grasp on what that input necessarily is)I . . . and that there appear to be limits on the extent to which

individuals can be influenced by community inputI Though the community has (with good reason) been the prime focus

of many sociolinguistic studies, a focus on the individual can elucidatequestions about our capacity to learn and our capacity to change, andthe nature of human language more generally


Acknowledgements

Lana Ali, Darian Flowers, & Laura GallagherDanielle TurtonJoe Fruehwald


Documents

Testing the predictions of usage-based models on language ...laurelmackenzie.com/presentations/MacKenzie_NWAV43...October 26, 2014 Laurel MacKenzie (U of Manchester) NWAV 43 1 / 24