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Longitudinal data on individual grammaticalisation Freek Van de Velde Peter Petré University of Leuven Research Foundation Flanders – FWO Fluid Construction Grammar Meeting, 8-13 August 2014

Longitudinal data on individual grammaticalisation - KU · PDF fileLongitudinal data on individual grammaticalisation ... [be Ving][imperfectivity/on- ... i.e. whether go is followed

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Page 1: Longitudinal data on individual grammaticalisation - KU · PDF fileLongitudinal data on individual grammaticalisation ... [be Ving][imperfectivity/on- ... i.e. whether go is followed

Longitudinal data on individual

grammaticalisation

Freek Van de Velde

Peter Petré

University of Leuven

Research Foundation Flanders – FWO

Fluid Construction Grammar Meeting, 8-13 August 2014

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Grammaticalisation

• Grammaticalisation: the recruitment of lexical

material to fabricate new grammar

– auxiliaries from main verbs:

(PIE *uert- 'turn around' > OE weorðan,

Germ. werden)

– condensation of small clause fragments

(het mag (ge)schieden > misschien)

(it may be > maybe)

– conjunctions from word groups:

(þa hwile þe > while)

Supporting stakes are

made of beams (i.e. of

trees)

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Grammaticalization: regular or erratic?

• Regularity:

– Across languages: Heine & Kuteva 2002

– Within languages: Van Gelderen 2011

• Variability:

– Co-determined by structural environment (Mithun 1991:160; Fischer

1997:265; 2007, ch.4; Hilpert 2008; Verstraete 2008; De Vogelaer

2010; Colleman & De Clerck 2011; Ghesquière & Van de Velde 2011;

De Smet & Van de Velde 2013; Petré 2014, among many others).

– Individual differences?

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Individual vs. aggregate level

"Unfortunately, of course, how to define language change remains a controversial issue. The basic

division is between two schools of thought. On the one hand there are those who,

following Chomsky and earlier writers such as Paul (1880), view the competence of the individual

speaker (I language) as the primary object of study in linguistics. On the other hand there are

those who stress the social dimension of language and focus their research on the "orderly

heterogeneity" (Weinreich, Labov and Herzog 1968: 100) of usage by different social groups

within a speech community. The latter school naturally views language change as minimally a

change common to all members of a particular subgroup of a speech community – anything less

is merely individual variation, not change." (Lucas 2014)

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Individual vs. aggregate level

"Unfortunately, of course, how to define language change remains a controversial issue. The basic

division is between two schools of thought. On the one hand there are those who,

following Chomsky and earlier writers such as Paul (1880), view the competence of the individual

speaker (I language) as the primary object of study in linguistics. On the other hand there are

those who stress the social dimension of language and focus their research on the "orderly

heterogeneity" (Weinreich, Labov and Herzog 1968: 100) of usage by different social groups

within a speech community. The latter school naturally views language change as minimally a

change common to all members of a particular subgroup of a speech community – anything less

is merely individual variation, not change." (Lucas 2014)

one individual (contextualised) multiple individuals

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Individual vs. aggregate level

"Unfortunately, of course, how to define language change remains a controversial issue. The basic

division is between two schools of thought. On the one hand there are those who,

following Chomsky and earlier writers such as Paul (1880), view the competence of the individual

speaker (I language) as the primary object of study in linguistics. On the other hand there are

those who stress the social dimension of language and focus their research on the "orderly

heterogeneity" (Weinreich, Labov and Herzog 1968: 100) of usage by different social groups

within a speech community. The latter school naturally views language change as minimally a

change common to all members of a particular subgroup of a speech community – anything less

is merely individual variation, not change." (Lucas 2014)

(From: Steels 2011) (From: Beuls & Steels 2013)(From: Van Trijp 2014)

one individual (contextualised) multiple individuals

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Individual vs. aggregate level

"Unfortunately, of course, how to define language change remains a controversial issue. The basic

division is between two schools of thought. On the one hand there are those who,

following Chomsky and earlier writers such as Paul (1880), view the competence of the individual

speaker (I language) as the primary object of study in linguistics. On the other hand there are

those who stress the social dimension of language and focus their research on the "orderly

heterogeneity" (Weinreich, Labov and Herzog 1968: 100) of usage by different social groups

within a speech community. The latter school naturally views language change as minimally a

change common to all members of a particular subgroup of a speech community – anything less

is merely individual variation, not change." (Lucas 2014)

(From: Roy 2011) (From: Szmrecszanyi 2012)(From: Wang et al. 2009)

short time span long time span

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Individual vs. aggregate level

(From: Szmrecszanyi 2012)

(From: Barlow 2013)

(From: De Smet, ms.)

synchronic / short time span:diachronic / non-longitudinal:

no individual differences:

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• Research on individual differences in

– language attainment experiments (see Dąbrowska 2012)

– Synchronic corpus studies (Barlow 2013)

– Historical corpus studies (Nevalainen et al. 2011; De Smet, ms.)

– Diachronic (longitudinal) corpus studies (Bergs 2005; Raumolin-Brunberg 2009;

Hendriks 2013)

• What is lacking?

– Diachronic (longitudinal) LARGE-SCALE corpus studies

(From: Nevalainen et al. 2011)

(From: Hendriks 2013)

diachronic, semi-longitudinal: diachronic, semi-longitudinal, small scale:

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Be going to ∙ grammaticalization

• [I am going] [to buy some chocolate] > [I am going to buy some chocolate]

• Source construction: [[go][allative motion]] + [[be Ving][imperfectivity/on-

goingness]] + [[to Inf][purpose adjunct]]

I am goyng to the Pope, to praie him to place me in mariage. (1566, The palace of

pleasure beautified ... [EEBOCorp 1.0])

• Previous work by Hilpert (2008), Traugott (2011, 2012), Traugott &

Trousdale (2013), Disney (2009, ms.), Petré (2013a).

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Methodology

• Corpus description

– EEBOCorp 1.0 (Petré 2013b)

– EEBO-database (eebo.chadwyck.com): English books printed 1473-1700.

– Selection criteria:

1. Sufficient material for first and second halves of writer’s careers

2. Constant register over time

3. Writers are from roughly the same social status.

– Resulting corpus: 31 million tokens, with individual author token counts

ranging between ca. 300,000 and 10,000,000 words

– Perl scripts for retrieving all instances of going (n = 5821), including variants

– After semi-manual filtering a total of 1591 instances of be going remained

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Methodology

• Data coding and analysis

– Several formal and semantic features that are commonly associated with the

grammaticalization of be going to. Summatively, we use these diagnostics to

assess the level of grammaticalization reached in a particular individuals,

which serves as the dependent variable in our inquiry.

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Methodology

• Data coding and analysis1. ‘adjacency’, i.e. the linear contiguity of go and the to-inf part

He's going (now) to see some fresher beauties.

2. ‘structural’ features (‘fronting’, ‘parenthetical use’, ‘coordination’ with existing aspectual auxiliaries)

that barbarous action he was going to commit.

3. ‘goal’, i.e. the presence or absence of a goal

Sir, I am just now going to a Lawyer (to aske his Councell).

4. ‘voice’, i.e. whether go is followed by a passive to-inf

Are not you going to be married?

5. ‘motion’, i.e. can going be interpreted as expressing spatial motion?

Count de Saluces was going to be her lover.

6. ‘animacy’, i.e. whether the subject is animate or not.

Examples which are now going to be Familiar to me.

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Methodology

• Data coding and analysis

– For each of the authors, we divided the collected data in half, to arrive at two

categories ‘earlier work’ and ‘later work’, in order to check whether

differences occurred through the years.

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Aggregate grammaticalisation, with lowess regression line

(Correlation: Kendall tau = 0.126, p < 0.0001)

1650 1660 1670 1680 1690 1700 1710 1720

0

2

4

6

8

10

Aggregate grammaticalisation score (jittered)

Datapoints, chronological

Sum

mat

ive

gram

mat

ical

isat

ion

scor

e

lowess

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Author aggregate scores, with lowess regression line

(Correlation: Kendall tau = 0.221, p < 0.0001)

12

34

56

Authors, by year of birth

gram

mat

ical

isat

ion

scor

e

Cla

rke

Bax

ter

Dav

ies

(Bul

teel

)

Boy

le

Bun

yan

Dry

den

Phi

llips

Beh

n

Hor

neck

Sha

dwel

l

Bur

net

DU

rfey

Rav

ensc

roft

Dun

ton

Findings

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0

2

4

6

8

10

Summative grammaticalization Score

Sum

mat

ive

gram

mat

ical

izat

ion

scor

e

Cla

rke

Ba

xte

r

Da

vie

s

(Bul

teel

)

Bo

yle

Bun

yan

Dry

den

Ph

illip

s

Beh

n

Ho

rne

ck

Sh

ad

wel

l

Bu

rne

t

DU

rfe

y

Ra

ven

scro

ft

Du

nto

n

lowess

grammaticalizernon-grammaticalizer

Authors, by year of birth

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1655 1665 1675

02

46

Samuel Clarke

year of attestation

gram

mat

ical

izat

ion

scor

e

1650 1670 1690

02

46

8

Richard Baxter

year of attestationgr

amm

atic

aliz

atio

n sc

ore

1655 1665 1675

02

46

8

John Davies

year of attestation

gram

mat

ical

izat

ion

scor

e

1660 1670 1680

02

46

8

(John Bulteel)

year of attestation

gram

mat

ical

izat

ion

scor

e

1665 1675 1685

02

46

8

Robert Boyle

year of attestation

gram

mat

ical

izat

ion

scor

e

1655 1665 1675 1685

02

46

John Bunyan

year of attestation

gram

mat

ical

izat

ion

scor

e

1670 1680 1690

02

46

8John Dryden

year of attestation

gram

mat

ical

izat

ion

scor

e

1655 1665 1675 1685

02

46

8

John Phillips

year of attestation

gram

mat

ical

izat

ion

scor

e1675 1680 1685

02

46

8

Aphra Behn

year of attestation

gram

mat

ical

izat

ion

scor

e

1680 1690

02

46

8

Anthony Horneck

year of attestation

gram

mat

ical

izat

ion

scor

e

1670 1680 1690

02

46

8

Thomas Shadwell

year of attestation

gram

mat

ical

izat

ion

scor

e

1670 1680 1690 1700

02

46

8

Gilbert Burnet

year of attestation

gram

mat

ical

izat

ion

scor

e

1680 1700 1720

02

46

8

Thomas D'Urfey

year of attestation

gram

mat

ical

izat

ion

scor

e

1675 1685 16950

24

68

10

Edward Ravenscroft

year of attestation

gram

mat

ical

izat

ion

scor

e

1690 1700 1710 1720

02

46

8

John Dunton

year of attestation

gram

mat

ical

izat

ion

scor

e

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12

34

56

Summative grammaticalisation score

Sum

mat

ive

gram

mat

ical

isat

ion

scor

e

lowess

Cla

rke

Bax

ter

Dav

ies

(Bul

teel

)

Boy

le

Bun

yan

Dry

den

Phi

llips

Beh

n

Hor

neck

Sha

dwel

l

Bur

net

DU

rfey

Rav

ensc

roft

Dun

ton

Legend

non-grammaticaliser, period 1non-grammaticaliser, period 2grammaticaliser, period 1grammaticaliser, period 2

Authors, by year of birth

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Grammaticalisation rate follows a bell-shaped pattern

-1.0

-0.5

0.0

0.5

individual grammaticalization rate

(all authors)

Dis

tanc

e P

2-P

1

Cla

rke

Bax

ter

Dav

ies

(Bul

teel

)

Boy

le

Bun

yan

Dry

den

Phi

llips

Beh

n

Hor

neck

Sha

dwel

l

Bur

net

DU

rfey

Rav

ensc

roft

Dun

ton

lowess

0.2

0.4

0.6

0.8

individual grammaticalization rate

(grammaticalizers only)

Dis

tanc

e P

2-P

1

Cla

rke

Bax

ter

(Bul

teel

)

Bun

yan

Dry

den

Phi

llips

Beh

n

Hor

neck

Sha

dwel

l

Bur

net

DU

rfey

Rav

ensc

roft

lowess

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1650

1660

1670

1680

1690

1700

1710

1720

0

1

2

3

4

5

Syntactic and semantic change (lowess)

Sum

mat

ive

gram

mat

ical

izat

ion

scor

e

Legend

Semantic ScoreSyntactic Score

Datapoints, chronologically

0

1

2

3

4

5

Syntactic and semantic change (lowess)

Sum

mat

ive

gram

mat

ical

isat

ion

scor

e

Authors, by year of birth

Cla

rke

Bax

ter

Dav

ies

(Bul

teel

)

Boy

le

Bun

yan

Dry

den

Phi

llips

Beh

n

Hor

neck

Sha

dwel

l

Bur

net

DU

rfey

Rav

ensc

roft

Dun

ton

Legend

Semantic ScoreSyntactic Score

Semantics: Kendall tau = 0.12, p < 0.0001

Syntax: Kendall tau = 0.13, p < 0.0001

Semantics: Kendall tau = 0.12, p < 0.0001

Syntax: Kendall tau = 0.11, p < 0.0001

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0 1 2 3 4 5

01

23

45

Semantic and Syntactic grammaticalization score

Semantic

Syn

tact

ic

lowesslinear reg.

• Linear regression: Adjusted R-squared: 0.90 , p<0.0001. Semantics and syntax co-evolve

• Lowess: syntax lags behind semantics (Heine at al. 1991:213; Givón 1991:123; Haspelmath

1999:1062; Francis & Yuasa 2008; Traugott 2008:17), then takes over

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Comments welcome

[email protected]

wwwling.arts.kuleuven.be/qlvl/freek.htm