Leaders and laggards: the intersection of
sex and gregariousness in change
Derek Denis
[email protected]
NWAV44, University of Toronto
Oct. 25, 2015
Background
Data and Methods
Results
Discussion
A pervasive finding
“Women have been found to be in advance
of men in most of the linguistic changes in
progress studied by quantitative means in
the past several decades” (Labov 2001:280)
2
Background
Data and Methods
Results
Discussion
A pervasive finding: women lead change
Percentage of devoiced /Ã/, Buenos Aires Spanish (Wolf and Jiménez 1979)
100
Percent incoming form
75
Female
Male
50
25
0
55+
36−55
24−35
18 15 12
9
Age
3
Background
Data and Methods
Results
Discussion
A pervasive finding: women lead change
Probability of quotative be like by sex and year of birth, Toronto English (Tagliamonte and D’Arcy 2007, 2009)
Fitted probabilities (logit transformed)
5
0
Sex
F
M
−5
−10
1920
1940
1960
1980
Year of Birth
4
Background
Data and Methods
Results
Discussion
Why female leaders
Descriptive vs. explanatory adequacy (Chomsky 1965)
▸
Descriptive adequacy: The theory correctly accounts for the
distribution of the data.
• “In linguistic change from below women use higher frequencies
of innovative forms than men do” (Labov 2001:292).
▸
Explanatory adequacy: The theory provides a principled
explanation for the distribution of the data.
• Factor X is a driving force of linguistic change and factor X
correlates with biological sex.
“[W]hile broad demographic correlations outline general
patterns of language use across a population, they do not
offer explanation for those patterns” (Eckert 2014:529).
5
Background
Data and Methods
Results
Discussion
Why female leaders
Probability of quotative be like by sex and year of birth, Toronto English (Tagliamonte and D’Arcy 2007, 2009)
Fitted probabilities (logit transformed)
5
0
Sex
F
M
−5
−10
1920
1940
1960
1980
Year of Birth
6
Background
Data and Methods
Results
Discussion
Paper goal
▸
▸
Explore this dispersion.
Firmly establish gregariousness as a key factor in linguistic
leadership.
• Won’t feign to provide explanation for “general [gender-based]
patterns” (Eckert 2014:529) but will explore the possibilities of
gregariousness being orthogonal to or intersecting with sex.*
7
Background
Background
Data and Methods
Results
Discussion
Leader in the rise of ‘and stuff’
Scatterplot of individuals’ normalized frequencies of ‘stuff’ GEs in York, UK (Denis 2011)
9
Background
Data and Methods
Results
Discussion
The leaders
Speaker
bB
bs
bI
ay
bA
bg
aZ
Sex
Male
Female
Male
Male
Male
Female
Female
Age
75
62
37
23
24
23
22
Occupation
Blue Collar
White Collar
White Collar
Blue Collar
Blue Collar
Blue Collar
White Collar
10
Background
Data and Methods
Results
Discussion
A gregariousness metric
Katz and Lazarsfeld (1955)
▸
Female fashion leaders have high number of friends and
belong to social clubs.
▸
Labov (2001) draws a parallel with leaders of linguistic change
and their particular social networks.
The Logic
▸
▸
Can’t go back in time...
The interviews in the York Corpus are free with respect to
topic and discussions
• The amount of discussion revolving around an interviewee’s
friends is taken to be an indicator of gregariousness.
• How important are their friendship networks?
• How much do they want to talk about their personal
relationships?
11
Background
Data and Methods
Results
Discussion
A gregariousness metric
Operationalizing “friend” (and synonyms)
▸
We can index a speaker’s gregariousness by operationalizing
the raw frequency “friend” in each interview.
▸
More “friend”s ↔ more friends ↔ higher gregariousness
Categorized into three groups.
▸
• Low Gregariousness
• Medium Gregariousness
• High Gregariousness
12
Background
Data and Methods
Results
Discussion
Gregarious leaders
Normalized Frequency of 'stuff' General Extenders
Scatterplot of individuals normalized frequencies of ‘stuff’ GEs in York, by gregariousness (Denis 2011)
bI
40
Nice... but...
30
20
▸
A post-hoc measure.
▸
Move forward analytically;
capture this data from the
participants themselves.
ay
Gregariousness
bA
a High
a Medium
a Low
bg
aZ
10
0
ah
bz
aWbh
bi aU
ai
bu
bv
ad
aN
bB
aAbp
aDbe
as
bF
aj
au
bwanaH
aE
bx ak
aL
aM
brab
bNav
aK
bc
bH
bd
ax
apaP
aq
ar
aI
aG
bG
aB
ag
ao
ba
ac
aC
bE
aFalaQ
bb
aa
bkam
aY
ae
aXaf
bM
bqazaw
bo
blatbt
aV
aR
aS
aT
bK
bLaJ bjaO
bnby
bf
bs
1920
1940
Birth Year
1960
1980
13
Data and Methods
Background
Data and Methods
Results
Discussion
Corpus design
LIN451/1151 Urban Dialectology, Winter 2015
▸
Students interviewed one (subjectively-judged) more
gregarious individual and one less gregarious individual.
• Kept the distribution by gregariousness and sex as balanced as
possible.
▸
Native Torontonians (from at least age 4).
▸
Speakers were 18 to 30 (mean = 24)
▸
Familiars
▸
Twenty-four interviews in total.
For this paper, a balanced subsample was used.
15
Background
Data and Methods
Results
Discussion
A better gregariousness metric
Survey
Friends
F1. How many friends do you communicate with on a
daily basis?
F2. How many friends do you communicate with on a
weekly basis?
F3. How many friends do you have?
F4. How many best friends do you have?
F5. How many groups of friends do you have?
Attitudes
A1. Do you make new friends easily?
A2. Do you consider yourself to be an introvert or an
extrovert?
A3. Are you a gregarious person?
16
Background
Data and Methods
Results
Discussion
Gregariousness metric
Gregariousness metric
The geometric mean of questions F1 through F5.
▸ Equal weight to each dimension despite inherently different scales.
▸ The nth root of the product of n numbers:
⎛N
⎝ i=1
• For {xi }Ni=1 , the geometric mean is ∏ xi
▸ For us: Gregariousness =
√
5
1/N
⎞
⎠
F1 ⋅ F2 ⋅ F3 ⋅ F4 ⋅ F5
Measure
# friends (speak with daily)
# friends (speak with weekly)
# of friends
# of best friends
# of friend groups
Gregariousness
A
2
4
7
3
2
3.2
Speaker
B
C
30
10
90
50
200
1000
5
2
5
6
26.7 22.7
***Gregariousness correlates with each of the Attitudes questions.
D
2
4
300
3
2
6.8
17
Background
Data and Methods
Results
Discussion
How is this not a social network index?
There is overlap but critical difference
▸
Milroy’s Network Strength Score and Labov’s Communication
Indices
• Density, multiplexity, and localization of social network.
• Named friends technique; far more sociometric; researcher
specified thresholds.
▸
Gregariousness
• Subjective and open ended.
• There is something socio-cognitively different about individuals
who report having 3 friends and having 1000 friends; talking to
4 friends in a week and talking to 90 friends in a week.
Highly likely that there is a connection but it’s not necessarily
bidirectional.
▸ More gregarious, more likely to have larger network outside
immediate community, more likely to hear innovation
▸ More likely to adopt innovation (Yu 2010, 2013)
18
London
Background
same in perception and production
different in perception and production
other
Data and Methods
Results
Windsor
Discussion
The Canadian Shift
Edmonton
St. John's
Vancouver
Calgary
Saskatoon
Sydney
Regina
Winnipeg
St. John
Thunder Bay
Montreal
SSMarie
Halifax
Arnprior
Toronto Ottawa
London
F1(e) > 650 and F2(æ) < 1825
and F2(o) < 1275
Map 15.3. above The merger of /e/ and /æ/ before intervocalic /r/
Triggering event (Labov 2010)
The minimal pair merry ~ marry is generally heard as “the same” in Canada, but
Newfoundland and Montreal stand out as different from the rest of Canada.
Merger of /o/ (lot), /oh/
(thought), and /ah/ (palm)
▸
▸
Windsor
Map 15.4. below The Canadian Shift
The dialect of Canada is defined phonologically as the area shown here, excluding the Atlantic Provinces. It is characterized by the Canadian Shift, a downward
and backward movement of /e/ and /æ/, triggered by the merger of /o/ and /oh/ in
low back position.
Brought to you by | University of Victoria McPherson Library Serials
Authenticated
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Leaves lack of phonological
backness contrast between merged
vowel and trap /æ/ (Roeder &
Gardner 2013).
Analogical dress /e/ and kit /i/
movement
19
Background
Data and Methods
Results
Discussion
uw-fronting
±Coronal split in Toronto
(Labov et al. 2006:165)
▸
/Tuw/ fully fronted.
▸
/Kuw/ moderately fronted
(relative to /uwl/).
20
Background
Data and Methods
Results
Discussion
Methodological considerations
In brief...
With respect to measuring formants, and contextual constraints
normalization etc....
▸
For Canadian Shift: following Roeder and Jarmasz (2010) on
Toronto English.
▸
For uw-fronting: following Labov et al. (2006) and Boberg
(2010).
With respect to the subsample of speakers
▸
A priori selection of subset of 12 speakers, balanced by
age, sex, and gregariousness; six speaker overlap.
21
Background
Data and Methods
Results
Discussion
Defining ‘innovativeness’
Canadian Shift
▸
Innovative speakers: lower and retracted /i/, /e/, and /æ/
• Higher F1 ↔ lower ↔ more innovative
• Lower F2 ↔ more retracted ↔ more innovative
uw-fronting
▸
Innovative speakers: advanced /Tuw/, advanced /Kuw/
• Higher F2 ↔ more advanced ↔ more innovative
• Larger F2 diff. between /uw/ and /æ/ ↔ more innovative
• “[A]n index of phonetic innovation in Canadian English, uniting
two of its most important developments” (Boberg 2010:205).
Hypothesis
Each determinant of innovation
will correlate with gregariousness.
22
Results
Background
Data and Methods
Results
Discussion
Canadian Shift: Retraction
æ
e
i
1200
●
●
●
Normalized F2 (Hertz)
●
1500
●
Gregariousness
High
1800
Low
2100
●
●
2400
Female
Male
Female
Male
Female
Male
Sex
24
Background
Data and Methods
Results
Discussion
Canadian Shift: Lowering
æ
e
i
●
●
Normalized F1 (Hertz)
900
Gregariousness
700
High
●
●
●
●
●
●
500
●
●
●
Low
●
300
●
●
●
●
●
●
●
●
Female
Male
Female
Male
Female
Male
Sex
25
Background
Data and Methods
Results
Discussion
uw-fronting: F2
Tuw
Kuw
●
2000
●
Raw F2
Gregariousness
High
Low
1500
●
Female
Male
Female
Male
Sex
26
Background
Data and Methods
Results
Discussion
uw-fronting: F2 of æ – F2 of uw
Tuw
Kuw
F2 diff. between æ and uw
●
−500
Gregariousness
High
Low
●
●
0
●
Female
Male
Female
Male
Sex
27
Background
Data and Methods
Results
Discussion
Summary
Vowel
/æ/
Stage
Early
/e/
Mid
/i/
Newer
/uw/
Earlier
Newer
Formant
F2
F1
F2
F1
F2
F1
F2 /Tuw/
F2 /Kuw/
Gregariousness
yes
no
yes
p = 0.06
yes
p = 0.07
yes
yes
Sex
p = 0.09
yes
yes
yes
no
no
yes
yes
Age
yes
no
yes
yes
yes
p = 0.07
??
??
For changes in progress...
▸
▸
▸
▸
CS retraction: Gregariousness always correlated, Sex
correlated for Mid-Range change only.
CS lowering: Gregariousness marginal, Sex correlated for
Mid Range change
Fronting of /uw/: Both Gregariousness and Sex correlate.
In no case did Gregariousness and Sex interact.
28
Discussion
Background
Data and Methods
Results
Discussion
Intersections
Given that women have been found to lead change and
gregariousness seems to play a role in linguistic leadership, we
reach a possible conclusion: women tend to be more
gregarious.
But we’re still left without explanatory adequacy.
▸ Social-psychological? Cognitive? (Yu 2010, 2013)
• A role for biology after all?
▸
Ideological?
• Being (hegemonically) feminine means being gregarious? (cf.
Bucholtz 1998)
• Being (hegemonically) masculine means not being gregarious?
30
Background
Data and Methods
Results
Discussion
Intersections?
Gregariousness
Sex
Gregariousness and sex seem to be quite orthogonal.
▸
Don’t interact in the models above.
▸
Account for variance within, not between groups.
31
Background
Data and Methods
Results
Discussion
Intersections?
Left with more questions than answers.
Where to look: Adolescent incrementation.
▸ Do girls and boys have different initial inputs (Foulkes et al.
2005; D’Arcy 2014)?
• Difference in language socialization (Ochs 1992); ideology
reenforces itself.
▸
Gregariousness is more principally related to the extent of
incrementation (Labov 2001, Tagliamonte and D’Arcy 2009)?
• King of Prussia: best predictor of how local an out-of-state
child sounded was the number of times they were named as a
friend by other children (Payne 1980).
• Milton Keynes: Children with highest degree of participation in
koinéization were “very well integrated [...], sociable, and often
cited as friends by other children” (Kerswill and Williams
2000:94).
32
Background
Data and Methods
Results
Discussion
Thanks!
▸
LIN451/1151 Urban Dialectology Winter 2015, especially
Emma Amato for her initial investigation of uw-fronting and
Erin Hall for discussion of the Canadian Shift.
▸
Matt Hunt Gardner for patience with my sociophonetic
questions and for sharing his Praat scripts.
▸
Alex D’Arcy and the Sociolinguistics Research Lab Reading
Group at UVic.
▸
Jack Chambers and Sali Tagliamonte for support while
teaching Urban Dialectology.
▸
U of T LVC Group.
This work was financially supported by a Social Sciences and
Humanities Research Council of Canada Post-Doctoral Fellowship.
33
Background
Data and Methods
Results
Discussion
Selected references
Boberg, C. 2010. The English language in Canada. Cambridge: Cambridge
University Press.
Denis, D. 2011. Innovators and innovation: Tracking the innovators of ‘and
stuff’ in York English. UPenn Working Papers in Linguistics 17.2.8.
Eckert, P. 2014. The problem with Binaries: Coding for gender and sexuality.
Language and Linguistic Compass 8(11):529–535.
Foulkes P., Docherty G. and J., Watt D. 2005. Phonological variation in
child-directed speech. Language 81:177206
Labov, W. 2001. Principles of Linguistic Change Vol. II: Social Factors.
Malden, MA.: Blackwell.
Labov, W., S. Ash, and C. Boberg. 2006. Atlas of North American English.
Berlin: Mouton de Gruyter.
Roeder, R. and L.-G. Jarmasz. 2010. The Canadian Shift in Toronto. Canadian
Journal of Linguistics 55(3):387–404.
Tagliamonte, S. A. and A. D’Arcy. 2009. Peaks beyond phonology:
Adolescence, incrementation, and language change. Language 85:58–108.
Yu, A. C. L. 2013. Individual differences in socio-cognitive processing and
sound change. InOrigins of sound change: approaches to phonologicalization
A. C. L. Yu (ed). Oxford: Oxford University Press.
Wolf, C. and E. Jiménez. 1979. El ensordecimiento del yeı́smo porteño: un
cambio fonológico en marcha. In Estudios lingüı́sticos y dialectológicos. Temas
Hispánicos. A. M. Barrenechea et al. (eds). Buenos Aires: Hachete.
34