Transcript NWAV34 Jeff Conn Of “moice” and men: The evolution of a male-led sound change Photo by John Frank Keith.

NWAV34
Jeff Conn
Of “moice” and men:
The evolution of a male-led sound change
Photo by John Frank Keith
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Sociolinguistic studies show language change led by:
Women
The interior social classes
Supported by the data from the study of Linguistic Change and
Variation in Philadelphia [LCV] (Labov, 2001)
Conformity Paradox: Women deviate less than men from linguistic
norms when the deviations are overtly proscribed, but more than
men when the deviations are not proscribed (367)
The Curvilinear Principle: Linguistic change from below
originates in a central social group, located in the interior of the
socioeconomic hierarchy (188)
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Problem variable in the LCV data: The raising of the nucleus of the
diphthong /ay/ before voiceless consonants (ay0)
Led by men
Shows no social stratification
psych
nice
man
Questions from the patterning of (ay0) in the LCV data:
Is (ay0) a counter-example to “typical” language change?
How does (ay0) progress through the speech community over time?
What about the movement on the front/back dimension of (ay0)?
If (ay0) does not behave like other vocalic changes in progress, are there
certain gender-based evaluations of this variable? That is, do certain variants
sound more masculine/feminine?
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
The current study: Of “moice” and men: The evolution of a male-led
sound change [OMM]
OMM:
Re-study of Philadelphia 30 years after LCV
Data collected from (2000-2003)
Focus on (ay0) and secondary focus on (aw)
Included self-identified gays and lesbians as part of the data set
Striving for high comparability with the original study, OMM followed the
methodology and data analysis of the LCV as discussed in Labov, 2001
Microphone and recorder differences were not taken into consideration,
but will be looked into in the future
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Sample: 65 native Philadelphians
The data: sociolinguistic interviews (at subject’s house) including formal tasks
of semantic differentials, minimal pairs tests, reading passage and a word list
Social Coding: Each speaker was coded for various social characteristics
following the LCV (see Labov, 2001 for further details) - education, occupation and
residence converted into socioeconomic class category (SEC)
 age
house upkeep
 sex
ethnicity
 education
foreign language background
 occupation
generation
 residence value
neighborhood of origin
 mobility
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Also coded for sexual orientation
Men
W omen
Gay Men
Lesbian W omen
LW C
UW C
LMC
UMC
4
7
4
6
8
6
2
4
8
8
3
5
Sexual orientation for both F1 and F2 (ay0) is not a significant social factor
predicting values as either a binary category (gay/lesbian~hetero) or a combo 4way split of sex and sexual orientation
Binary Category
Sex/Sexual Orientation Combo
F1
F2
F1
F2
p < . 0.9478
(F2) p <
0.5843
p < 0.6660
p < 0.3294
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Acoustic vowel analysis
LPC analysis in Praat
Single-point, synchronous nuclear measurements of F1 and F2
Additional auditory support for single-point selection
Vowels of all Plotnik 25 vowel classes were measured - at least 5 tokens per
class per speaker - complete vowel system for every speaker (200-500
tokens)
Data cleaned for measurement errors
Using Neary’s Log mean normalization in Plotnik, each speaker’s cleaned
system was normalized, and from these data, a mean F1/F2 for each vowel
class (and phonetic subclasses) was calculated
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Some methodological concerns for investigating a speech community in
real time 3 decades later
Subject recruitment: representative neighborhoods have changed
Updating the socioeconomic class index (SEI)
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Subject recruitment:
LCV neighborhoods selected to represent different social classes - Kensington
(NE), South Philly (S), Overbrook (W) & King of Prussia (NW)
OMM neighborhoods sampled similar areas - biggest change was substituting
Chestnut Hill/Mount Airy for King of Prussia
Self-identified gays and lesbians recruited through personal contacts (sometimes
relatives/friends of neighborhood subjects)
Men
W omen
Neigh borhood area of Philadel ph ia
South
W est
North
Northwest Northe ast
9
4
3
4
8
14
4
2
7
9
C en te r
1
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Updating the socioeconomic class index (SEI):
LCV used scale below to calculate socioeconomic score, which was used to
calcluate socioeconomic class category (SEC)
Education (E)
6
professional school
5
college grad
4
some college
3
high school grad
2
some high school
1
grammar school
Residence Val ue (R)
6
$25,000+
5
$20,000 – $24,900
4
$15,000 – $19,900
3
$10,000 – $14,900
2
$5,000 – $9,900
1
$0 – $4,900
Occu pati on (O )
6
professional, owner director of large firm
5
white collar – proprietor, manager
4
white collar – merchant , foreman, sales
3
blue collar – skilled
2
blue collar – unskilled
1
unemployed
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Methodology
Updating the socioeconomic class index (SEI):
The median residence values according to the census data have increased
from $10,600 (1970) to $59,700 (2000), so each level of the residence scale
was multiplied by 5.632 to reflect this change
According to the 1970 and 2000 censuses, the median education attainment
level changed from 10.9 years in 1970, to graduating high school or equivalent
in 2000. This reflects an overall increase in the population’s education, so 1
point was added to each SEC to account for this.
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Methodology
Updating the socioeconomic class index (SEI):
Translation of social class categories (SEC) from LCV to OMM
LCV Class
C ate gory
LW C
MW C
UW C
LMC
UMC
UC
SEI
Score
2-3
4-6
7-9
10-12
13-15
16
OMM Class
C ate gory (SEC)






SEI
Score
LW C
3-7
UW C
LMC
UMC
--
8-10
11-13
15-18
--
Jeff Conn
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Statistical Analysis
In order to examine all the independent variables at the same time, a
stepwise multiple regression analysis was conducted using the following
independent social variables:






age
sex
education
occupation
residence value
mobility
house upkeep
ethnicity
foreign language background
generation
neighborhood of origin
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Apparent Time F1 (ay0) Results
The stepwise regression analysis of (ay0) selected the following social
variables as significant factors in predicting F1 (ay0) values

age

occupation
generation
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Apparent Time F1 (ay0) Results
This model with age, occupation and generation can account for 46% of the
variation (r2 = 0.46) of F1 (ay0) in the data, with age as a significant predictor
at p < .0001
Predicted F1 (ay0)
Data show change in apparent time
650
700
750
800
14-29
30-39
40-49
age groups
50-59
60+
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Apparent Time F1 (ay0) Results
Generation score of 3 significantly higher F1 (ay0) values (non-raised
variants) than the other scores
Predicted F1 (ay0)
Occupation score of 3 has significantly lower F1 (ay0) values, while a score
of 4 has significantly higher F1 (ay0) values (not curvilinear principle)
650
700
750
800
1
2
3
4
5
6
occupation scores
Occupation scores based on regression estimates (least squares means)
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Apparent Time F1 (ay0) Results
Apparent time shows no sex differentiation or social stratification
bivariate normal elipses)
LWC
UWC
LMC
UMC
650
ay01
600
ay01
600
Sex not significant social factor
predicting F1 (ay0) - distribution
shown below (linear fit lines and p = .90
SEC not significant social
factor predicting F1 (ay0) distribution shown below
Sex = Female
Sex = Male
650
700
700
750
750
800
10
20
30
40
50
60
70
800
Age
Regression lines for each social class of
F1 (ay0) with age as a continuous
variable
10
20
30
40
50
Age
60
70
80
90
100
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Apparent Time F2 (ay0) Results
F2 (ay0) does not show age as significant social factor predicting F2 values
(no change in apparent time)
SEC does show significant effects (p<.001), but when sorted by sex, only
men show significant social stratification (p<.001) while women do not (p>.10)
F2
1500
1400
1300
1200
600
650
F1
LWC Men
700
UWC Women
UWC Men
UMC Men
LMC Men
UMC Women
750
LWC Women
LMC Women
Predicted F1/F2 (ay0) values plotted by sex and social class
800
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
OMM: Real Time F1 (ay0) Results
Transformed LCV data into comparable age groups with OMM
Predicted F1 (ay0)
F1 (ay0) in apparent time for both data sets
650
700
OMM
LCV
750
800
850
under 30
30-39
40-49
age group
50-59
60+
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Real Time F1 (ay0) Results
Added 30 years to LCV ages and combined data sets
Stepwise process selected age and sex as significant social factors (at the p
< 0.1 level) with 33.7% of variation explained by model (r2 = .337)
Predicted F1 (ay0)
Real time change shows larger decreases in F1 (ay0) followed by plateaus
of little change
650
700
750
800
850
14-29
30-39
40-49
50-59
60-69
70-79
80-89
90+
age group
Predicted F1 values of (ay0) for both LCV and OMM data sets
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Real Time F1 (ay0) Results
Sorting the data by sex, varying moments of sex differentiation
Predicted F1 (ay0)
This picture is different from apparent time analysis in Labov, 2001 in that
unified speech community in 80-89 age group
650
MEN:
Age coefficient = 1.44
r2 = 0.260
700
Women
Men
750
800
WOMEN:
Age coefficient = 1.46
r2 = 0.348
850
14-29
30-39
40-49
50-59
60-69
70-79
age group
80-89
90+
Predicted F1 (ay0) values for combined data sets sorted by sex
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Real Time F1 (ay0) Results
SEC not selected as significant factor in the regression model, but sorting
the data by SEC, age still a significant factor (p < .10 level) for each class
(change occurring in all classes)
550
LWC
600
F1 ay0
650
UWC
LMC
700
UMC
750
800
850
900
10 20 30 40 50 60 70 80 90 100 110 120
Age
Regression lines for each social class of F1 (ay0) for both studies
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Real Time F2 (ay0) Results
F2 (ay0) in combined data set - stepwise regression model selected age,
occupation, residence and education as significant social factors (p <.10)
Predicted F2 (ay0)
1300
1350
1400
1450
1500
1550
1600
14-29
30-39
40-49
50-59
60-69
70-79
80-89
90+
age group
Predicted F2 (ay0) values by age groups for combined data
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Real Time F2 (ay0) Results
Real time analysis does not show clear social stratification of this change
Predicted F2 (ay0)
Sorting the data by SEC, age only significant factor in LWC (p < 0 .0354) and
UWC (p < 0.0205)
1250
1300
1350
1400
1450
1500
1550
1600
LWC
UWC
LMC
UMC
1650
1700
14-29
30-39
40-49
50-59
60-69
70-79
80-89
90+
age group
Predicted F2 (ay0) values for both data sets by age group and SEC
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Real Time Summary
The mechanism of (ay0) raising sound change: change began by whole
community, and then sex differentiation
No clear social stratification of this variable
Only real time analysis shows F2 backing over time
F2: no sex differentiation, but social class stratification
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Subjective Reaction Test
6 “Speakers”:
Jill - 24 year old woman; Ben - 43 year old man (2 guises each)
1 other man and 1 other woman used as fillers
Sentences
3 variables investigated (aw, ay0, and neutral) X 2 sentences each
Table 6.1 SRT sentences by variable
Variable
Sentence
Name
Neu tral
Neu tral
It was a lot different from what we expected.
We bought some equip ment a couple weeks before we left.
It was quite a fight, trying to put in the two big pipes, but we
finally did it .
It was a fine sight; we got a bite to eat and got to sleep by nine.
We scouted around for wood, and found some without much
trouble.
We took down the tent and set out toward a mountain about
two hours south of us.
Diff
Equ ip
(ay0)
(ay0)
(aw)
(aw)
Figh t
S ight
Scout
Mou nt
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Subjective Reaction Test
Creating the test:
Both Jill & Ben practiced so they produce moderate Philadelphia tokens
and more extreme Philadelphia tokens (extra Philly)
Jill/Ben’s vowel system calculated through reading passage and word
list
Tokens for each guise selected from the many possibilities comparing
the extra Philly tokens within each speaker’s “regular” vowel system
Sentences spliced together from the selected tokens
Sentences were duplicated (so each sentence played two times
consecutively) and randomized
Male then female speaker alternating
Used filler speakers to make sure that no two identical sentence of
the corresponding Jill/Ben guise occurred close together
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Subjective Reaction Test
Administering the SRT
36 sentence SRT administered as part of socioling interview (sometimes
after, sometimes before)
Evaluators were told to rate each speaker (3 men, 3 women) on the
following
scale
forscales
each sentence.
Table
6.2 SRT
Job suitabi l it y
Tough ne ss
What is the highest job t his person could
hold, speaking as (s)he does?
If this speaker got into a fight, how
likely is it t hat (s)he would win?
No job
at all
Television
1 2 3 4 5 6 7 Personality
Not at
al l
l i kely
Very
1 2 3 4 5 6 7 l i kely
Mascu lini ty/Fem i nini ty
Friendl i ness
How masculine or feminine do you think
this speaker is, speaking as (s)he does?
(4 = Average/Typical)
If you got to know this speaker well,
how likely is it that (s)he would
become a good friend of yours?
Very
Feminine
Very
1 2 3 4 5 6 7 Masculine
No at
all likely
1 2 3 4 5 6 7
Very
likely
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Subjective Reaction Test
3 Analyses of SRT evaluations
1) looks at the data from all of the evaluators to see if patterns from the
matched guise aspect are revealed from the entire speech community
2), following the analysis of the LCV SRT in Labov, 2001, examines the
difference for each speaker/guise from the neutral sentence ratings to the
ratings of each variable
3) uses a series of differences in each evaluator’s ratings to uncover any
social variables which may affect the ratings
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Subjective Reaction Test
All evaluators matched guise evaluations
2-tailed, unequal variance t-tests conducted on mean evaluations for
matched guises (boxed diffs are significant at p < 0.01)
Variable: (ay0)
7
6
5.1
Rating
5
4.1
4
5.5
4.9
3.9 4.0
3.9
3.4
4.8
4.8
Jill
4.1
3.4
2.7
3
2.3
2.6 2.6
2
1
Job
Friend
Tough
Scale
M/F
Jill2
Be n
Be n2
Of “moice” and men:
The evolution of a male-led sound change
NWAV34
Jeff Conn
Subjective Reaction Test
All evaluators intraspeaker evaluations
Jill/Jill2: (Æ) - (ay0)
7
6
4.4
4.3
4.2
4.1
Jill(ay0)
Jill(Æ)
Jill2(ay0)
Jill2(Æ)
3.9 3.9
4
3.4
3.8
2.7 2.8
3
2.9
2.5
2.6 2.6
2.6 2.5
2
1
Job
Friend
Tough
M/F
Scale
Ben/Ben2: (Æ) - (ay0)
7
6
5.6
5.1
5
Rating
Rating
5
4.9 4.9
4.7
4.5
3.9
4
4.0
3.7
4.8
5.5
5.1
4.8
4.5
Ben(ay0)
4.1
3.8
Ben(Æ)
Ben2(ay0)
3
Ben2(Æ)
2
1
Job
Friend
Tough
Scale
M/F
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Subjective Reaction Test
Social factors of evaluators
Some significant factors, but not consistent
Age or sex never significant
Uniform speech community as evaluators
Jeff Conn
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
Subjective Reaction Test
SRT Summary
Uniform speech community
Male and female speaker for (ay0) evaluated on different scales but
male and female evaluators agree on this distinction and difference in
sociolinguistic expectations of men and women
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
SUMMARY
Real time support for apparent time analysis of LCV (ay0)
(ay0) backing only shown in real time
This variable shows language change progresses not linearly, but taking
large steps forward, and then relative stability
Sex differentiation not a given, but needs to be maintained at each step in
the change
NWAV34
Of “moice” and men:
The evolution of a male-led sound change
Jeff Conn
OMM: To be continued
What’s next? (To be continued at NWAV35...)
While (ay0) does not show sex differentiation or social stratification, the other
new and vigorous changes do (eyC) and (aw)
They also show a significant effect of sexual orientation
What about other changes - incipient, completed? - in Philadelphian English
Is Philadelphia becoming a Northern city and losing its Philly-ness? What
does this all mean?
Check out my website to download this presentation and find out more
details about methodology: www. jeffconn.net