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NWAV 35. NWAV 35 – Columbus, Ohio. Lesbians as leaders of linguistic change in Philadelphian English. Photo by John Frank Keith. Variationist sociolinguistic studies show language change led by: Women The interior social classes.

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slide1

NWAV 35

NWAV 35 – Columbus, Ohio

Lesbians as leaders of linguistic

change in Philadelphian English

Photo by John Frank Keith

slide2

Variationist 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)

Also, language and gender literature investigates the linguistic behavior of gay men and lesbians, as well as criticizes the limitations of the studies on gay and lesbian speech (Jacobs, 1996; Kulick, 2000; Moonwomon-Baird, 1997; Gaudio, 1994; Cameron & Kulick, 2003) - Problematic correlation between sexual orientation and linguistic behavior

slide3

OMM (Of “moice” and men):

    • Re-study of Philadelphia [European Americans only] 30 years after LCV
    • Data collected from (2000-2003)
    • Focus on (ay0) and secondary foci on (aw) and (eyC)
    • 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

REPEAT OF SLIDE 6

slide4

“date”

“new and vigorous” changes

“south”

“spike”

slide5

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
  • 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?

Questions from the patterning of (ay0) in the LCV data:

slide6

The current study: Of “moice” and men: The evolution of a male-led sound change [OMM]

  • OMM:
    • Re-study of Philadelphia [European Americans only] 30 years after LCV
    • Data collected from (2000-2003)
    • Focus on (ay0) and secondary focus on (aw) and (eyC)
    • 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

slide7

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
  • sex
  • education
  • occupation
  • residence value
  • mobility
  • house upkeep
  • ethnicity
  • foreign language background
  • generation
  • neighborhood of origin
slide8

Methodology

A new twist: Sexual orientation as a social factor and the Gender Index (GI)

  • Coded for sexual orientation

Ages: 29-92

Ages: 29-60

  • In order to investigate the role that socially constructed gender has on a person’s position within a language change situation, the GI was created (modeled after the SEI)
  • Had to utilize the single event interview (rather than look at intraspeaker variation) so needed to use static rather than dynamic gender aspects
slide9

Methodology

Gender Index (GI)

Why choose this type of continuum?

Language is a social behavior which exists within a set of cultural/social stereotypes and expectations

From the idea of segregated socialization of the sexes - Cultural Difference approach in Lang and Gender

(Maltz & Borker, 1982)

The GI range is from 2 (stereotypically feminine) to 9 (stereotypically masculine)

slide10

Methodology

Gender Index (GI)

GI Category based on GI scores - distribution shown below

slide11

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
slide12

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
  • {3 above separately or SEC} (Socioeconomic Class Category)
  • mobility
  • house upkeep
  • ethnicity
  • foreign language background
  • generation (2nd generation Philadelphian)
  • neighborhood of origin
slide13

Statistical Analysis

Results of gender variables for (ay0)

  • 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 4-way split of sex and sexual orientation
  • (details of (ay0) discussed at NWAV34 – see at http://www.jeffconn.net/papers.html )

So now onto (aw) and (eyC) . . .

slide14

Apparent Time F2 (aw) Results

  • The stepwise regression analysis of (aw) selected the following social variables as significant factors in predicting F2 (aw) values
  • age
  • sex
  • SEC (Socioeconomic Class Category)
slide15

Apparent Time F2 (aw) Results

  • This model with age, sex and SEC can account for 26% of the variation (r2 = 0.256) of F2 (aw) in the data, with age as a significant predictor at p < .05
  • Data show change in apparent time (reversal of direction predicted by LCV = (aw) is now backing in Philadelphia)

2200

2100

2000

Predicted F2 (aw)

1900

1800

< 30

30-39

40-49

50-59

60+

Age Group

slide16

Real Time F2 (aw) Results

  • Apparent time analysis supported by real time data when combined OMM data with LCV data (and adding 30 years to age of LCV speakers)

2200

2100

2000

1900

Predicted F2 (aw)

1800

1700

1600

14-29

30-39

40-49

50-59

60-69

70-79

80-89

90+

Age Group

Predicted F2 (aw) values by age group LCV/OMM combined data

slide17

Apparent Time F2 (aw) Results

  • When data are sorted by sex, men no longer show change in progress

(age p = 0.8948) but women still do (age p = 0.0138)

2200

2100

Women

2000

Predicted F2 (aw)

Men

1900

1800

< 30

30-39

40-49

50-59

60+

Age Group

Predicted F2 (aw) values with regression lines for age groups for each sex

slide18

Apparent Time F2 (aw) Results

  • When the variable Sex is substituted for the 4-way category Sex/Sexual Orientation (SO), this new variable is still significant predictor of F2 (aw) values at the p < .10 level (p = 0.07) [age and SEC also still significant predictors in this model at p levels of 0.0437 and 0.0652 respectively].

2200

2100

2000

Predicted F2 (aw)

1900

1800

Heterosexual

Gay Men

Lesbians

Heterosexual

Women

Men

Sex/Sexual Orientation

Predicted F2 (aw) values by sex/sexual orientation

slide19

Apparent Time F2 (aw) Results

  • Looking at just the women’s data, the picture of language is similar to one sorted by sex, although these data are sorted by sexual orientation.

2300

2200

2100

2000

Heterosexual

Predicted F2 (aw)

Women

1900

Lesbians

1800

1700

1600

< 30

30-39

40-49

50-59

60+

Age Group

Predicted F2 (aw) values for women of two sexual orientations

slide20

Apparent Time F2 (aw) Results

  • SEC - When the women are sorted by SEC, it is the LMC lesbians who are really a step ahead of their heterosexual counterparts

2200

2100

All Women

Predicted F2 (aw)

Heterosexual

2000

Women

Lesbians

1900

1800

LWC

UWC

LMC

UMC

SEC

Predicted F2 (aw) values of social class categories for women

slide21

Apparent Time F2 (aw) Results

For F2 (aw), both GI score (p = .0286) and GI CAT (p = .0631) statistically significant social factor (at p < .10 level)

Predicted F2 (aw) by GI score

Predicted F2 (aw) values by gender category

With regard to the direction of this change, non-feminine groups lead change

slide22

Apparent Time F1 (eyC) Results

  • Unlike LCV data, F2 of (eyC) does not show significant age effects (no change in progress for the F2 dimension). The stepwise regression analysis of (eyC) selected the following social variables as significant factors in predicting F1 (eyC) values
  • age
  • sex
  • SEC (Socioeconomic Class Category)
slide23

Apparent Time F1 (eyC) Results

  • This model with age, sex and SEC can account for 43% of the variation (r2 = 0.432) of F1 (eyC) in the data, with age as a significant predictor at p < .0001
  • Sex and SEC significant predictors (p = 0.0012 and 0.0004, respectively) in the raising of this vowel (lower F1 values)

400

500

Predicted F1 (eyC)

600

700

< 30

30-39

40-49

50-59

60+

Age Group

Predicted F1 (eyC) values by age groups

slide24

Add

Real Time F1 (eyC) Results

  • Apparent time analysis supported by real time data when combined OMM data with LCV data (and adding 30 years to age of LCV speakers)
    • SEC and sex not significant factors in real time analysis at p < .10 level) Couldn’t investigate sexual orientation in real time

Predicted F1 (eyC) values by age group LCV/OMM combined data

slide25

24

Apparent Time F1 (eyC) Results

  • (Sex/SO) variable has a significant effect at the p < .10 level (p value of 0.0060), and 43% of the variation is accounted for (r2 = 0.434). Both age and SEC are still significant at the p <.10 level. Lesbians show the highest vowels (represented by lowest F1 values) while gay men show the lowest vowels

400

535

500

554

576

580

Predicted F1 (eyC)

600

700

Lesbian

Heterosexual

Heterosexual

Gay Men

Women

Women

Men

Sex/Sexual Orientation

Predicted F1 (eyC) values by sex/sexual orientation

slide26

25

Apparent Time F1 (eyC) Results

  • SEC and Sex/SO: Lesbians do not show change in apparent time (age not significant factor at p <.10 level)
  • All other Sex/SO groups do show age as significant, so other groups are catching up to the lesbians with respect to raising of this vowel
  • Only men’s groups show SEC as significant factor (heterosexual men p < .01; gay men p < .07)

400

Heterosexual

Men

500

Heterosexual

Women

Predicted F1 (eyC)

Gay Men

600

Lesbian

Women

700

LWC

UWC

LMC

UMC

SEC

Predicted F1 (eyC) values by sex/sexual orientation for each SEC

slide27

26

Apparent Time F1 (eyC) Results

For F1 (eyC), both GI score (p = .0157) and GI CAT (p = .0173) statistically significant social factor (at the p < .05 level)

Predicted F1 (eyC) for each GI score

Predicted F1 (eyC) values by gender category

Similar to the curvilinear hypothesis, this analysis suggests that it is the speakers located in the interior of a masculine/feminine continuum who are leading this change (a gender curvilinear hypothesis?)

slide28

27

SUMMARY

  • With 2 variables involved in language change, lesbians show up as leaders of linguistic change
  • (aw) should be noted that this change is a reversal of direction, so lesbians being ahead may be in opposition to the heterosexual lead in the other direction
  • (eyC) is also a change involved in the redefinition of Philadelphia from a southern city to a northern one - may interact with sexual orientation
  • Labov’s depiction of leaders of language change as women who are anti-establishment, strong and the centers of their social circles may be defining a type of women captured in my data by lesbians = TOMBOYS, or women who do not define themselves by stereotypically feminine traits
slide29

28

2 B continued

What’s next?

  • Explanations of why lesbians are leaders of language change
  • Other socioling variables show the same effect of sexual orientation?
  • Is sexual orientation the true social variable or is it more likely gender?
  • Need more data on gay men to see where they pattern with respect to language change.
  • Need other studies to examine sexual orientation as a possible significant social factor in language change
  • Need to improve Gender Index to examine the role of gender socialization with respect to dialect acquisition
  • Check out my website to download this presentation www.jeffconn.net

Thank You!

slide30

29

REFERENCES

  • Cameron, Deborah and Kulick, Don. 2003. Language and Sexuality. Cambridge: Cambridge University Press.
  • Eckert, Penelope. 1989. The whole woman: Sex and gender differences in variation. Language Variation and Change 1:245-268.
  • Eckert, Penelope. 2000. Linguistic Variation as Social Practice. Oxford: Blackwell.
  • Gaudio, Rudolph P. 1994. Sounding gay: Pitch properties in the speech of gay and straight men. American Speech 69:30-57.
  • Jacobs, Greg. 1996. Lesbian and gay male language: A critical review of the literature. American Speech 71(1):49-71.
  • Kulick, Don. 2000. Gay and lesbian Language. Annual Review of Anthropology 29:243-285.
  • Maltz, Daniel N. and Borker, Ruth A. 1982. A cultural approach to male-female miscommunication. In Gumperz, John J (ed.), Language and Social Identity. Cambridge: Cambridge University Press. 196-216.
  • Moonwomon-Baird, Birch. 1997. Toward a study of lesbian speech. In Livia, Anna and Kira Hall (eds.), Queerly Phrased: Language, Gender and Sexuality. Oxford: Oxford University Press. 202-213.
  • Labov, William. 1994. Principles of Linguistic Change, vol. 1: Internal Factors. Oxford: Blackwell.
  • Labov, William. 2001. Principles of Linguistic Change, vol. 2: Social Factors. Oxford: Blackwell.
  • Milroy, Leslie. 1987. Language and social networks (2nd Ed.). Oxford: Blackwell
  • Please see my dissertation for more references and further accounts of these data.
  • Conn, Jeff. 2005. Of “moice” and men: The evolution of a male-led sound change. Ph.D. dissertation. The University of Pennsylvania. Available at my website: www.jeffconn.net
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