NWAV 34 Jeff Conn Of moice and men

NWAV 34 Jeff Conn Of “moice” and men: The evolution of a male-led sound change Photo by John Frank Keith

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Sociolinguistic studies show language change led by: ØWomen ØThe 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)

NWAV 34 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 (ay 0) ØLed by men ØShows no social stratification psych nice man Questions from the patterning of (ay 0) in the LCV data: ØIs (ay 0) a counter-example to “typical” language change? ØHow does (ay 0) progress through the speech community over time? ØWhat about the movement on the front/back dimension of (ay 0)? ØIf (ay 0) 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?

NWAV 34 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: ØRe-study of Philadelphia 30 years after LCV ØData collected from (2000 -2003) ØFocus on (ay 0) and secondary focus on (aw) ØIncluded 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

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology ØSample: 65 native Philadelphians ØThe data: sociolinguistic interviews (at subject’s house) including formal tasks of semantic differentials, minimal pairs tests, reading passage and a word list ØSocial 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) Ø age Øhouse upkeep Ø sex Øethnicity Ø education Øforeign language background Ø occupation Øgeneration Ø residence value Øneighborhood of origin Ø mobility

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology ØAlso coded for sexual orientation ØSexual orientation for both F 1 and F 2 (ay 0) 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 Binary Category Sex/Sexual Orientation Combo F 1 F 2 p <. 0. 9478 (F 2) p < 0. 5843 p < 0. 6660 p < 0. 3294

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology Acoustic vowel analysis ØLPC analysis in Praat ØSingle-point, synchronous nuclear measurements of F 1 and F 2 ØAdditional auditory support for single-point selection ØVowels 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) ØData cleaned for measurement errors ØUsing Neary’s Log mean normalization in Plotnik, each speaker’s cleaned system was normalized, and from these data, a mean F 1/F 2 for each vowel class (and phonetic subclasses) was calculated

NWAV 34 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 ØSubject recruitment: representative neighborhoods have changed ØUpdating the socioeconomic class index (SEI)

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology Subject recruitment: ØLCV neighborhoods selected to represent different social classes - Kensington (NE), South Philly (S), Overbrook (W) & King of Prussia (NW) ØOMM neighborhoods sampled similar areas - biggest change was substituting Chestnut Hill/Mount Airy for King of Prussia ØSelf-identified gays and lesbians recruited through personal contacts (sometimes relatives/friends of neighborhood subjects)

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology Updating the socioeconomic class index (SEI): ØLCV used scale below to calculate socioeconomic score, which was used to calcluate socioeconomic class category (SEC)

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Methodology Updating the socioeconomic class index (SEI): ØThe 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 ØAccording 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.

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Methodology Updating the socioeconomic class index (SEI): ØTranslation of social class categories (SEC) from LCV to OMM Jeff Conn

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Statistical Analysis ØIn order to examine all the independent variables at the same time, a stepwise multiple regression analysis was conducted using the following independent social variables: Ø Ø Ø age sex education occupation residence value mobility Øhouse upkeep Øethnicity Øforeign language background Øgeneration Øneighborhood of origin

Of “moice” and men: The evolution of a male-led sound change NWAV 34 Jeff Conn Apparent Time F 1 (ay 0) Results ØThe stepwise regression analysis of (ay 0) selected the following social variables as significant factors in predicting F 1 (ay 0) values Ø age Ø occupation Øgeneration

Of “moice” and men: The evolution of a male-led sound change NWAV 34 Jeff Conn Apparent Time F 1 (ay 0) Results ØThis model with age, occupation and generation can account for 46% of the variation (r 2 = 0. 46) of F 1 (ay 0) in the data, with age as a significant predictor at p <. 0001 Predicted F 1 (ay 0) ØData show change in apparent time 650 700 750 800 14 -29 30 -39 40 -49 age groups 50 -59 60+

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Apparent Time F 1 (ay 0) Results ØGeneration score of 3 significantly higher F 1 (ay 0) values (non-raised variants) than the other scores Predicted F 1 (ay 0) ØOccupation score of 3 has significantly lower F 1 (ay 0) values, while a score of 4 has significantly higher F 1 (ay 0) values (not curvilinear principle) occupation scores Occupation scores based on regression estimates (least squares means)

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Apparent Time F 1 (ay 0) Results ØApparent time shows no sex differentiation or social stratification ØSex not significant social factor predicting F 1 (ay 0) - distribution shown below (linear fit lines and p =. 90 ØSEC not significant social factor predicting F 1 (ay 0) distribution shown below bivariate normal elipses) ay 01 600 Sex = Female Sex = Male 650 700 750 800 Regression lines for each social class of F 1 (ay 0) with age as a continuous variable 10 20 30 40 50 Age 60 70 80 90 100

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Apparent Time F 2 (ay 0) Results ØF 2 (ay 0) does not show age as significant social factor predicting F 2 values (no change in apparent time) ØSEC 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) F 2 1500 1400 1300 1200 650 F 1 LWC Men 700 UWC Women UWC Men UMC Men LMC Men UMC Women 750 LWC Women LMC Women Predicted F 1/F 2 (ay 0) values plotted by sex and social class 800

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn OMM: Real Time F 1 (ay 0) Results Transformed LCV data into comparable age groups with OMM Predicted F 1 (ay 0) ØF 1 (ay 0) 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+

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Real Time F 1 (ay 0) Results Added 30 years to LCV ages and combined data sets ØStepwise process selected age and sex as significant social factors (at the p < 0. 1 level) with 33. 7% of variation explained by model (r 2 =. 337) Predicted F 1 (ay 0) ØReal time change shows larger decreases in F 1 (ay 0) 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 F 1 values of (ay 0) for both LCV and OMM data sets

Of “moice” and men: The evolution of a male-led sound change NWAV 34 Jeff Conn Real Time F 1 (ay 0) Results ØSorting the data by sex, varying moments of sex differentiation Predicted F 1 (ay 0) ØThis 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 r 2 = 0. 260 700 Women Men 750 800 WOMEN: Age coefficient = 1. 46 r 2 = 0. 348 850 14 -29 30 -39 40 -49 50 -59 60 -69 70 -79 age group 80 -89 90+ Predicted F 1 (ay 0) values for combined data sets sorted by sex

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Real Time F 1 (ay 0) Results ØSEC 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 UWC F 1 ay 0 650 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 F 1 (ay 0) for both studies

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Real Time F 2 (ay 0) Results Predicted F 2 (ay 0) ØF 2 (ay 0) in combined data set - stepwise regression model selected age, occupation, residence and education as significant social factors (p <. 10) age group Predicted F 2 (ay 0) values by age groups for combined data

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Real Time F 2 (ay 0) Results ØReal time analysis does not show clear social stratification of this change Predicted F 2 (ay 0) ØSorting the data by SEC, age only significant factor in LWC (p < 0. 0354) and UWC (p < 0. 0205) age group Predicted F 2 (ay 0) values for both data sets by age group and SEC

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Real Time Summary ØThe mechanism of (ay 0) raising sound change: change began by whole community, and then sex differentiation ØNo clear social stratification of this variable ØOnly real time analysis shows F 2 backing over time ØF 2: no sex differentiation, but social class stratification

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test Ø 6 “Speakers”: ØJill - 24 year old woman; Ben - 43 year old man (2 guises each) Ø 1 other man and 1 other woman used as fillers ØSentences Ø 3 variables investigated (aw, ay 0, and neutral) X 2 sentences each

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test ØCreating the test: ØBoth Jill & Ben practiced so they produce moderate Philadelphia tokens and more extreme Philadelphia tokens (extra Philly) ØJill/Ben’s vowel system calculated through reading passage and word list ØTokens for each guise selected from the many possibilities comparing the extra Philly tokens within each speaker’s “regular” vowel system ØSentences spliced together from the selected tokens ØSentences were duplicated (so each sentence played two times consecutively) and randomized ØMale then female speaker alternating ØUsed filler speakers to make sure that no two identical sentence of the corresponding Jill/Ben guise occurred close together

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test ØAdministering the SRT Ø 36 sentence SRT administered as part of socioling interview (sometimes after, sometimes before) ØEvaluators were told to rate each speaker (3 men, 3 women) on the following scale for each sentence.

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test Ø 3 Analyses of SRT evaluations Ø 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 Ø 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 Ø 3) uses a series of differences in each evaluator’s ratings to uncover any social variables which may affect the ratings

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test ØAll evaluators matched guise evaluations Ø 2 -tailed, unequal variance t-tests conducted on mean evaluations for matched guises (boxed diffs are significant at p < 0. 01)

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Subjective Reaction Test ØAll evaluators intraspeaker evaluations Jeff Conn

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Subjective Reaction Test ØSocial factors of evaluators ØSome significant factors, but not consistent ØAge or sex never significant ØUniform speech community as evaluators Jeff Conn

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn Subjective Reaction Test ØSRT Summary ØUniform speech community ØMale and female speaker for (ay 0) evaluated on different scales but male and female evaluators agree on this distinction and difference in sociolinguistic expectations of men and women

NWAV 34 Of “moice” and men: The evolution of a male-led sound change Jeff Conn SUMMARY ØReal time support for apparent time analysis of LCV (ay 0) Ø(ay 0) backing only shown in real time ØThis variable shows language change progresses not linearly, but taking large steps forward, and then relative stability ØSex differentiation not a given, but needs to be maintained at each step in the change

NWAV 34 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 NWAV 35. . . ) ØWhile (ay 0) does not show sex differentiation or social stratification, the other new and vigorous changes do (ey. C) and (aw) ØThey also show a significant effect of sexual orientation ØWhat about other changes - incipient, completed? - in Philadelphian English ØIs Philadelphia becoming a Northern city and losing its Philly-ness? What does this all mean? ØCheck out my website to download this presentation and find out more details about methodology: www. jeffconn. net