Child Acquisition of Sociolinguistic Variation

A Dissertation submitted to the Faculty of the Graduate School of Arts and Sciences of Georgetown University in partial fulﬁllment of the requirements for the degree of Doctor of Philosophy in Linguistics

Shannon Mooney, M.A.

ii Child Acquisition of Sociolinguistic Variation

Shannon Mooney, M.A.

Dissertation Advisor: Jennifer Nycz, Ph.D.

Abstract

This dissertation explores the acquisition of sociolinguistic variation by 5;0 to 6;0 year old children in a public bilingual immersion elementary school setting. It shows how children at this age engage in spontaneous stylistic variation during play with peers, suggesting early diffusion of non-local forms. The capacity for stylistic variation indicates an emergent sociolinguistic competence. This emergent sociolinguistic competence is then shown to play a role in phonological accommodation to peers and acquisition of a second dialect vowel system over the course of the first year at school, as, by the end of the school year, children were found to move toward the vowel system of the classmate to whom they showed the most affinity. Spontaneous child speech with classmates was recorded at monthly timepoints throughout a year of ethnographic fieldwork at the school. Vowel formants in fifteen lexical classes were extracted from the recordings to test for the presence of the traditional Eastern New England English (ENEE) dialect vowel system, as well as the vowel systems of surrounding regional dialects and vowels undergoing change in multiple North American English varieties. While a qualitative analysis reveals stylistic variation in performance of personae during roleplay, statistical modeling using classification and regression trees (CART) shows accommodation to the vowel system of a second dialect that appears to be subject to interpersonal relationships between peers as well as a potential influence of peer ethnicity.

iii A major ﬁnding from this study is the amount of linguistic variation that exists between peers in this public early education setting that draws students from across many residentially-segregated communities in a small post-industrial city near Boston. The exposure of the very young children in this study to extensive linguistic variation leads to an active role for the children’s sociolinguistic competence as they navigate relationships with peers, identity, stances, power, and development into adult-like sociolinguistic actors.

Index words: sociolinguistic development, dialect acquisition, phonological accommodation, stylistic variation, child speech, language in schools, peer learning, ethnicity, Eastern New England English

iv Dedication

For Elsie.

v Acknowledgments

Jen, we did it! Thank you for everything — our writing retreats, coffees at the cathe- dral, celebratory text messages, etc. From when I first reached out to you for advice in early 2009, you have been there for me, allowing me to find my way academically and develop an independent and interdisciplinary voice while also having my back and putting in sometimes a lot of effort just to keep me going. I am also grateful to Natalie Schilling for her guidance while I was designing and carrying out the project, as well as for her enthusiasm and engagement throughout, and for some truly restora- tive lunches. I am grateful as well to Elissa Newport for taking me under her wing and welcoming me into her lab meetings and reading groups, and for encouraging me along as I discovered and began to engage with foundational concepts in cognitive science and developmental psychology. Elissa, I also admire and am deeply grateful for your fierce advocacy for women. I am grateful to Youngah Do for serving on an earlier version of my dissertation committee while at Georgetown, as well as for our evolving collaborative relationship now that we find ourselves on opposite sides of the world. Thank you, above all, to my parents Jean and Joe Mooney, as well as Pat Mooney and Alisen Downey, whose support, love, and encouragement have sustained me through the completion of this very long project. I am also grateful for my Glover Park family, Lara Bryfonski, Lindley Winchester, Andrew Scanlan, and Nick Osmund- son. Thank you to my ‘second parents’, Kathy and Mike Lentini, who provided me with food, shelter, a car(!), and friendship during my year of fieldwork. Thanks as

vi well to staff and students at the Center for New Designs in Learning and Scholarship (CNDLS), and especially to Eddie Maloney, Maggie Debelius, and Yianna Vovides for their support, understanding, and encouragement of me while completing this work. Thank you to Caitlin Crafton, Desniq Campbell, and Adam Leader-Smith for the cupcakes, the balloons, and the hugs, and thank you, Joselyn Schultz Lewis, just for being you. I am grateful to Dr. Susan McGilvray-Rivet, and to Dr. Anna Nolin for connecting us, as well as to Framingham Public Schools administrators, teachers, aides, volunteers, and families. Thanks especially to my Kindergarten participants (now third-graders!) and their families, who will remain very special to me always. Very en- thusiastic thanks to Sarah Sybicki, who is the most amazingly brilliant and dedicated research assistant I could have ever asked for. Thanks also to all the research assistants who have contributed to the project: Annie Xie, Kenzie Offley, Daniel Wheelock, Jocelyn Alvarez, Jade Ponciano, Nimitha Kommoju, and Elizabeth Krueger. Lastly, I am grateful to the National Science Foundation DDRI Linguistics Program for their financial support of this project (Award no. 1729018).

vii Contents

Chapter 1 Introduction ...... 1 2 Context: Social and Linguistic Diversity in the Greater Boston Area . .8 2.1 The Greater Boston Area ...... 8 2.1.1 “The Most Racist City in America” ...... 12 2.1.2 Kindergarten Representation Index ...... 15 2.2 The Community: Framingham, MA ...... 19 2.2.1 Ethnic and Racial Diversity and Immigration . . . . . 20 2.2.2 Linguistic Diversity ...... 21 2.2.3 Residential Segregation by Neighborhood ...... 22 2.2.4 Dissimilarity, Isolation, and Exposure Measures . . . . 25 2.2.4.1 Dissimilarity Index ...... 26 2.2.4.2 Isolation Index ...... 27 2.2.4.3 Exposure to Other Groups ...... 28 2.2.5 Poverty and Race/Ethnicity ...... 29 2.2.6 Issues with Relying on Census Data ...... 30 2.3 Conclusion ...... 31 3 Methodology: Sociolinguistic Fieldwork for a Linguistically Diverse Ur- ban Elementary School ...... 33 3.1 Introduction to the Fieldsite ...... 33 3.1.1 Immersion Elementary School ...... 35 3.1.2 Ethnicity and Labels ...... 37 3.2 Participants and Participant Selection ...... 41 3.3 School Culture and Implications for Language Use ...... 50 3.3.1 Exposure to Spanish and English ...... 52 3.3.2 Bilingual Immersion in the School Day ...... 52 3.3.3 English Classes ...... 54 3.4 Methods of Data Collection and Data Analysis ...... 55 3.4.1 Recording Schedule ...... 57 3.4.2 Recording Equipment ...... 59 3.4.3 Data Processing ...... 61 3.4.3.1 Transcription and Alignment of Recordings . . 62 3.4.3.2 Coding and Extraction of Phonetic Data . . . 65

viii 3.4.4 Additional Data Artifacts ...... 65 3.4.4.1 Class Transcripts ...... 66 3.4.4.2 Sociomatrices ...... 66 3.4.4.3 Observation Notes ...... 67 3.4.4.4 Parent Surveys ...... 68 3.5 Conclusion ...... 68 4 The Development of Style ...... 70 4.1 Stylistic Practice ...... 73 4.1.1 Style and Stylistic Variation ...... 73 4.1.1.1 Models of Stylistic Variation and Language Change ...... 74 4.1.2 Stance and Indexicality ...... 75 4.1.3 Acquisition of Stylistic Practice ...... 78 4.1.4 Performance ...... 82 4.2 Young Children as Social Actors ...... 85 4.2.1 Participant Details ...... 86 4.2.1.1 Age ...... 86 4.2.1.2 Neighborhood and Background ...... 88 4.3 KIT, DRESS, TRAP, GOAT, GOOSE, and FOOT Vowels . . . 92 4.3.1 Front Lax Vowels KIT, DRESS, and TRAP ...... 92 4.3.2 Back Vowels GOAT, GOOSE, and FOOT ...... 93 4.3.3 California Vowel Shift ...... 94 4.4 Case Study: Acquisition of ‘rude’ ...... 97 4.4.1 The Phonetics of ‘rude’ ...... 114 4.5 Case Study: Stylization in Roleplay ...... 116 4.5.1 Normalization ...... 119 4.5.2 Performance Vowel Classes ...... 121 4.5.2.1 GOOSE and FOOT ...... 124 4.5.2.2 KIT, DRESS, and TRAP ...... 125 4.5.2.3 GOAT ...... 129 4.6 Discussion ...... 132 5 Peer Aﬃnity and Accommodation in Dialect Acquisition ...... 135 5.1 Background ...... 135 5.1.1 Input ...... 136 5.1.2 Accommodation and Second Dialect Acquisition . . . . 138 5.1.2.1 Interactive Alignment Theory ...... 145 5.1.2.2 Audience Design Theory and Communication Accommodation Theory ...... 147 5.2 Aﬃnity and Attention ...... 148 5.2.1 Testing the Role of Input ...... 148 5.2.2 Nardy et al. (2014) ...... 150

ix 5.2.3 Aﬃnity Mapping ...... 151 5.2.4 Power and Conﬂict ...... 154 5.3 Variables ...... 156 5.3.1 Low Vowel Systems ...... 156 5.3.2 Canadian Raising ...... 157 5.3.3 Coding and Extraction ...... 159 5.3.4 Normalization ...... 162 5.4 Phonetic Convergence ...... 168 5.5 Dialect Acquisition ...... 175 5.5.1 Low Vowel Systems ...... 175 5.5.1.1 Baselines ...... 177 5.5.2 Canadian Raising ...... 184 5.5.2.1 Baselines ...... 186 5.5.3 Testable Hypotheses ...... 188 5.5.4 Change to Individual Systems ...... 191 5.5.4.1 Marshall ...... 191 5.5.4.2 Sienna ...... 196 5.6 Discussion and Limitations ...... 200 6 Conclusion ...... 207 6.1 Contributions ...... 207 6.2 Discussion of Findings ...... 209 6.3 Limitations and Directions for Future Research ...... 212 Appendix A Additional Demographics Tables ...... 214 B Parent Dialect Background and Attitudes Survey Text ...... 216 C Roleplay: Full Transcripts ...... 223 D Summary Tables for Low Vowel Systems Regression Tree Models . . . . 240 Bibliography ...... 244

x List of Figures

2.1 Major roadways in Metrowest Boston (Google n.d.)...... 9 2.2 The counties of Massachusetts (U.S. Census Bureau, n.d.)...... 9 2.3 A map of towns in the Greater Boston Area...... 11 2.4 Various photographs capturing some of the angry and often violent response to school integration by white residents of affected neighborhoods. 13 2.5 This map shows school districts in Suffolk, Norfolk, and Middlesex counties colored gradiently to indicate racial diversity in the 2017–2018 Kindergarten class...... 17 2.6 A map of Framingham showing major neighborhoods...... 23 3.1 Neighborhoods of residence for 15 Kindergarteners (markers colored by homeroom) and the location of Immersion Elementary School (yellow marker)...... 47 3.2 Layout of the Kindergarten hallway and common areas on the second floor that see frequent use by Kindergarteners...... 51 4.1 The canonical positions of KIT, DRESS, TRAP, GOOSE, FOOT, and GOAT vowel classes...... 93 4.2 A diagram of the California Vowel Shift from Podesva (2011) using the description from Eckert (2008b)...... 95 4.3 The vowel spaces of Rebecca and each of her three characters, with all tokens, vowel category means, and an ellipse representing an estimated normal distribution in F1 and F2 dimensions...... 120

xi 4.4 F1 and F2 of GOOSE and FOOT per character...... 125 4.5 Front lax vowel lowering for Rebecca’s performances...... 126 4.6 Carolina’s and The Babysitter’s front lax vowels...... 128 4.7 Distributions of GOOSE and GOAT for Rebecca and her performed characters...... 130 4.8 Carolina shows no sign of performative high- or mid-back vowel fronting as The Babysitter...... 131 5.1 The interactive alignment model from Pickering and Garrod (2004). . 146 5.2 These maps from Labov, Ash, and Boberg (2005) shows the distribution of the LOT/THOUGHT merger (left), PALM/START fronting (center), and nasal short /a/ system (right) that sets Eastern New England English apart from nearby varieties...... 158 5.3 Table of Eastern New England English lexical classes and phonemic approximations from Nagy and Roberts (2004)...... 159 5.4 Raw vowel space area in F1 and F2 dimensions per participant per timepoint (Marshall)...... 164 5.5 Normalized vowel space area in log F1 and log F2 dimensions per participant per timepoint (Marshall)...... 165 5.6 Raw vowel space area in F1 and F2 dimensions per participant per timepoint (Sierra)...... 166 5.7 Normalized vowel space area in log F1 and log F2 dimensions per participant per timepoint (Sierra)...... 167 5.8 Normalized median F2 of TRAP tokens before alveolar stops by month for Marshall homeroom...... 169 5.9 Normalized median F2 of LOT tokens before alveolar stops by month for Marshall homeroom...... 170

xii 5.10 Mean F1 and F2 values by month for TRAP and LOT for Marshall homeroom, with ellipses indicating one standard deviation from the mean and individual tokens plotted in faded colors...... 171 5.11 Normalized median F2 of TRAP alveolar stops by month for Sienna homeroom...... 172 5.12 Normalized median F2 of LOT alveolar stops by month for Sienna homeroom...... 173 5.13 Mean F1 and F2 values by month for TRAP and LOT for Sienna homeroom, with ellipses indicating one standard deviation from the mean and individual tokens plotted in faded colors...... 174 5.14 Regression tree model of Carolina’s low vowel system from October. . 178 5.15 Regression tree model of Ariana’s low vowel system from October. . . 179 5.16 Regression tree model of Rebecca’s low vowel system from October. . 180 5.17 Regression tree model of Laura’s low vowel system from October. . . 181 5.18 Regression tree model of Sophie’s low vowel system from December. . 183 5.19 Regression tree models of Kendall’s low vowel system from December. 184 5.20 Regression tree models of Beryl’s low vowel system from December. . 185 5.21 Regression tree model of Sylvia’s low vowel system from December. . 185 5.22 Marshall October normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts...... 186 5.23 Sienna December normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts...... 187 5.24 Regression tree model of Carolina’s low vowel system from March. . . 192 5.25 Regression tree model of Ariana’s low vowel systems from March. . . 193 5.26 Regression tree model of Rebecca’s low vowel system from March. . . 194 5.27 Regression tree model of Laura’s low vowel system from March. . . . 195

xiii 5.28 March normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts for Sra Marshall’s homeroom. . . 196 5.29 Regression tree model of Sophie’s low vowel system from May. . . . . 197 5.30 Regression tree model of Kendall’s low vowel system from May. . . . 198 5.31 Regression tree model of Sylvia’s low vowel system from May. . . . . 199 5.32 Regression tree model of Beryl’s low vowel system from May...... 199 5.33 May normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts for Sra Sienna’s homeroom...... 200

xiv List of Tables

1.1 Hypotheses of the dissertation...... 4 1.2 The subset of Eastern New England English vowels examined in Chap- ter5...... 6 2.1 School districts where Kindergarten Enrollment for the 2017 – 2018 school year by race/ethnicity ranges between two Black or Latinx students per one white student and one Black or Latinx student per two white students...... 19 3.1 Participant metadata compiled from responses to parent surveys. Eth- nicity reflects school records and Age is age at end of school year when survey was distributed to participating parents...... 44 3.2 Language background and attitudes parent survey items, condensed and reworded for clarity, are listed here...... 46 3.3 Fieldwork dates for the project, including number of days for each monthly field visit and a description of the type of fieldwork included in the visit...... 57 3.4 The Kindergarten schedule for the 2017–2018 academic year on a day when a homeroom would have ELD...... 58 3.5 This table shows the recording schedule for homerooms based on what two days of the week they had ELD...... 59 3.6 The data sources for analysis generated from the year-long fieldwork project and subsequent preliminary data processing...... 61

xv 3.7 The corpus resulting from the fieldwork for this research project is depicted in detail...... 64 3.8 This example sociomatrix shows that at the 12:55pm timepoint, Car- olina and Laura are having a conversation while Ariana sits near them. 67 4.1 Select developmental milestones for 3, 4, and 5 year olds in the “Learn the signs. Act early.” checklists from the National Center on Birth Defects and Developmental Disabilities...... 88 4.2 American Girl...... 90 4.3 A timeline of disparaging peer evaluation adjectives from the transcribed fieldwork recordings...... 100 4.4 disgusting appears in a December recording...... 102 4.5 bad appears in two November recordings...... 103 4.6 mean appears in a December recording...... 104 4.7 mean appears in an October recording...... 106 4.8 mean appears in a May recording...... 106 4.9 rude appears in a February recording...... 107 4.10 bossy appears in a November recording...... 108 4.11 rude, gross, and bad appear in a March recording...... 109 4.12 Tokens of rude in the May recordings...... 113 4.13 Carolina and Rebecca play Babysitter and Mom...... 117 4.14 Mean formant values (Hz) and ns for each character and vowel. . . . 123 5.1 Word counts per participant from two days of recordings in Sra. Mar- shall’s homeroom – one in October and the other in March...... 149 5.2 Word counts per participant from two days of recordings in Sra. Si- enna’s homeroom – one in December and the other in May...... 149 5.3 Unidirectional affinity scores for Marshall homeroom...... 153

xvi 5.4 Unidirectional affinity scores for Sienna homeroom...... 153 5.5 The number of references coded in NVivo across all transcribed data for positive and negative instances ‘talking to participant’...... 155 5.6 Tokens of each vowel class collected from Sra. Marshall’s class data. . 161 5.7 Tokens of each vowel class collected from Sra. Sienna’s class data. . . 161 5.8 The baseline vowel systems for each participant...... 188 5.9 For each speaker, their predicted vowel system by the end of year if only input matters for accommodation or if affinity for a specific peer plays a role...... 190 5.10 Change between baseline and year end vowel systems for each participant for traditional features of ENEE dialect...... 201 A.1 Representation index figures for 2017–2018 Kindergarten enrollments of school districts in Suffolk, Norfolk, and Middlesex counties. . . . . 215 C.1 Rebecca plays Baby Cook...... 223 C.2 Rebecca plays Hairdresser...... 228 C.3 Carolina and Rebecca play Babysitter and Mom...... 234 D.1 Statistics for the hierarchical regression tree of the October low vowel system F2 data for Sra Marshall’s homeroom...... 240 D.2 Statistics for the hierarchical regression tree of the December low vowel system F2 data for Sra Sienna’s homeroom...... 241 D.3 Statistics for the hierarchical regression tree of the March low vowel system F2 data for Marshall...... 242 D.4 Statistics for the hierarchical regression tree of the May low vowel system F2 data for Sienna...... 243

xvii Chapter 1

Introduction

How do children acquire sociolinguistic variation? While language is first acquired in the home and influenced by caregivers, children ultimately come to acquire community norms (Labov 2012), with this first community influence coming from the peers they encounter in early education.1 When a child enters an early education classroom that is composed of linguistically, ethnically, and socioeconomically diverse peers, the child is exposed to patterns of linguistic variation potentially quite different from those they have been acquiring in the home setting. In these newly formed communities of children, the extent and direction of linguistic accommodation may be subject to a developing sociolingustic mechanism that associates linguistic variants to speaker social attributes, personal traits, stereotypes about the speakers, stances towards other speakers2, and potentially other speaker information. The basic mechanism underlying acquisition of variation (in sound, at least) is phonetic convergence, the process by which phonetic production shifts in acoustic space towards an input signal over the course of an interaction. The factors influencing this process are still much debated in the sociolinguistic and variationist literature.3 1As found by Chevrot, Nardy, and Barbu (2011); Barbu, Nardy, Chevrot, and Juhel (2013); Nardy, Chevrot, and Barbu (2013, 2014). 2As well as speaker-external objects and other aspects of the social world surrounding a speaker interaction. 3A full issue of Language in Society (37.2) was devoted to the debate over the relative automaticity versus role of social, linguistic, personal, cognitive, and contextual factors in linguistic convergence (Trudgill 2008a; Bauer 2008; Coupland 2008; Holmes and Kerswill 2008; Mufwene 2008; Schneider 2008; Trudgill 2008b; Tuten 2008).

1 Some scholars argue that the process is largely automatic, subject to quality and extent of input, gradually but inevitably leading to convergence between speaker groups who initially linguistically differ (Trudgill 1986).4 Yet, even the earliest empirical work on phonetic convergence (Giles 1973) showed that this process is additionally subject to various social, interactional, interpersonal, contextual, and motivational constraints, and that these same constraints could lead just as straightforwardly to divergence in the course of an interaction. Recent work has similarly shown that cog- nitively grounded factors such as salience and awareness (Auer and Hinskens 2004; Nycz 2015) and socially grounded phenomena such as indexicality (Hay and Drager 2010) can mediate or block accommodation processes among adult speakers. This dissertation will continue the study of social effects on linguistic accommo- dation5 processes, or lack thereof, by examining variation and change in the speech of a group of U.S. public school Kindergarteners over the course of one school year. The focus of analysis is the developing vowel systems of these participants, who come into the school year with heterogeneous dialects and languages spoken in the home environment, and converge on shared vowel systems with peers over the course of the year. I also explore and discuss the potential for development of adult- or adolescent-like command of style through situations of performed, or stylized, speech during roleplaying games, as has been found previously in young speakers in a more homogenous community by Slosberg-Andersen (1990). Children at the early age under study in this dissertation are still acquiring some of the most complex structural aspects of their first language (Jackson 1998), in addition to the sociolinguistic and stylistic variation present in their communities (Kerswill and Trudgill 2005) and social norms in general (Koeppen 1970). Therefore

4“If a common identity is promoted through language, then this happens as a consequence of accommodation; it is not its driving force” (Trudgill 2008a; 251). 5Convergence and divergence.

2 there are many potential areas of an individual child’s linguistic practice that may be influenced through accommodation to individual peers and community patterns, such as knowing what stylistic variants to use in what social context, or moving towards the vowel system of a second dialect to index a stance or identity. This is an interdisciplinary study which attempts to engage research across fields and subfields. The study examines how speakers develop sociolinguistic knowledge over the first year in school and explores the particular means through which this sociolinguistic knowledge comes about, positing a role for peer relationships and performance during play. It draws on findings, methods, and theories from ethnographic and corpus based studies of child acquisition of sociolinguistic variation (Foulkes, Watt, and Docherty 2001; Foulkes, Docherty, and Watt 2005; Kerswill 1996; Roberts 1997, 1994; Roberts and Labov 1995; Roberts 2018; Ochs and Schieffelin 1995), research on second dialect acquisition (Chambers 1992; Nycz 2011, 2015, 2016), studies of the development of style-shifting (Smith, Durham, and Fortune 2007; Foulkes 2010; Chevrot, Beaud, and Varga 2000; Eckert 1997; Snell 2010; Cameron 2010; Kerswill and Williams 2000; Slosberg-Andersen 1990; Buson 2017), and experimental studies on phonetic convergence (Babel 2010, 2012; Babel, McGuire, Walters, and Nicholls 2014; Campbell-Kibler 2012; Walker and Campbell-Kibler 2015; Pardo, Urmanche, Wilman, and Wiener 2017). Specifically, the study addresses the question of what happens when young children enter a new community with peers whose vowel systems differ from their own at an age where first language phonological competence is still in the latter stages of development (Sander 1972). It demonstrates that total convergence in vowel systems does not occur across an entire peer cohort (Hypothesis 2a), but is mediated by an individual child’s affinity for a given peer (Hypothesis 2b). The influence of affinity on the accommodation process (both discussed further in Chapter 5) suggests that

3 the children in this study were able to somehow link phonological production and social meaning (sociolinguistic competence) at a local level within their peer cohort

(Hypothesis 1). Evidence for an emergent sociolinguistic competence comes from phonetic variation during roleplay showing style-shifting capacity, as discussed further in Chapter 4. The main study hypotheses are summarized in Table 1.1.

Table 1.1: Hypotheses of the dissertation.

Hypothesis 1 Participants recognize a link between phonological production and social meaning (sociolinguistic competence).

Hypothesis 2a Accommodation will occur over the course of a school year. Hypothesis 2b Accommodation that occurs is motivated by aﬃnity for and alignment between friends.

The data come from ten months of fieldwork with Kindergarten students at a public elementary school in Framingham, Massachusetts, a socioeconomically, ethnically, and linguistically diverse western suburb of Boston. The collected audio recordings are combined with classroom observation data on peer relationships and affinities to provide insights about the role of peer groups in dialect acquisition, accommodation, and development of sociolinguistic and stylistic competence over the course of the school year. The analysis of data collected during the study not only confirms that some sociolinguistic and stylistic information is reproduced in a way that most likely targets adult norms, but also reveals some social meanings that may be unique to the local community of Kindergarten peers. Such a study is valuable because it documents the development of stylistic and sociolinguistic variation in phonetic and phonological variables for children during their first year at school. The findings will be discussed

4 in terms of style, salience, and indexicality in Chapter 4 and in terms of dialect acquisition and accommodation in Chapter 5. The dissertation begins at the macro-level of census data in order to situate the reader in the socioeconomic, ethnic, racial, and linguistic variation that exists in and around the community where language is to be learned (Chapter 2). First the socio-historical context around racial residential segregation is explored, especially considering the effects which linger into the present. Then, the fieldwork context of Framingham, Massachusetts is further situated using a census data analysis of the geographical distribution of communities and the continuing residential segregation within the city. The dissertation then moves onto the selection of a specific fieldsite, and makes methodological suggestions for studies of natural speech by children in public schools (Chapter 3). I describe the practical aspects of the fieldwork including protocols and timelines, and explain why this fieldsite is an appropriate place for hypothesis testing. The participants in the study are introduced and described, and the school culture is considered for its effects on language use. Finally, the methods of audio, observational, and survey data collection are described. The dissertation examines how participants acquire a style-shifting competency through performance of different identities in play, as well as the influence of certain peers who wield social power on this process (Chapter 4). Various models of stylistic variation and accounts of its acquisition are reviewed, before moving to some expectations and hypotheses for the case study of stylization in roleplay that is presented in that chapter. Finally, the dissertation looks at convergence in dialectal vowel systems over the course of the year between peers based on affinity, and finds that peers accommodate to each other along the lines of friendship and potentially also race/ethnicity

5 Table 1.2: The subset of Eastern New England English vowels examined in Chapter 5.

Lexical Class (Wells 1982) Description TRAP Nasal short /a/ system: pre-nasal tokens produced with distinctly raised F1 and fronted F2 BATH Tokens in the phonetic context of a following fricative are historically separate and retracted from TRAP in F2 START Tokens before a rhotic (orthographically -art) are fronted in F2 distinct from LOT/THOUGHT PALM Romance loanwords (e.g., pasta) and others (e.g., father)are fronted in F2 distinct from LOT/THOUGHT LOT Backs in F2 and raises in F1 to merge with THOUGHT THOUGHT Merged with LOT MOUTH Canadian Raising (see also PRICE): central- ized nucleus (raised F1) in tokens with following phonetic context of a voiceless stop

(Chapter 5). The literature is reviewed for insights on dialect acquisition and peer convergence among young children as well as adults. The same homeroom in Chapter 4 is reexamined along with an additional homeroom of data. The vowel system of the Eastern New England English dialect is introduced and individual participants’ vowel systems are analyzed for change over the course of the year at school in reference to this dialect. The Eastern New England English vowels of interest are outlined in Table 1.2 using roughly the summary provided by Nagy and Roberts (2004)(Stanford 2019; see also).

6 The selection of the specific fieldwork site for this project addresses an underrepresentation of ethnically and socioeconomically diverse communities of color in variationist sociolinguistic research, especially within the dialect region of Eastern New England. This underrepresentation is troubling given the well-documented history of racial residential segregation and racial animosity in the Greater Boston metropolitan area (Formisano 2004). A foundational study in the field of sociolinguistics rests on the premise that certain features of Eastern New England English were at one point indexical of ethnicity among Boston speakers of Irish, Italian, and Jewish descent (La- ferriere 1979), yet almost no additional work has sought to document the influence of ethnicity on perception and production of local sociolinguistic variants for non-white communities and more recent immigrant populations (but cf. Nagy and Irwin 2010; Browne and Stanford 2018; for work on the speech of African Americans in Boston). As early education classrooms redesign their environments and pedagogies to meet the needs of communities characterized by language and dialect diversity across the United States, there must be research into the effects of exposure to variation — linguistic, sociolinguistic, and stylistic — on child acquisition of language in natural social contexts. The present study has direct implications for early education teachers and administrators in Framingham Public Schools and elsewhere, as it increases knowledge about the role of speech communities in child linguistic and social development (Mallinson, Charity Hudley, Strickling, and Figa 2011).

7 Chapter 2

Context: Social and Linguistic Diversity in the Greater Boston Area

2.1 The Greater Boston Area

Before focusing on the community under study in more detail, it is important to convey its greater geographical and cultural context. As shown in 2.1, Framingham is located on the west side of Route 128 from the City of Boston, with Interstate-495 to the west, and is bisected east to west by the Massachusetts Turnpike, Route 9, and the Massachusetts Bay Transportation Authority (MBTA) commuter rail Boston- Worcester line. Its centrality among major roadways in and out of Boston places it unquestionably as one of the western suburbs. It can also be considered part of the Greater Boston Area, which is mostly believed to extend to all towns within the I-495 outer loop.1 Boston and its surrounding communities are divided into four counties, as shown in Figure 2.2. Suﬀolk County contains only Boston and the cities of Chelsea, Winthrop, and Revere to the east, while the rest of the direct Boston suburbs are contained in the bordering counties of Norfolk (extending west and south from Quincy) and Middlesex (extending west and north from Cambridge). Middlesex County, which contains Framingham, is bordered by the New Hampshire state border to the north

1Some limit the Greater Boston Area to only towns within the Route 128 inner loop; this would mean that, for example, Newton would be considered part of the Greater Boston Area while Wellesley would not.

8 Figure 2.1: Major roadways in Metrowest Boston (Google n.d.).

and I-495 to the west, while Norfolk County is bordered by the Rhode Island state border to the west and Plymouth county to the south.

Figure 2.2: The counties of Massachusetts (U.S. Census Bureau, n.d.).

9 In this way, the county demarcations make a split between the northern and the southern suburbs of Boston, with the western suburbs being divided in a jigsaw pattern between the two counties. Yet the county boundaries are not especially salient in the popular conception of the region, where the more relevant split is made between northern, southern, and western suburbs of Boston, corresponding to the MBTA (“T”) subway lines that serve the different communities: the northern suburbs are serviced by the orange line, the southern suburbs have the red line, and the western suburbs are connected to Boston by the green line. This division of the Boston suburbs into roughly northern, southern, and western towns also corresponds to parishes, as shown in Figure 2.3. The salience of this three-way division reflects general community knowledge about what populations live where in and around Boston, knowledge rooted in a history of ethnic segregation that started with earlier waves of European immigration to the United States. Immigrants of Italian nationality tended to reside in the northern suburbs, Jewish immigrants tended to reside in the western suburbs, and Irish immigrants tended to reside in the southern suburbs. This geographic distribution of ethnic communities is described in some of the early sociolinguistics literature on the Boston area (Laferriere 1979). Although residential distributions of European Americans have become more diffuse and overlapping within the areas and within communities, these demarcations of the areas still hold in the imaginations of many lifelong Bostonians, and are wielded with pride by the descendants of Italian, Irish, and Jewish groups who live in the area. This division of the suburbs is even maintained and repurposed to make sense of newer waves of migration: Southeast Asian and Caribbean immigrants (southern suburbs), Latin American immigrants (northern suburbs), and largely educated, middle-to-upper class ‘WASP’2 migrants from

2White Anglo-Saxon Protestant

10 elsewhere in the United States (western suburbs).3 Unlike other large cities in the Northeast, Boston was not a prominent site of settlement for African Americans during the Great Migration or afterwards, and Black people continue to be a minority in Boston. The Boston Globe newspaper reported in 2017 that out of the 23% of the Greater Boston Area who are Black, 36% are of Afro-Caribbean rather than of African American descent, where the term ‘Afro-Caribbean’ indicates a relatively recent personal or family history of immigration to the United States from a Caribbean country.

Figure 2.3: A map of towns in the Greater Boston Area. The regions in the ﬁgure represent parish regions, but also approximate regions of suburbs according to the conceptions of Boston area residents. Framingham, a small city in the western suburbs, is highlighted (Archdiocese of Boston 2018).

3The popular perception of patterns of settlement of certain groups into northern, southern, and western suburbs is obviously a vast oversimpliﬁcation of the true complexities in the data.

11 2.1.1 “The Most Racist City in America”

Boston is popularly referred to as one of the most racist cities in America. In late 2017 the Spotlight Team, a group of Boston Globe journalists famous for their investigation of child abuse in the Catholic Church approximately two decades ago, turned their focus to the problem of racism in Boston in a series called Boston. Racism. Im- age. Reality. (Johnson, Wallack, Dungca, Kowalczyk, Ryan, Walker, and Wen 2017). In articles covering healthcare, education, real estate, sports, and access to government services, the journalists investigated and exposed quantitative correlates of the structural and institutional racism underpinning Boston’s mainstream reputation for racism.4 One example illustrating the level of racial tension in Boston was the response to the public school desegregation policy in the 1970s and 1980s (1974-1988), informally known as busing, that led to street riots, violence against young people of color, white ﬂight to the suburbs, and huge increases in enrollment for private Catholic schools in the Boston area as a generation of white children were pulled out of the Boston Public Schools system by their parents. School desegregation in Boston came about because of a court ruling that the racial segregation of the Boston Public Schools was in violation of the 1965 Racial Imbalance Act enacted by the state legislature (The Commonwealth of Massachusetts 1965).5 Out of the 55 schools in violation of the Act, 44 were in the City of Boston. The

4Referenced in joke form by Michael Che on Saturday Night Live (“the most racist city I’ve ever been to”), John Oliver on Last Week Tonight (in reference to the anti- white nationalist demonstration in summer 2017 in the hopes that it might “finally make Boston unracist”), and Trevor Noah on The Daily Show, who devoted a full segment to asking white Red Sox fans about Boston’s racist culture. 5The text of the act, the first attempt at fighting racial residential segregation in schools in US history, reads “racial imbalance shall be deemed to exist when the percent of nonwhite students in any public school is in excess of fifty percent of the total number of students in such school”.

12 Figure 2.4: Various photographs capturing some of the angry and often violent response to school integration by white residents of aﬀected neighborhoods. Top left: Boston, September 14, 1974, author unknown; Top right: ‘The Soiling of Old Glory’, Forman (1976); Middle left: South Boston, October 4, 1974, Boston Globe archives; Middle right: Boston, 1974, author unknown; Bottom left: From Masur (2008); Bottom right: South Boston, September 12, 1974, Associated Press.

13 solution to desegregation devised by the court was to compulsorily transport children from schools in Black neighborhoods (e.g., Roxbury, Mattapan, western Dorchester) to schools in Irish American neighborhoods (e.g., West Roxbury, Roslindale, Hyde Park, South Boston, eastern Dorchester), and vice versa. Though operable until 2013, it was overseen by the court system only through 1988. Not until 2013 did the Boston School Committee replace the policy with a solution involving fewer cases of compulsory busing. Angry and violent responses to school desegregation (mostly on the part of white Bostonians; see Figure 2.4) weakened over the decades following the 1970s, but this does not mean that racial resentment against people of color disappeared. The Spot- light Team cite a nationwide survey undertaken by a marketing firm that asked a sample of African Americans what the most unwelcoming city to people of color was. Boston topped the list with 54% of respondents indicating it was the most unwelcoming, distantly followed by Charlotte, Philadelphia, Chicago, and San Francisco. Racism is further reflected in inequalities at the population level. For example, the Boston Globe Spotlight team uncovered during their investigation that the median net worth of white families in the City of Boston was $247,500. In comparison, the average net worth of Black Boston residents was only $8. These figures indicate the tremendous amount of debt and lack of property systematically constraining generations of Black residents of the city. The Spotlight Team further found that enrollment of Black students at all the city’s major universities has not risen in the past three decades (remaining at <5% of enrollment), and that only 1% of corporate board members in the city’s private industry sector are Black.

14 2.1.2 Kindergarten Representation Index

Despite the best eﬀorts of the legislative and judicial rulings of the past 50 years, many Greater Boston Area school districts remain racially segregated since many towns also remain so. Figure 2.5 shows school districts in the Greater Boston Area and is color-coded for the extent of over- or underrepresentation of Black, Latinx, and white students, given that the regional average proportion for Suﬀolk, Norfolk, and Middlesex counties is roughly one ‘non-white’ (Black or Latinx) resident per two white residents. The gradient colors on the map correspond to a public school district Kindergarten representation index. The representation index is a proportion of non-white Kindergarteners to white Kindergarteners in each district in 2017–2018. The data informing the representation index come from the Massachusetts Depart- ment of Elementary and Secondary Education Kindergarten Enrollment Report for the 2017–2018 school year, last updated on January 12, 2018. Blue on the map represents school districts where Black and Latinx Kindergarteners outnumber white Kindergarteners at a rate of more than 2 Black and Latinx Kindergarteners per 1 white Kindergartener, with the blue color increasing gradiently in intensity to indicate greater underrepresentation of white Kindergartners in a given district. In the green-colored districts, enrollments range between 2 Black and Latinx Kindergarten- ers per 1 white Kindergartener to 2 white Kindergarteners per 1 Black or Latinx Kindergartener. The green districts are districts that could be described as overall ‘diverse’ – these range between 2 Black/Latinx students per 1 white student to 2 white students per 1 Black/Latinx student. The red-colored districts are ones where there are more than 2 white Kindergarteners per 1 Black or Latinx Kindergartener, and the color increases gradiently in intensity as the underrepresentation of Black and Latinx Kindergarteners increases– up to just 1 Black or Latinx Kindergartener per

15 100 white Kindergarteners. Specific representation indices per district can be found in Appendix A. The category ‘non-white’ in the calculation of the index is made up of the sum of enrolled Latinx and Black Kindergarteners for each district, and excludes Asian American Kindergarteners, Native American Kindergarteners, Pacific Islanders, and Kindergarteners of other ethnicities that may be regarded or self-identified as ‘non- white’.6 It also conflates self- and other-identified ‘white’ and ‘non-white’ Latinx students into a non-white category. Nevertheless, even if the index itself may be un- reliable with regard to specific proportion of white to non-white students cited per district, the overall impression of the figure holds, as the extreme underrepresentation of non-white students in the vast majority of districts would only be exaggerated by the alignment of white-identifying Latinx students with the rest of the white student population. The regional average population-level demographics across the three counties is two white residents per one Black or Latinx resident, so the amount of variation in representation of the Black and Latinx populations in the Kindergarten enrollment per district indicates different distributions across towns and cities by race/ethnicity. While a few districts, mostly in Suffolk County and including the City of Boston itself, reflect a large non-white majority in students, they are far outnumbered by the 6While Black and Latinx residents may experience and interact with some of the negative effects of the structures of racial oppression in the Greater Boston Area in some similar ways, the nature of how Asian Americans, Native Americans, and Pacific Islanders experience structural oppression is not as obvious in this regional context. This may be due, in the case of Asian Americans, to a mixed valency of stereotyping which is not parallel to the over- whelmingly negative valency of stereotyping faced by Black and Latinx residents in this area and in national discourse (Mok 1998). In the case of Native Americans and Pacific Islanders in the region, due to the smaller size of the populations, there is likely some variation in how structural oppression is experienced by members of these groups. In any case, this particular dissertation relies on data in which none of the three racial/ethnic groups– Asian American, Native American, or Pacific Islander– are represented by participating individuals in a way that is known to the researcher.

16 Figure 2.5: This map shows school districts in Suﬀolk, Norfolk, and Middle- sex counties colored gradiently to indicate racial diversity in the 2017–2018 Kindergarten class. Green districts have from at least 1 Black/Latinx Kinder- gartener enrolled for every 2 white Kindergarteners, while red districts have fewer than 1 Black/Latinx Kindergartener enrolled per 2 white Kindergarteners. Blue districts have at fewer than 1 white Kindergartener enrolled for every 2 Black/Latinx Kindergarteners.

17 smaller towns in Middlesex and Norfolk Counties where the Kindergarten enrollment demographics are disproportionately skewed towards overrepresentation of white students and underrepresentation of Black and Latinx students. The representation index does not attempt to account for neighborhood-level residential segregation, which can lead to greater levels of school segregation by race and ethnicity even within the same town. Given such widespread segregation in the region, only a few locations could potentially provide the right setting in which to investigate the core research question of this dissertation — how sociolinguistic variation is acquired in a diverse setting. Specifically, only 11 of the 71 total towns and cities throughout all three counties exhibit a 2017–2018 Kindergarten enrollment that is demographically within two white students per nonwhite student to two nonwhite students per white student. These 11 are colored green in Figure 2.5, and listed in Table 2.1; a full ranking of all 71 localities can be found in Appendix A. These districts were the initial focus of the search for a field site, as they present the optimal context for examining acquisition of variation where mixing of multiple dialects and ethnolects of English may take place. Though it was difficult to locate a diverse school in the Boston area, the location of a field site in this region was important to examine the variable acquisition of a dialect with as distinct a vowel system as Eastern New England English, which contrasts with most other varieties of American English. Contacts were ultimately established within Framingham Public Schools that allowed for a year-long study with an ethnographic component.

18 Table 2.1: School districts where Kindergarten Enrollment for the 2017 – 2018 school year by race/ethnicity ranges between two Black or Latinx students per one white student and one Black or Latinx student per two white students.

District County Latinx Black White Other Total Revere Suﬀolk 304 28 208 37 577 Lowell Middlesex 372 69 311 386 1138 Marlborough Middlesex 182 19 160 30 391 Malden Middlesex 93 78 142 155 468 Waltham Middlesex 186 33 218 50 487 Somerville Middlesex 143 41 188 55 427 Cambridge Middlesex 84 108 280 174 646 Framingham Middlesex 204 58 389 69 720 Avon Norfolk 7 11 27 3 48 Stoughton Norfolk 35 45 133 30 243 Lincoln Middlesex 25 11 68 17 121

2.2 The Community: Framingham, MA

Framingham is a small post-industrial city of approximately 70,000 people, about one-tenth the size of Boston. It is located 20 miles west of Boston, just inside of the Interstate 495 loop. Despite being home to Framingham State University, it is not a wealthy suburb, in contrast to the other western suburbs of Boston such as We- ston, Dover, Sherborn, Sudbury, Wellesley, and Wayland, which have the highest per capita income in the state of Massachusetts. While the Framingham average annual household income of $70,000 mirrors that of the state as a whole, the percentage of the population living in poverty, at 11.2%, is slightly larger than the state average of 10.4%.7 Per capita income in the city averages $33,000, compared to a per capita

7All demographic data presented in this section come from the 2012–2016 American Community Survey (ACS) except where noted (e.g., 2010 census).

19 income of $75,000 to $100,000 in bordering towns. Framingham was officially a town- ship up until January 1st, 2018, when it became a city and elected as its first mayor Yvonne M. Spicer, the first African-American mayor in the history of Massachusetts.

2.2.1 Ethnic and Racial Diversity and Immigration

Census data reveals the city of Framingham to be the most ethnically and linguistically diverse city or town in the area immediately west of Boston. Twenty-six percent of the population of Framingham are ﬁrst-generation immigrants to the United States, and 37% primarily speak a language other than English at home. In 2016, as much as 18% of the population of Framingham had moved to the town from elsewhere within the previous year, and 20% of them had immigrated directly from abroad. While in Massachusetts as a whole one out of seven businesses is minority-owned, in Framing- ham it is one out of 5. While the populations of neighboring towns can be up to 95% white non-Hispanic/Latino, Framingham is just 67% white non-Hispanic/Latino. Within the non-white population in Framingham, approximately 20% are African American non-Hispanic/Latino, 25% are Asian, and fully 50% are Hispanic/Latino.8 Framingham also has the largest, and still growing, Brazilian population in Mas- sachusetts, though there is similar growth in the Brazilian population in many cities and towns in Massachusetts since the 1980s. Brazilians make up 5% of the population of Framingham, similar in size to the Puerto Rican population.9

810% of the population of Framingham consider themselves to be two or more races. 9Immigration from Portuguese-speaking countries has a long history in Massachusetts beginning with Azorean whalers and the whaling economy, as discussed extensively in Labov (1963). Brazilians are a newer immigrant population in the Boston area, with immigration beginning around the 1960s and including a large wave of arrivals in the mid-1980s due to the collapse of the Brazilian economy. Boston is home to more Brazilian immigrants than any other United States major metropolitan area, perhaps due partially to the draw of a large and long-settled Portuguese speaking population, with established Portuguese- speaking communities and businesses. As of 2010 Framingham claimed a larger Brazilian

20 Corresponding to trends in immigration and, to a degree, ‘white ﬂight’, there has been a lot of ethnic and racial change in Framingham between the 1990 census and the 2010 census, despite a population increase of only 3,000 during that time. The ‘diversity index’ of the city, which ranges from 1-100 and measures the presence of multiple ethnic groups in a metropolitan statistical area (Iceland, Weinberg, and Steinmetz 2002), has jumped in that time from 36.1 to 68.5, indicating a large increase in the ethnic make-up of the town. Despite a limited population increase, the percentage of white non-Hispanic residents of the town has decreased from 95% to 65% between 1980–2010, which corresponds to about 17,000 white residents leaving the town. Non- Hispanic Black residents and Asian residents make up a steadily increasing, but still small, percentage of the town population (3% in 1980 to 6% in 2010 and 3% in 1980 to 7% in 2010 respectively), and those designating themselves as ‘Other’ or more than one race in the census went up from 0% in 1980 to 10% in 2010, outnumbering both the Asian and non-Hispanic Black populations. The Hispanic population increased in the same time period from 8% to 14% of city residents, an increase of over 4,000 people.

2.2.2 Linguistic Diversity

The languages spoken in the city as a primary home language reﬂect its diversity, with 24,000 out of the 65,000 residents speaking a language other than English (or in addition to English) at home, which is roughly 2 out of every 5 Framingham residents. Spanish (8,500 speakers, 13% of town) and Portuguese (7,800 speakers, 12% of town) are roughly equally robust, but Portuguese speakers are more likely than Spanish speakers to have a limited proﬁciency in English — 45% of all Spanish population than the City of Boston, making it “one of the most Brazilian places in the US” (Skorczeski 2009).

21 speakers reported limited proﬁciency in English, while 55% of Portuguese speakers did the same. Other language communities present in smaller numbers in the city (but still with more than 400 speakers) are Russian, French/Creole, Gujarati/Hindi/Other Indic, Chinese, Arabic, and African languages.

2.2.3 Residential Segregation by Neighborhood

As shown in Figure 2.6, Framingham can be roughly divided into four quadrants, as it is intersected by the Mass Pike (Interstate 90, the thick red line on the map) that runs from east to west through the center of town, the Sudbury Reservoir (the body of water to the left of Downtown on the map) that separates the southwest of Framingham from the southeast, and the forests and state parks that separate the northwest from the northeast. If the Mass Pike forms the division between northern and southern Framingham, the quandrants are delimited east and west by, roughly, Winter Street in the south and Edgell Road in the north. The neighborhoods of Framingham are somewhat racially and ethnically segregated, correlating with a long history of socioeconomic and residential racial segregation in the Northeastern United States (Charles 2003), as well as Framingham’s recent immigration history. The southeast is the most densely populated area of Framingham and contains within it the Downtown Framingham / Framingham Center neighborhood, which has been the commercial center of the town since the 1880s when the railroad running between Boston and Worcester was built. In the 1980s, the factories that had anchored the economy of the town closed, causing devastation to the commercial district and the town as a whole. The commercial district was not revived for over 2 decades, until the early 2000s when an inﬂux of Latino and Brazilian residents revitalized the neighborhood with businesses catering to Latino and Brazilian clientele.

22 Figure 2.6: A map of Framingham showing major neighborhoods. Taken from (Explore Our Communities | Choose Framingham, MA - Oﬃcial Website n.d.).

23 Today, southeast Framingham is the area of the city where many Latino and African American residents live. Low-income housing and subsidized apartments are clustered in the adjacent neighborhoods of Framingham Center and Coburnville. The other three quadrants of the town, containing the neighborhoods of Woodcrest Acres (southwest), Nobscot (northeast), Saxonville (northeast), and the large area comprising North Framingham, are demographically mostly white. The southwest of the town, containing the wealthy neighborhood of Woodcrest Acres, is separated from Coburnville and Framingham Center by the Framingham Reservoir, and populated by old Victorian mansions. Nobscot and Saxonville, on the other side of I-90 from Framingham Center, are two socioeconomically distinct neighborhoods despite their adjacency to one another. Nobscot is another wealthy neighborhood that also houses Framingham State University. Saxonville contains densely populated suburban neighborhoods with cookie-cutter houses largely built in the 1950s and 1960s. The northwest of the town is mostly farmland and forests. “North Framingham” is a catch-all term for areas north of I-90 that are not considered part of either Nobscot or Sax- onville. It is not as densely populated as any of the other neighborhoods and contains large swathes of protected forest. Residential segregation impacts the exposure to and, conversely, isolation of, socioeconomic, racial, and ethnic groups in Framingham as it does in surrounding areas. For the Cambridge–Newton–Framingham MSA, socioeconomic segregation has been higher than the national average since the 1990s, with also less income variation by neighborhood than the national average. The amount of socioeconomic segregation in this MSA is rapidly increasing. There was a substantial increase in the socioeconomic segregation of the poorest 10% of families in the 1980s that was unmatched by the national average, and since then it has outpaced the national average every decade.

24 Meanwhile, the socioeconomic segregation of the most aﬄuent 10% of families has stayed constant over time. If the intersection of race and socioeconomic segregation is further examined for the 1980–2010 censuses, we ﬁnd that increases in the extent of socioeconomic segregation (Massey and Denton 1988) of the poorest 10% of white families stays parallel with the change in the national average over time, while the residential socioeconomic segregation of the poorest 10% of Black families is approximately double the national average over the past 30 years, and the socioeconomic segregation of the poorest 10% of Hispanic families is one-and-a-half times the national average over the past 30 years.10

2.2.4 Dissimilarity, Isolation, and Exposure Measures

Three measures are commonly used to quantify the extent of racial residential segregation across census tracts in a given area: dissimilarity, isolation, and exposure (Massey and Denton 1988). The data available for these measures come from the 2010 census and the 2005–2009 ACS (data from the 2012–2016 ACS were not available). Dissimilarity, isolation, and exposure measures were calculated by the Diversity and Disparities project at the Spatial Structures in the Social Sciences program at Brown University. Though the measures rely on mathematical formulae (Appendix B of the U.S. Census Bureau’s publication Racial and Ethnic Residential Segregation in the United States: 1980–2000 ), the mathematical formulae will not be themselves reported here, but each measure will rather be described holistically.

10Poor Asian families in this area largely defy the pattern of increased socioeconomic residential segregation of the non-white poor, with a lower extent of socioeconomic segregation of the poorest 10% of Asian families than the national average.

25 2.2.4.1 Dissimilarity Index

The dissimilarity index ranges on a score from 0–100 and describes whether one group in a given census area is distributed across census tracts in the same way as another group. According to the Diversity and Disparities project, any score above 60 on this measure is considered to be a high level of racial residential segregation. A score of 60 indicates that 60% or more of the members of one group would have to move to a diﬀerent census tract in order for the group to be evenly distributed with the other groups in their census tract. Values of 40 to 50 (40% to 50% of the group would have to move to have an even distribution) are considered to represent a moderate level of segregation, and values of 30 or below (less than 30% of a group would have to move) are considered fairly low. All comparisons detailed below are between two racial/ethnic groups in the city. Framingham receives scores representing a moderate level of segregation between Black and white (39.7), Hispanic and white (51.5), Black and Asian (40.3), and His- panic and Asian (54.9) groups. In contrast, there are low levels of segregation between white and Asian (16.2) and Black and Hispanic (31.4) groups. The population dynamics can be further illuminated through taking a longitudinal view of the dissimilarity index using census data from 1980–2010. The extent of segregation between Black and white residents of Framingham has been steadily increasing since the 1980s from a low segregation level. The same can be said for the extent of segregation between Black and Asian residents. In contrast, the moderate extent of segregation between Hispanic and white Framingham residents has largely stayed the same since the 1980s (and the same goes for the moderate extent of segregation between Hispanic and Asian populations). The low level of segregation between Black and Hispanic households has also remained about the same since the 1980s.

26 2.2.4.2 Isolation Index

The isolation index is a measure of the probability that a given person from one racial or ethnic group will share a census tract with a person from another racial or ethnic group. It is another way to measure residential segregation that focuses more on the average for individual experience than the dissimilarity index, which captures population-level redistribution. The scores range from 0-100, with scores closer to 0 representing a very small group that is very dispersed across census tracts, and scores closer to 100 representing complete isolation of a group to a single census tract where no other group lives. Practically, the isolation index scores are usually inevitably lower for smaller racial or ethnic groups and higher for larger racial or ethnic groups, so it is sometimes not seen as as reliable of a measure as the Dissimilarity Index. The white population in Framingham is the most isolated group according to this measure. It is also the largest in Framingham, with an isolation index of 75, meaning that the average white person lives in a census tract that is 75% white. This is 10 percentage points higher than the white population percentage of the city (65%), indicating some residential segregation in the white population. The same goes for the Asian population, with a slightly higher score of 10 on the isolation index than the percentage of the population in Framingham (7%). The Black population, a small group in the city relative to whites and Latinxs, has an isolation index of 7 corresponding to the Black population which makes up 6% of Framingham. According to the measure, a given Black person will live in a census tract with a Black population that is roughly proportional to the overall Black population of the town. In contrast, there seems to be much more isolation of Latinx communities, with an isolation index of 25.4 relative to a population percentage of 14% of Framingham residents.

27 2.2.4.3 Exposure to Other Groups

Another measure of residential segregation by census tract is exposure to other groups. This measure, like the isolation index, is on a scale of 0–100, where a larger value corresponds to a given ethnic or racial group member living in a census tract with a higher percentage of a specific other group. This measure, like the isolation index, is sensitive to overall group populations, so that if a group is small, the measure will tend to find higher exposure to a large population group, and if a group is large, there is seen to be lower exposure to a small population group. Because of this, the dissimilarity index is normally used over this measure or the isolation index to obtain a view of racial and ethnic residential segregation that is not as subject to population size. For the purposes of viewing the extent of racial and ethnic residential segregation in the city of Framingham, though, the measure of exposure may be most relevant to the research questions of this dissertation. Another advantage of this measure is that it allows, like the dissimilarity index, a direct comparison between two ethnic or racial groups. Unlike the dissimilarity index, though, it bases itself on the average individual experience of a given member in one of those groups of the other group, rather than on inequalities in population-level distribution across census tracts. This measure will therefore be especially useful for establishing a key assumption of the dissertation that an individual child entering public school Kindergarten will have been exposed to less sociolinguistic, linguistic, and ethnic variation before entering Kindergarten than they will encounter in a school which is more representative of the overall population of the town. Framingham census figures for 1980 and 2010 indicate a huge decrease in the measure of exposure of Blacks to whites in the city (a drop from 91 to 58). This roughly can be taken to mean that for a given member of the Black racial group, out

28 of every 100 people living in their census tract, in 1980 91 were white and in 2010 58 were white. Presumably this drop, like other demographic trends, has continued in the decade following the 2010 census. Similarly for Hispanics in Framingham, exposure to whites dropped from 86 to 49 between 1980 and 2010. The drop in Asian exposure to whites was not as drastic between 1980 and 2010, with a decrease in the exposure measure of 94 to 69. Meanwhile, the self-identifying Black racial group experienced a rise in exposure to Hispanics, with, in 2010, 18 out of 100 people in a given Black resident’s census tract being Hispanic. For a given Hispanic resident, 10 out of 100 people in their census tract are Black. For comparison, a given white person will have only 1 out of 100 people in their census tract be Black, 10 out of 100 people in their census tract be Hispanic, and 7 out of every 100 people in their census tract be Asian. When taken together with the overall population demographics breakdown by race and ethnicity for the city, these numbers show a systematic tendency of the town to have some census tracts where the Black and Hispanic population largely lives (though there are some whites and Asian residents in these tracts as well). Meanwhile, other census tracts are predominantly populated by white residents, with some Asian residents as well. This gives a view of racial and ethnic residential segregation of the Black and Hispanic residents of the town, but, from this analysis of the census data, there still seems to be potential for exposure to whites in a given census tract overall, as the white population seems to be more diﬀusely distributed throughout the town.

2.2.5 Poverty and Race/Ethnicity

The 2016 American Community Survey (ACS) estimate for poverty status by race in Framingham reveals a strong correlation between poverty and race/ethnicity in this area. While 7% of the white population (and 6% of the Asian population) live in poverty, 35% of the Black population and 27% of the Hispanic population of the

29 city do. For Hispanic residents this is sometimes naïvely explained by pointing to immigration patterns, since first-generation immigrants often hold low income jobs upon arrival in the United States. Indeed, even for Black residents of Framingham, it is unclear whether there is also an intersectional differential by national origin status, as the numbers in this table of the 2016 ACS do not partition Black non-Hispanic and Black Hispanic individuals, and, moreover, there is a large first- (and second-) generation Caribbean population in the Greater Boston Area who are often Black- identifying but may not identify as African-American. Based on the discussion in Section 2.1 and the sheer size of the gap itself, it is reasonable to suspect that national origin and length of time in the United States does not entirely determine the large racial and ethnic disparity in poverty, and to conclude that patterns of racial and ethnic residential segregation relate partially to differential income potential in the context of the Greater Boston Area that comes about, as in other metropolitan areas of the United States, through both historical factors and synchronic racial and ethnic bias by institutions, structures, and individuals.

2.2.6 Issues with Relying on Census Data

It is likely that census greatly undercounts the number of undocumented residents in Framingham. A person of undocumented residential status may be reasonably afraid to interact and provide details about their employer, income, house, and family to the federal, state, or local government. This is a problem for any estimation of the overall counts, segregation indices, and poverty levels experienced by ﬁrst-generation families who have undocumented members (Passel 2005).

30 Another issue with relying on census data is that Brazilians represent a large cultural proportion of Framingham yet have no response category on the census where they are able to indicate Brazil specifically as a country of origin. Consequently, Brazilian residents may not know whether to classify themselves as ‘Hispanic’ or not. They face the confusing situation that they are from South America, similar to other Latino populations, but do not typically speak Spanish. When it comes to questions about race/ethnicity, they must classify themselves and their family according to the categories ‘White Non-Hispanic’, ‘Black Non-Hispanic’, ‘Hispanic’, or ‘Other’. A Brazilian or Brazilian-American respondent’s answer to what ethnic category they belong to is thus unpredictable as it is based solely on what that respondent takes to be the meaning of the ‘Hispanic’ category. The size of this immigrant group that, in this area, faces economic and xenophobia-based struggles similar to those faced by newly immigrating communities from other Latino countries, is thus unknown. In fact, the only census instrument capable of being used to estimate the size of this group is the data on language spoken at home (Language Spoken at Home, Table B16001) in the ACS, where a first-generation Brazilian American family will most likely respond that Portuguese is spoken in the home, with accompanying limited proficiency in English).

2.3 Conclusion

This chapter showed the extent of racial, ethnic, and socioeconomic segregation in Framingham through a variety of measures. It also provided some general history of the particular ethnic, racial, and linguistic groups in the region and in the town of Framingham. Even though the Framingham Public School district as a whole is one of the few districts in the Boston area that is reﬂective of and proportional to the overall

31 distribution of racial groups in the region, there is some segregation by neighborhood within the district which could lead to potential segregation of individual schools within Framingham. The following chapter will present more information on how Framingham Public Schools navigates this issue, and introduces the school within the district that was ultimately ideal for testing the hypotheses of phonological acquisition from peers in a multiple dialect setting. An early education school reflective of the ethnic, national, and socioeconomic diversity broadly found in this area, rather than reflective of the residential segregation of particular neighborhoods, is a suitable fieldsite for studying the impacts of multiple dialects and varieties of English on how children will acquire aspects of language (in particular the Eastern New England English regional dialect vowel system) and will begin to develop a stylistic repertoire in this environment. As the fieldsite described in the next chapter is a microcosm of this broader diversity, rather than a school delimited by residential segregation, it enables the study of dialect acquisition in a socially, linguistically, and sociolinguistically variable environment.

32 Chapter 3

Methodology: Sociolinguistic Fieldwork for a Linguistically Diverse Urban Elementary School

This chapter describes the public elementary school which served as the fieldsite for this study and the methods of data collection and analysis. I address some specific factors affecting the social and linguistic dynamics at the school, such as its ethnic and linguistic diversity, its bilingual Spanish-English immersion programs, and its majority ‘economically disadvantaged’ student population who enroll from residentially and socioeconomically segregated communities. After describing the fieldsite, I introduce the participants in the study and present the sources of data informing the analysis, before providing a detailed description of the methods of data collection and processing.

3.1 Introduction to the Fieldsite

As discussed in the previous chapter, the school integration policy introduced to remedy school segregation, mandatory bussing, was met with controversy and violence in previous decades. The Commonwealth of Massachusetts Department of Elementary and Secondary Education (DESE) has since attempted to reduce racial and ethnic segregation instead via an inter-district school choice program. Framingham does not participate in this state-wide initiative; instead, it implements its own “school- choice” program in which families living anywhere in Framingham can apply through

33 a lottery system to send their children to any of the elementary or middle schools in the district.1 The Framingham Public Schools Policy Manual (last updated by the Framingham School Committee in June 2012) includes a “Racial Balance Policy” (Section J, File JCAA) that contains a mission statement, an excerpt from which reads:

The Framingham School Committee believes that attendance in schools which reﬂect the racial and ethnic diversity of our community promotes students’ understanding, appreciation, and acceptance of per- sons of various racial, ethnic, and cultural backgrounds. The ability to learn and work with individuals of diverse backgrounds is an important skill for success in the world. In accordance with these beliefs and the Massachusetts laws governing racial balance (Chapter 636 of the Acts of 1974, M.G.L. Chapter 71, Sec- tions 37C and 37D), it is the policy of the Framingham School Committee that each elementary and middle school shall enroll a student body that is racially balanced. Racial balance shall mean that each student body shall include a percentage of minority students which reﬂects the system-wide percentage of minority students, plus or minus ten percent.

The policy guarantees that all elementary and middle school student bodies at schools in the district are roughly equivalent to the district-wide student population demographics (7% African American, 5.1% Asian, 27.1% Hispanic, 56.8% White). Most children do not attend formal pre-school before enrolling in kindergarten. Par- ents and school oﬃcials informed me that families lacking the ﬁnances to pay for

1There is only one high school, which comprises Grades 9 through 12. Elementary schools in Framingham comprise Kindergarten through Grade 4, and middle schools comprise Grades 5 through 8.

34 early education in years prior to Kindergarten are likely to instead take advantage of caregiver networks for daycare, or may make the tough ﬁnancial decision to have a parent stay home with the child. Massachusetts has no state-wide legislation requiring free public Pre-K options, but some Framingham parents may pay tuition for a Pre-K program called B.L.O.C.K.S. (Building Learning Opportunities for Children’s Kindergarten Success). The number of students who attended this Pre-K program was 273 in the 2016–2017 school year, out of 720 who went on to enroll in Kindergarten in the 2017–2018 school year, meaning that only one out of every three children in the 2017–2018 Kindergarten class received a public Pre-K education (Massachusetts Department of Elementary and Secondary Education DESE 2018). In informational materials on the program, tuition rates for full-day public Pre-K during the 2016– 2017 school year were reported to be $848 per month, making it an unrealistic option ﬁnancially for many working families. Thus the typical early education experience in Framingham presents an ideal test site for studying child sociolinguistic development during primary exposure to a diverse input environment: the racial residential segregation and lack of public Pre-K makes it likely that children acquire a variety mostly shaped by that of their caregivers and immediate neighborhood (Labov 2014), while the public school policy enforcing diversity in Kindergarten places children in a context where they are likely to receive new and varied input.2

3.1.1 Immersion Elementary School

The participants in my study are students in the 2017–2018 Kindergarten class at Immersion3 Elementary School in Framingham, Massachusetts. Immersion Elemen-

2See Chapter 2 for more discussion the city’s population demographics and for an extended description of the six main residential neighborhoods. 3Pseudonym.

35 tary School is a public Spanish-English immersion elementary school, meaning that students spend part of each day learning in Spanish and part of each day learning in English. Immersion, like all elementary schools in the Framingham Public School District, is a choice school, meaning that families can apply from all over the city of Framingham to have their children attend this school. The most recently published race/ethnicity demographics for enrollment at Immersion Elementary School4 show that, out of 681 Kindergarten through 5th graders, 4% were African American, 70% were Hispanic, 23% were white, less than 1% were Asian, and 3% were multi-race non-Hispanic.5 Administrators and teachers at Immersion allowed access to students and classrooms at the school throughout the school year lasting from September 2017 through June 2018. Planning for the study in partnership with the district began in August of 2016, with the study evolving over the course of the following year to reflect researcher, administrator, and district needs and constraints. The timeline for study set-up prior to September 2017 included approximately six months of vetting of the protocol by the district, five months of discussion with the school principal, and an additional last round of suggested revisions to the protocol from the head of the En- glish language department at the school approximately a month before the start of fieldwork. Many changes were made to the original study design over time through conversations with school and district gatekeepers. For example, the final round of requested study protocol revisions included a ‘soft-open’ on the project, where, in lieu of the

4The 2017–2018 school year, which is the year the research team was present in the school. 5These race/ethnicity categories align with the categories used in the federal census discussed in detail in the preceding section, and are consequently problematic or potentially non-representative in similar ways. See Chapter 2 and Subsection 3.1.2 of the current chapter for additional discussion of this point.

36 planned individual lavalier microphones on participating students, only classroom recorders would be used for the entire first month of fieldwork, with lavalier microphones used in an increasing number of classes and days beginning with one class on one day in October. This limits the reliability of the conclusions that can be drawn from each study participant’s first individual recording, which was initially intended to serve as their sociolinguistic baseline. Similar practical and ethical constraints on the study suggested by gatekeepers arose throughout the course of the fieldwork. This chapter presents an account of the research protocol, which reflects these methodological complexities, changes, and their rationale, whenever relevant.

3.1.2 Ethnicity and Labels

Table 3.1 captures three broad categories of ethnicity among study participants, corresponding to the three categories selected from in Framingham Public Schools notation, which are designed to match state and federal race/ethnicity categories. The relevant categories used in the census and by the Massachusetts Department of Elementary and Postsecondary Education district profiles and student registration are ‘African- American/Black’, ‘Hispanic/Latino’, and ‘White’ (Massachusetts Department of Ele- mentary and Secondary Education DESE 2018). These ethnic/racial categories seem to be problematic on multiple levels. Problems include the conflation of distinct ethnic identities of major cultural groups in the local area, the mis-naming of groups, and the marginalization of those that fit in multiple categories or no category. In the Boston area, as discussed in Chapter 2, there are many recent Caribbean diaspora communities. Some members of these communities self-identify as Black and/or Caribbean, but not African American. The use of ‘African American’ to refer to an ethnically diverse population can marginalize those who share both the experience of being Black in the United States and the experience of a Caribbean and/or

37 Afro-Caribbean cultural heritage. In this dissertation, when it is necessary to refer to an individual or a community who may identify as Black, African American, and/or Afro-Caribbean, the inclusive descriptor ‘Black’ will be used in addition to relevant descriptors signifying cultural, ethnic, regional, or national backgrounds. A similar issue is encountered in regard to the ethnic group referred to as ‘His- panic/Latino’ on the census and school registration forms. There is widespread rejection of the term ‘hispanic’ among Latinx activist communities due partially to its colonialist implications of Spanish dominance (Salinas Jr and Lozano 2019). More- over, the use of the term ‘hispanic’ rather than ‘Latinx’ could imply that this group is united in speaking the Spanish language or having a Spanish colonial history. In Massachusetts moreso than other states, a large proportion of the Latinx population is made up of those with a Brazilian cultural heritage or Brazilian nationality. It is possible that these residents and those with a family immigration history from other Portuguese-speaking areas could see their ethnic identities as falling outside of the term ‘hispanic’. In addition, I have chosen to use the term ‘Latinx’ instead of ‘Latino’ or ‘Latin@’ because ‘Latinx’ is not marked for gender in the Spanish language and therefore does less to marginalize non-male gender and non-binary gender, respectively, than the preceding two terms with the ‘latin-’ stem (Salinas Jr and Lozano 2019). Using any one name to encompass diverse ethnic groups discursively minimizes the variation in cultures– and sociolinguistic practices– among distinct ethnic communities with diverse cultural heritages and immigration histories (Freire and Macedo 1995), so all attempts will be made to identify participants and cultural groups by local community aﬃliation, usually corresponding to family national heritage, but sometimes with dialectal and other sociolinguistic groupings where known. A naming practice based in family national heritage appears to be preferred by some community

38 members themselves, based on my experience engaging with community businesses and events largely organized around or otherwise signaling national pride among communities containing recent and ancestral immigrant families. In interaction with the residents of the city, school community members, parents, and even the young participants, I consistently observed that individuals tended to refer to themselves by their or their ancestors’ nationality, and the cultural heritage that may imply, rather than by using one of the broad labels applied to them on the census and district forms. Even when referring to businesses or neighborhood blocks, the nationality or cultural heritage of the owners/clientele would be used (e.g., “a Salvadoran bakery”, “a Brazilian corner store”, “a Dominican coﬀee shop”), rather than their membership in a Latinx and/or Black ethnic group. The exception to this tendency is that when macro-ethnic categories like ‘Black’ and ‘Latin@’6 were brought up, such as in a conversation about racism and politics, when community members were talking about Latinx and Black people as national groups, residents often alluded to their self-identiﬁcation with a macro-category. To summarize the impact of these decisions on the way ethnic groups are described in this dissertation, I assume that the divisions into ‘Latinx’, ‘Black’, and ‘white’ are imposed on individuals and communities by the structures and dispositions of US society, and then may be either adopted or not adopted by people in those communities depending on interactional context. The conception of ethnic identity here is thus best understood in the sense advocated by Bucholtz and Hall (2005; 585):

(1) Identity is the product rather than the source of linguistic and other semiotic practices and therefore is a social and cultural rather than

6I did not ever hear a community member themselves use the word ‘Latinx’, but have chosen to do so anyways in this dissertation out of a scholarly commitment to feminist epistemology (Bernal 1998).

39 primarily internal psychological phenomenon; (2) identities encompass macro-level demographic categories, temporary and interactionally specific stances and participant roles, and local ethnographically emergent cultural positions; (3) identities may be linguistically indexed through labels, implicatures, stances, styles, or linguistic structures and systems; (4) identities are relationally constructed through several, often overlapping, aspects of the relationship between self and other, including similarity/difference, genuineness/artifice and authority/delegitimacy; and (5) identity may be in part intentional, in part habitual and less than fully conscious, in part an outcome of interactional negotiation, in part a construct of others’ perceptions and representations, and in part an outcome of larger ideological processes and structures.

The idea developed in this dissertation assumes that children display complex emergent cultural and social identities. The work therefore avoids, wherever possible, the categorization of participants into macro-ethnic categories. Besides being problematic in the ways detailed above, among others not described, the reliance on broad ethnic categories for analysis in this study would also preclude one of the objects of the study, which is a ground-up investigation of what stances, perceptions, styles, and self-understandings are actually being encountered and navigated by the young participants in the form of phonetic and morphophonological variation. Though the dissertation begins with a thorough grounding in analyses of the census data that make use of broad racial categories that may be problematic and marginalizing in the ways described above, additional speciﬁcity and nuance are enabled by my ethnographic work at the ﬁeldsite.

40 3.2 Participants and Participant Selection

27 Kindergarteners ultimately participated in this study. When the study began in September, the children ranged in age from about 5;2 to 5;11; when data collection ended in May, they were approximately 5;9 through 6;6.7 While the goal was to have six participants per homeroom in the five Kindergarten homerooms at Immersion Elementary, consent forms were distributed to more than six families per homeroom asking permission for their child to participate, and all children whose parents returned signed permission forms were included in the study. As a result, between three and eight students participated in each of the five Kindergarten homerooms. Overall, 66% of participants were girls (18), with only 9 male participants. All real names, including teacher names, have been replaced with pseudonyms in this study to protect the privacy of the Immersion school community and the confidentiality of personal data guaranteed to the participants and their families. In the 2017–2018 Kindergarten class, 64 (52%) of the 122 students are classified as ‘Economically disadvantaged’. Students categorized as economically disadvantaged by the Massachusetts Department of Elementary and Secondary Education participate in at least one of the following programs: the Supplemental Nutrition Assistance Program (SNAP), the Transitional Assistance for Families with Dependent Children (TAFDC), the Department of Children and Families’ (DCF) foster care program, or MassHealth (Medicaid). Each of these programs is provided by the U.S. federal government or the Commonwealth of Massachusetts government to assist low-income families and children. This statistic about the Kindergarten population at Immersion implies that, in addition to being racially and ethnically diverse as an intentional re-

7All numbers are approximate due to only partial survey completion by the parents of the participant population.

41 flection of the city’s racial and ethnic diversity, the students are also socioeconomically diverse. There are also many second-language English speakers at Immersion, among both the student population and those who are teachers. 67 out of the 122 Kindergarteners (55%) meet the Massachusetts Department of Elementary and Secondary Education’s diagnostic for ‘Limited English Proficiency’ (LEP) English language learners. Most of the students who fall within this designation are first-language Spanish speakers, but some Kindergarteners may instead have Portuguese as a first language, as there are many Brazilian families who call the city home (as discussed in greater detail in Chapter 2). Because of the study’s focus on acquisition of sociolinguistic variables in English, participants were selected based on performance on the WIDA8 English language proficiency screening tool (Gottlieb, Cranley, and Cammilleri 2007) in Spring/Summer of 2017 prior to the first day of Kindergarten. The WIDA Screener, as the tool is called, is used by the school to split all students, both native and non-native speakers of English, into two tracks for their English Language Development (ELD) classes, which are described in more detail below. The Kindergarteners are scored on a scale between 1 and 6 based on their proficiency in listening and speaking during the test administration period, with 1 being the lowest proficiency and 6 being the highest proficiency. One ELD track contains Kindergarteners who scored between 1 and 3, and the other contains Kindergarteners who scored between 4 and 6.

8World-class Instructional Design and Assessment, a consortium of states agreeing to Common Core instructional design and assessment standards. The Common Core was developed in 2009 by the Council of Chief State School Oﬃcers (CCSSO) and the National Governors Association Center for Best Practices (NGA Center) as a set of standards used in states to benchmark and assess learning at each grade level. The Common Core has been adopted by 41 states including Massachusetts, where WIDA has also been adopted.

42 Study recruitment efforts were restricted to parents of students in the higher- proficiency ELD track (scores of 4 to 6 indicating native or near-native proficiency in English). Homeroom instructors distributed to these parents notices of the opportunity to consent to have their child participate. I did not ask for access to individual student scores on the WIDA due to data privacy concerns around test scores. De- spite the participating students’ reported and directly observed high proficiency in English, many parents were not comfortable speaking English, and some reported in a survey distributed towards the end of the year that English was not spoken in the home. Consequently, the dividing line commonly drawn between individual native and non-native English-speaking children is overly simplistic in this case, and such a characterization will not be employed in reference to the children participating in this study. That said, this study does include native and non-native speaker participants. The presence or absence of English spoken at home, and, if present, the specific variety of English, greatly influences the ultimate results for individual participants in the study in complex ways, which will be described in more detail in Chapter 5.

43 Table 3.1: Participant metadata compiled from responses to parent surveys. Ethnicity reﬂects school records and Age is age at end of school year when survey was distributed to participating parents.

Characteristics

Child (Homeroom) Ethnicity Gender Age (y;m) Neighborhood Language of Neighbor- L2 English Parent (L1) Parent with “Boston ac- hood cent”

Conor (Rojo) White M 6;3 Woodcrest Acres English Matilda (Rojo) White F 5;11 North Framingham English Helen (Rojo) Latinx F 6;1 Nobscot English X (Portuguese) Marianna (Rojo) Black/Latinx F 6;6 Framingham Center Spanish X (Spanish) Ryan (Rojo) White M ?? Jorge (Rojo) Latinx M ?? Kiki (Rojo) White F ??

Alayna (Green) White F 5;9 Coburnville Portuguese X Kirsten (Green) White F 6;0 Nobscot English

44 Kaylin (Green) Latinx F ??

Ariana (Marshall) White F 5;10 Saxonville English X Carolina (Marshall) White F 6;6 Coburnville Portuguese Laura (Marshall) Latinx F 6;4 Framingham Center Spanish X (Spanish) Rebecca (Marshall) Latinx F ??

Kendall (Sienna) Black F 5;10 Portuguese X (Haitian Creole) Sophie (Sienna) Black F 6;2 North Framingham English X Timothy (Sienna) White M 6;0 Coburnville Portuguese X Benjamin (Sienna) Latinx M ?? Gordon (Sienna) White M ?? Sylvia (Sienna) White F ?? Tanisha (Sienna) Latinx F ?? Beryl (Sienna) Latinx F X (Spanish)

Allison (Ventura) White F 6;1 Coburnville Portuguese Jeffrey (Ventura) Latinx M 6;3 Saxonville English X (Spanish) Georgina (Ventura) Latinx F 6;4 Saxonville English X (Spanish) X Jaden (Ventura) Latinx M 6;5 Framingham Center English X (Spanish) Andrew (Ventura) Latinx M The information reported about participants is largely taken from a parent survey that was sent home at the conclusion of the academic year of fieldwork. The specific items to which caregivers responded appear paraphrased in Table 3.2. The full survey text appears in Appendix B. The categories of survey items inquire about child linguistic and regional/national background, adult linguistic and sociolinguistic background, and the survey respondent’s linguistic and sociolinguistic attitudes and folk linguistic perceptions. The information provided about the child and family background on the parent survey combined with child’s patterns of speech in the early months of the school year suggested a baseline for the language acquisition process which this study sought to observe during the Kindergarten year. The survey items, including open-ended responses provided by the survey takers, were assembled into participant metadata. The participant characteristics generated by the responses to an item or a combination of items are listed in Table 3.1 along with homeroom, gender, and ethnicity. I decided that ethnicity would be an unnecessarily sensitive question to ask parents to provide on such an instrument given the political climate of 2017. Instead, I gathered this information by asking school administrators about the relevant section of participants’ school registration records. I replaced the categories on the school registration records (e.g., ‘African American’, ‘Hispanic’) with ethnic identity terms consistent with the study, as discussed further in Section 3.1.2. In addition to language background and age in years and months, survey responses identified the neighborhood in which participants live.9 The 15 children whose parents responded to the survey are fairly equally distributed across Coburnville (4) and Framingham Center (3), the diverse low-income neighborhoods making up the major-

9This information is not available for children whose parents failed to complete the end- of-year parent surveys.

45 Table 3.2: Language background and attitudes parent survey items, condensed and reworded for clarity, are listed here. Full survey appears in Ap- pendix B.

Items

Child’s age in years and months (at end of Child language background: school year) Framingham neighborhood(s) of current residence(s) Town and state, or country, of any of the child’s previous residence(s) since birth and approximate ages and durations at each location Prior knowledge of Spanish, if any (at home or at previous school speciﬁed) Knowledge of additional languages besides Spanish and English and environment in which learned

Accent/dialect/language spoken by adult (mul- For each adult in the home: tiple choice and open-ended) Other comments (open-ended)

Language attitudes and folk Neighborhood/community language/accent perceptions: Geographic boundary marking diﬀerent variety from local Diﬀerent languages/accents/dialects in Fram- ingham and what neighborhoods Additional information about languages, accents, and dialects (open-ended)

46 Figure 3.1: Neighborhoods of residence for 15 Kindergarteners (markers colored by homeroom) and the location of Immersion Elementary School (yellow marker).

ity of the southern part of Framingham, and Saxonville (3), Nobscot (2), and North Framingham (2), the wealthier and less diverse northern part the city. One child, Conor, lives in Woodcrest Acres, a relatively wealthy white neighborhood in the far southwest of town. Neighborhood assignment was based on an item on the parent survey that asks for the child’s residential address. This information reveals potential inﬂuences on dialect acquisition such as neighborhood socioeconomic information, ethnic and linguistic communities present, and potential exposure to variability in language prior to attendance at Immersion Elementary. For additional information on the socioeconomic and cultural proﬁles of the neighborhoods, refer to the section in Chapter 2 on residential segregation by neighborhood in Framingham.

47 Survey items also elicited information about participant linguistic backgrounds, asking parents questions about the mainstream language of the neighborhood in which they live, the language(s) spoken in the home, and the accent/dialect with which En- glish is spoken in the home (if at all). There was almost complete agreement on what the mainstream language of each neighborhood was. Moreover, the reported neighborhood language in all cases except one coincides with the output of analyses of census-level data on segregation in the previous chapter. Coburnville was systematically described by all four parents as Portuguese-speaking, while Framingham Center was described as Spanish-speaking by two out of the three parents.10 Nobscot, Sax- onville, and North Framingham are all identified as English-speaking by all parents of children who live there. Of the 15 respondents, 8 reported that at least one caregiver of the child spoke with the child in a language other than English. Of those 8, 6 reported speaking Spanish to their child. In addition, Helen’s mother reported that the entire family speaks only Portuguese, and Kendall’s mother reported that Haitian Creole is the sole language spoken at home. Some of the children with Spanish or Portuguese spoken at home live in the English-speaking neighborhoods with high levels of white residents as identified in the earlier census data. Helen’s family lives in Nobscot, and Jeffrey and Georgina’s families live in Saxonville. Only five of the children’s families contain speakers with a self-reported ‘Boston accent’.11 In the cases where a respondent does report a Boston accent in the home, those survey responses categorically identified a spouse as having “a worse one” in

10The third child lives close to the boundary between Framingham Center and Saxonville; thus perhaps there is overlap in the communities, or the boundary between communities should be placed further south than it is characteristically placed. 11Described as Eastern New England English in this study and elsewhere (e.g., Stanford 2019).

48 the cases that the spouse was also an L1 English speaker. This observation about the self-reported strength of accents among spouses does not generalize to cases where both are identified as having “Spanish-accented English” or similar. The observation suggests that there may be social pressure for a parent to downplay their own Eastern New England English (ENEE) dialect vernacularity compared to others, suggesting that there could be local prestige associated with not having an ENEE dialect. The ‘Boston accent’, like many regional dialects, tends to be heavily stigmatized, even in the Greater Boston Area, as being “obnoxious” (Nagy and Irwin 2010). An additional consideration is that the surveys were categorically filled out by mothers. It could be true that these women do speak closer to a standard, supra-regional variety of English, as has been found in many variationist studies (see Labov 2001b; Trudgill 1972; Milroy and Milroy 1992; Eckert 2008a; on the “gender paradox”). Another factor that could lead to underreporting of Boston accents in the data could be that people who have features unique to Eastern New England English believe nonetheless that they speak ‘Standard American English’, due to their lack of knowledge of what features are dialect-specific and the differential salience among ENEE dialect features (Stanford, Severance, and Baclawski 2014). All L1 English parents reported being “from” Massachusetts, so it is possible that many of them use at least some features of Eastern New England English without awareness or identification. In sum, students arrive in the Kindergarten classroom with a diverse set of linguistic backgrounds and experiences with community and caregiver language attitudes that may influence the type and extent of linguistic variation and change that takes place over the course of the school year.

49 3.3 School Culture and Implications for Language Use

At Immersion, the Kindergarten is set off in a hallway separate from the other grades, which each also have their own hallways at the school. The layout of the school leads to each grade functioning as its own community – the Kindergarteners interact with other Kindergarten homerooms, but rarely see their peers in higher grade levels. The Kindergarten hallway is the hallway closest to the school entrance and main office, so it sees a lot of foot traffic in the form of visitors and administrators, as well as students from other grades using bathroom passes or visiting the nurse’s office. The layout of the school is depicted in fuller detail in Figure 3.2. From the first few weeks of school, Kindergarteners are inculturated into Immersion-specific practices, such as certain chants to show willingness to pay attention, and the reward system of “suns”, where an individual or a class will receive a paper stamp with a picture of a sun on it in recognition of good behavior. They also receive exposure to and quickly adopt what must be more general elementary-school preferred behaviors, such as adopting silence in hallways, during naptime, and when a teacher starts speaking, standing and walking in single-file lines, raising hands to ask questions, etc. They learn the school song in music class, they learn which of their classmates have older siblings in higher grades or mothers12 who work or volunteer in the school, and who those older siblings and mothers are, they learn to clean off their trays at lunch, and they learn to use lockers. Kindergarteners are encouraged by school practices and policies to converge on preferred behaviors and to act as a coherent group, which can serve to encourage linguistic convergence and coherence as well (e.g., Giles, Howard, Coupland, Nikolas, and Coupland, Justine 1991).

12I did not see any fathers volunteer.

50 Figure 3.2: Layout of the Kindergarten hallway and common areas on the second ﬂoor that see frequent use by Kindergarteners. The research team hub was located in the library, and microphones were attached to participants in the cafeteria.

51 3.3.1 Exposure to Spanish and English

The L1 Spanish or Portuguese speaking children who have been designated as Limited English Proﬁciency begin to learn English in Kindergarten, if those who were ﬁnan- cially able to attend daycare or preschool did not already begin learning a second language there. The L1 English speaking children who enroll at the school are somewhat more likely to have had previous exposure to Spanish in daycare or preschool situations, given that their enrollment in Immersion Elementary is evidence of their parents’ interest in the language and/or the importance their parents ascribe to bilingualism/multilingualism. As there is no fully Spanish-medium option for Spanish language elementary schools in the Framingham Public Schools system, the same assumptions cannot be made regarding the motivation for enrollment at Immersion for children from predominantly Spanish-speaking families and households. In any case, exposure to and tolerance of a second language — whether Spanish or English — and a concomitant tolerance of linguistic and other diversity is yet another cultural practice that entering Kindergarteners are socialized into. Increased exposure to one of two languages necessarily carries with it an increased exposure to one or multiple dialects of that language, along with exposure to other dialects of the language spoken at home, creating a complex acquisition situation from truly variable input.

3.3.2 Bilingual Immersion in the School Day

Bilingual immersion at the school is structured in terms of classrooms and teachers, so that there were set rooms, times, and people to whom the students knew to speak Spanish or English. The morning is spent solely in the homeroom, where the homeroom teacher facilitates the bulk of the Spanish instruction for the day. The homeroom teacher is the students’ main teacher, and is assisted by a classroom aide

52 who serves as a co-teacher or teaching assistant. In four out of the five total Kinder- garten homerooms in the school, both teacher and aide had L1 Spanish proficiency, and in the fifth homeroom the aide had Spanish as an L1 whereas for the teacher, Sra. Marshall, it was an L2. Students knew (though sometimes had to be reminded) to speak in Spanish to both individuals, although students who spoke English more comfortably than Spanish did often continue to speak to each other in English during this time period. Students had assigned seats both at tables and while sitting on the floor in every class, and had assigned spots in line for traveling through the hallways. Late in the morning, recess outside preceded lunch in the cafeteria. At lunch, the students sat at tables with their homerooms, but were largely given freedom of where to sit at the table, and sometimes chose to sit near their friends rather than the person who was next to them in line. At lunch was where the research team approached participating students to attach lavalier microphones. Since researchers followed each homeroom class on at least two days during the research week, homerooms where more than six students were participating would have some students wearing microphones on the first day of recording and others wearing microphones on the second day of recording. After the microphones were hooked up, the students largely ignored the research team and continued interactions with friends. Recess and lunch involved a choice of language for bilingual students, though in practice students who were comfortable in English usually chose to speak English during these free times. By the middle of the year, even L1 Spanish-speaking children with only recent robust exposure to English would speak mostly English during recess and lunch. In addition to making comments about each others’ food and eating, students also used lunch time to share stories about themselves and their families, and sometimes to comment on the strength of friendships with classmates or to invite classmates to future activities such as playdates and birthday parties. Because fellow classmates

53 often did not have the patience to listen to extended personal narratives, students often seized the chance, when encountering an adult in proximity, to regale them with these stories. While most adults in the area had other responsibilities during lunchtime and did not have the luxury to stay and chat, my RAs and I were happy to listen to these naturally-occurring narratives if approached by a student, and thus quite a few of them appear throughout the collected recordings from the school year. Most adults were still spoken to in Spanish during these time periods. An exception is myself and my RAs, who always began interactions with the children in English and were also spontaneously spoken to in English by the children throughout the school year. Although we followed homerooms around throughout their afternoons for one week per month, the majority of interactions we had with the children came during the application of microphones at the lunch period. We approached lunch tables with the intention of putting microphones on quickly and leaving as soon afterwards as possible to enable maximum time for interactions between participants, but we would remain at the table when participants or other students in the class wanted to talk to us in case there were any questions about the study we could answer for them. Another reason for our rapid retreat from the lunch tables was that we were also conscious of the potential for our presence to aﬀect which language might be spoken during lunch.

3.3.3 English Classes

Following lunch, the students returned to the Kindergarten hallway to put their jack- ets and lunchboxes away, and then proceed to either their homeroom classroom for a break, ‘Specials’, or English class, depending on their homeroom’s schedule for the day. Specials were made up of Art, Music, and Physical Education (PE) classes, and English class at Immersion was referred to as English Language Development (ELD),

54 as discussed earlier in this section. Specials and ELD were both taught exclusively in English, as none of the Specials teachers and few of the English teachers knew much Spanish, and students spoke in English throughout this time to one another and to instructors, including classroom aides to whom students were expected to speak Spanish at all other times. All students participated in ELD. The homeroom stayed together for English-medium Specials, but split into low-proficiency and high- proficiency English tracks for ELD in separate classrooms with separate instructors. All study participants were in the high-proficiency English group, which included En- glish speakers of both native and near-native proficiency, so only this classroom was observed by the research team. Between Specials and ELD, these English-medium classes took up most of the rest of the afternoon before school dismissal. While students attended either Art, Music, or P.E. class four out of five days of the week (there were no Specials scheduled for Fridays), students only attended ELD two out of the five days.

3.4 Methods of Data Collection and Data Analysis

The research team, comprising me and two local research assistants, observed school days one week per month throughout the duration of the school year, as shown in Table 3.3. One research assistant was a part-time graduate student in developmental psychology at Salem State University, a public university north of Boston, and a graduate of Framingham State University. The other research assistant was a current third-year undergraduate at Framingham State University. The undergraduate research assistant was Chinese American and lived with her parents in Framingham, and the graduate research assistant was white and lived with her parents north of Boston in Tewksbury, Massachusetts. Research assistants were recruited through the

55 Framingham State University Department of Early Education listserv and trained in the methods of the study over two weekends in August. Additional research assistants helped to transcribe the recordings. These other research assistants will be described more in Section 3.4.3.1. In the first month at the school in September 2017, the research team was limited to ethnographic observation and classroom recordings, as a strategy for recording of individual students was still being worked out with gatekeepers at the school. The following month (October 2017), the research team was allowed to attach individual microphones to a small sample of participating Kindergarten students as a study pilot. November 2017 was the first full month of recording at scale. The only months skipped were January, due to Massachusetts state standardized testing limiting the amount of classtime, and April, where the week chosen for research was the first week of May, approximately 6 weeks after the previous fieldwork week. Every attempt was made to ensure a time period of 3–6 weeks in between all fieldwork weeks, so that the data supports an analysis that tracks change in phonetic and phonological features over set timepoints throughout the school year. The sources of data collected at each monthly timepoint were ethnographic observation notes, one to two afternoons of recordings of spontaneous speech by individual students, and sociomatrices. A sociomatrix is a matrix representation of whether actors are in proximity and/or in interaction with one another at a designated timepoint. It can be described as an alternative view on a social network diagram, where a cell is provided for each possible edge between each node, and the cell is filled in with the edge type (Latour 2005). In this study, edge types used were N (near), W (working together nonverbally), P (playing together nonverbally), and T (talking to each other). Sociomatrices are described in greater detail in Section 3.4.4.2 and an example sociomatrix is shown in Table 3.8.

56 Table 3.3: Fieldwork dates for the project, including number of days for each monthly ﬁeld visit and a description of the type of ﬁeldwork included in the visit. Type of recording is indicated in the column furthest right, and all rows also mention the ethnographic observation and notetaking that took place at each timepoint.

Month Dates Methods

Ethnographic observation, classroom recordings, September 2017 9/11–9/12 sociomatrices Individual recordings on Tuesday only, ethno- October 2017 10/10–10/13 graphic observation, classroom recordings, sociomatrices Individual recordings, ethnographic observation, November 2017 11/13–11/17 sociomatrices Individual recordings, ethnographic observation, December 2017 12/11–12/15 sociomatrices February 2018 2/12–2/15 Individual recordings, ethnographic observation 3/19–3/23, 3/27– Individual recordings, ethnographic observation, March 2018 3/28 sociomatrices Individual recordings, ethnographic observation, May 2018 4/30–5/4 sociomatrices

3.4.1 Recording Schedule

The Kindergarten is made up of 5 homerooms: Sra. Green, Sra. Marshall, Sra. Rojo, Sra. Sienna, and Sra. Ventura are the homeroom teachers.13 The homerooms have a rotating weekly schedule to allow them to attend each of the ‘Specials’ (Art, P.E., and Music) and ELD class 1-2 times per week. Table 3.4 shows the outline of the Kindergarten daily schedule from lunch onwards. A research team member was assigned to observe and record a homeroom on each day it had an ELD class scheduled, and homerooms were not observed or recorded on days where there was no ELD class scheduled. This means that each afternoon during the week of ﬁeldwork, between one

13Rojo: 7 participants, Green: 3 participants, Marshall: 4 participants, Sienna: 8 participants, Ventura: 5 participants.

57 Table 3.4: The Kindergarten schedule for the 2017–2018 academic year on a day when a homeroom would have ELD. Homerooms had ELD two days a week, so for a given ELD time above, one of the homerooms listed in parentheses would be scheduled. On weekdays when a homeroom did not have ELD, homeroom would occupy the entire period.

Schedule

11:40 Lunch 12:15 Homeroom 12:30 ELD (Green or Sienna), Homeroom (Rojo, Marshall, and Ventura) 1:00 Specials (except Fridays) 2:00 ELD (Rojo, Marshall, or Ventura), Homeroom (Green and Sienna) 2:30 Homeroom 3:00 Dismissal in waves by bus number

and three of the homerooms had students wearing microphones and being recorded and followed around by a member of the research team. Table 3.5 summarizes the recording and observation schedules by homeroom and trimester. As ELD occurs twice per week, there are two recordings per month for participating students in all homerooms. Recording commenced at some point during the Lunch period (11:40am–12:10pm) and ended after either the Specials period (12:55pm– 1:55pm) or the ELD period (either 12:15pm–12:55pm or 1:55pm–2:35pm, depending on homeroom), whichever occured later. This means that recordings are considerably longer for homerooms with a later scheduled ELD class. Recordings from Sra. Green and Sra. Sienna’s homerooms, who have ELD before

1 the Specials period, routinely have a duration ranging between 2 and 2 4 hours, while recordings from Sra. Rojo, Sra. Marshall, and Sra. Ventura’s homerooms have a dura-

1 tion between 2 2 and 3 hours. This holds in all cases except for the Friday recordings

58 Table 3.5: This table shows the recording schedule for homerooms based on what two days of the week they had ELD. On days of the week where no ELD was scheduled for a homeroom, that homeroom was not recorded and the afternoon schedule is consequently not captured in this table.

Rojo Green Marshall Sienna Ventura

Sep–Nov Mon Music ELD Tue ELD Music Art ELD Wed ELD P.E. Art ELD Thu ELD Art P.E. ELD Fri ELD ELD ELD Dec–Feb Mon Music ELD Tue ELD Music Art ELD Wed ELD P.E. Art ELD Thu ELD Music Art ELD Fri ELD ELD ELD Mar–May Mon Music ELD Tue ELD Music Art ELD Wed ELD P.E. Art ELD Thu ELD P.E. Music ELD Fri ELD ELD ELD

in Sra. Rojo, Sra. Sienna, and Sra. Ventura’s homerooms, where recordings end after the homeroom attends ELD, which ended on Fridays at 12:55pm, 1:35pm, and

1 2:35pm respectively, yielding respective Friday recording durations of ∼ 1 4 hours, 3 3 ∼ 1 4 hours, and ∼ 2 4 hours. As the linguistic medium of instruction is Spanish during the morning and English during the afternoon, the afternoon recordings are made up of instruction in an English language medium as well as free time when English is spoken spontaneously to peers by participants.

3.4.2 Recording Equipment

The sound equipment used in this study were three Zoom H6 recorders and 18 Azden Pro-XD wireless microphone systems. Zoom H6 recorders were chosen in order to allow

59 for the recording of 6 separate tracks, one for each participant in a given homeroom. The isolation of the individual participant to their own track in the resulting recording means that participant tracks can be analyzed separately or together. Analysis of individual recordings is useful for investigating the hypotheses of this study concerning phonetic and phonological variables, while layering multiple recordings and generating multi-party transcripts is useful for contextualizing variation in discursive interactions between participants. Audio was recorded to 44kHz/16-bit wav files to support a fine- grained phonetic analysis. Wireless microphone systems were chosen to allow students to move about freely with minimal disturbances from the sound equipment, as microphones would be worn for a large part of the school day. The necessity of capturing, for each participating student, close to normal behavior at school in order to address the questions motivating this study outweighed the somewhat choppy sound quality of a few of the recordings, occurring at times such as when a large metal object stood in the way of the wireless transmission between the transmitter and the receiver. Azden Pro-XD wireless microphone systems were specifically selected for use in this study because, when pairing, receivers and transmitters automatically find an open airwave frequency in the 2.4GHz range to connect over. This separates them from other systems that are pre-assigned to operate over only one frequency. For the use of up to 18 wireless microphone systems at once within the same building where walkie-talkies are also employed by staff and administrators, it was critical that the wireless microphone systems would be able to adapt to whatever frequency would be usable on a given day. Participating students each wore a lavalier microphone with windscreens clipped to the side collars of their shirts or dresses and directed toward their mouths. Micro- phones were not attached to students directly in the front of their collars to limit the

60 Table 3.6: The data sources for analysis generated from the year-long ﬁeld- work project and subsequent preliminary data processing.

Data artifacts

Recordings Time-aligned transcripts Aggregated class transcripts Sociomatrices Observation notes Parent surveys

distractions that would accompany the microphones being constantly in view by the wearers. Wireless transmitters were attached securely to belts which the researchers belted around students’ waists over their clothing so that the transmitters were at the students’ backs. The wire connecting the lavalier microphone to the transmitter was taped down the back of the student’s upper clothing, to, again, limit the distractions which would most likely occur if recording equipment were visible to the wearers. The research team member assigned to a homeroom kept that homeroom’s receivers for each transmitter in a basket along with the recorder that remained in their possession as they observed the homeroom. On days with simultaneous recording of multiple homerooms, each homeroom was recorded to a separate Zoom recorder so that synchronization of all six tracks per recorder could provide holistic classroom recordings.

3.4.3 Data Processing

Several types of data artifacts were collected during the course of ﬁeldwork (see Table 3.6). The procedure for coding of information from each of these sources is described herein.

61 3.4.3.1 Transcription and Alignment of Recordings

Corpus materials that have been created from this study include separate wav files from each individual track of a recording, accompanied by time-aligned individual transcripts. Time-aligned individual transcripts were knit together to form a time- aligned class transcript for all participants in a given homeroom. Individual recordings totaled approximately 600 hours. Given the size and quantity of recordings from the year-long fieldwork, not all recordings could be transcribed for this dissertation. Approximately 200 hours of recordings have been transcribed so far, 82 hours of which (two homerooms) are used in this study. Recordings for transcription were selected strategically in order to enable an analysis that compares speech from at least two timepoints spaced at least 5 months apart for each child participant. Recordings and transcriptions for participants are shown in Table 3.7. Transcriptions were undertaken in the ELAN transcription software (Wittenburg, Brugman, Russel, Klassmann, and Sloetjes 2006), completed primarily by trained Georgetown University advanced undergraduate Linguistics majors and Linguistics Masters students under my supervision. Seven Georgetown University student research assistants total assisted with transcription across three timepoints. Three undergraduate RAs transcribed the November and December recordings in December 2017, and two undergraduate and two graduate RAs transcribed recordings from February and March over the summer of 2018. Three graduate RAs finished the remaining transcriptions in Fall 2018. Additional transcription help was provided by the graduate student fieldwork RA local to the fieldsite, who transcribed in ELAN all recordings from Sra. Marshall’s homeroom, which she had been stationed to observe throughout the 2017–2018 school year.

62 Transcriptions also do not include non-speech noises produced by the participants, such as singing, humming, screaming, crying, laughing, etc. Where words are mispro- nounced, innovated as non-adult forms, or non-adultlike in other ways, transcriptions attempt to reproduce the child utterance orthographically as faithfully as possible. Otherwise, transcription procedure follows the UPenn/LDC guidelines (LDC 2003; Rosenfelder, Fruehwald, Evanini, and Yuan 2011a). These guidelines were followed because I originally imagined that the transcriptions would be able to be automatically aligned to the audio using the UPenn/LDC forced aligner FAVE (Rosenfelder, Fruehwald, Evanini, and Yuan 2011b). Even though forced alignment was ultimately not possible due to the diﬀerences between child speech and the adult corpus on which FAVE was trained, the guidelines still served as a beneﬁcial mechanism for standardization across many transcribers. Except where noted, analyses involve only transcribed recordings.

63 Table 3.7: The corpus resulting from the ﬁeldwork for this research project is depicted in detail. Recordings exist as standalone audio or with accompanying transcriptions as noted.

October November December February March May

Child (Homeroom) Day 1 Day 2 Day 1 Day 2 Day 1 Day 2 Day 1 Day 2 Day 1 Day 2 Day 1 Day 2

Conor (Rojo) Audio Transcr. Transcr. Matilda (Rojo) Audio Audio Transcr. Audio Transcr. Audio Audio Transcr. Helen (Rojo) Audio Transcr. Audio Audio Transcr. Marianna (Rojo) Audio Transcr. Audio Transcr. Audio Audio Transcr. Audio Ryan (Rojo) Audio Transcr. Transcr. Audio Jorge (Rojo) Audio Audio Transcr. Kiki (Rojo) Audio Audio Transcr. Audio Transcr. Audio Audio Transcr.

Alayna (Green) Transcr. Audio Audio Audio Transcr. Audio Audio Transcr. Kirsten (Green) Transcr. Audio Audio Audio Transcr. Audio Audio Audio Transcr. Kaylin (Green) Transcr. Audio Audio Audio Transcr. Audio Audio Audio Transcr. 64

Ariana (Marshall) Transcr. Transcr. Audio Transcr. Audio Transcr. Transcr. Transcr. Carolina (Marshall) Transcr. Transcr. Audio Transcr. Audio Transcr. Audio Transcr. Transcr. Laura (Marshall) Transcr. Transcr. Audio Transcr. Audio Transcr. Transcr. Rebecca (Marshall) Transcr. Transcr. Audio Transcr. Audio Transcr. Audio Transcr. Transcr.

Kendall (Sienna) Audio Audio Transcr. Audio Transcr. Audio Transcr. Sophie (Sienna) Transcr. Audio Audio Audio Transcr. Timothy (Sienna) Audio Transcr. Benjamin (Sienna) Audio Gordon (Sienna) Audio Audio Sylvia (Sienna) Audio Audio Transcr. Audio Audio Audio Transcr. Tanisha (Sienna) Audio Transcr. Beryl (Sienna) Audio Audio Transcr. Audio Transcr. Audio Transcr.

Allison (Ventura) Audio Audio Transcr. Audio Audio Transcr. Transcr. Audio Jeﬀrey (Ventura) Audio Audio Transcr. Audio Audio Transcr. Transcr. Audio Georgina (Ventura) Audio Audio Transcr. Audio Audio Transcr. Transcr. Audio Jaden (Ventura) Audio Audio Transcr. Audio Audio Transcr. Transcr. Audio Andrew (Ventura) Audio Audio Transcr. Audio Audio Transcr. Transcr. Audio 3.4.3.2 Coding and Extraction of Phonetic Data

The performance of forced automatic alignment on child speech data is often unreli- able (cf. Story and Bunton 2015; Xu, Richards, and Gilkerson 2014). This fact and the sometimes noisy recordings led to the need for all tokens of phonetic and phonological variables of interest to be manually coded for formant values in the acoustic analysis software Praat (Boersma and Weenink 1996). For most of the child participants, setting a maximum formant value of 8000Hz was impressionistically found to accurately track the ﬁrst through third formants (F1 through F3) in most vowels. The bands of energy at certain frequencies in Hertz (Hz) represented in the ﬁrst formant and in the second formant (F1 and F2) are the measurements typically used to establish vowel quality (e.g., height via F1 and backness via F2). Praat’s built-in linear predictive coding algorithm (LPC), intended to automatically track formant paths throughout a vowel, largely did not perform accurately enough to enable automatic extraction of formant frequency values, especially in vowels with a high F2 (extreme fronting) and/or a low F1 (extremely high). There- fore the formant coding and extraction process was fully manual and often relied on visual cues from the spectrogram rather than Praat’s LPC tracks. Additional details about the coding and extraction process for the variables analyzed in this study will be given when relevant to introduce the analyses contained in the following chapters.

3.4.4 Additional Data Artifacts

The following artifacts are paired with the speech data from the recordings to provide additional insight regarding some of the interactional, behavioral, and cultural characteristics of the participants.

65 3.4.4.1 Class Transcripts

Transcripts of individual recordings were combined to form class transcripts. These class transcripts are representative of the speech of all the children (between 3 to 6 participants) who were wearing microphones during a given afternoon. Although the class transcripts do not capture everything that was being said in the classroom, as, in all cases, the majority of the approximate 22 students per homeroom were not wearing microphones, events of the school day can be pieced together through noting what types of events contextualize speech in all the transcripts. The class transcripts become particularly useful in analysis of interactions between students. Many of the participants in this project made up close two- to four-person friend units, with the result that conversations between participants were able to be captured at an individual level for granular phonetic analysis and at a group level for an analysis focused on the social functions of a jointly constructed interaction.

3.4.4.2 Sociomatrices

Sociomatrices, introduced briefly at the beginning of this section, were used to capture both interaction and proximity among participants throughout the school day, inspired by a similar use in Nardy et al. (2014). Sociomatrices can be thought of as an alternative visualization of a social network under actor-network theory (Latour 2005), as the same information about actors and ties is presented in tabular format rather than through nodes and edges. The common practice of filling out sociomatrices at timepoints separated by fairly short time intervals gives sociomatrices an advantage over the more common social network notational format because change over time can be captured more straightforwardly.14 Sociomatrices were filled out ev-

14Nardy et al. (2014) cite Altmann (1974) with generating the method of ‘instantaneous scan sampling’ used by them as well as in this study.

66 Table 3.8: This example sociomatrix shows that at the 12:55pm timepoint, Carolina and Laura are having a conversation while Ariana sits near them.

12:55pm Ariana Carolina Laura Rebecca

Ariana NN

Carolina N T

Laura N T

Rebecca

ery 20 minutes throughout the school day by the member of the research team who was observing a given homeroom. An example of a sociomatrix is pictured in Table 3.8. It displays each participant on both horizontal and vertical axes, so that a value can be marked in the box that unites two participants at every timepoint listed. In this study, possible notational values were N to designate that participants were near each other but not speaking or even seemingly paying attention to one another, W for participants working with each other nonverbally, P for participants playing with each other nonverbally, and T for participants talking to each other. Any other notational values could be used depending on the needs and motivations of the study. A ﬁner-grained notational system could have been chosen, but given that the sociomatrices were to be ﬁlled out by my research assistants as well as myself, I chose a simple notational system to ensure accuracy and consistency in the sociomatrix logging.

3.4.4.3 Observation Notes

In addition to completing sociomatrices at 20 minute intervals, the research team took ethnographic observation notes liberally throughout the school day. These notes

67 provide the holistic setting and context of the speech and interactions captured in the recordings.

3.4.4.4 Parent Surveys

Parent surveys, as discussed in greater depth earlier in this chapter, were distributed to parents of all participating students at the conclusion of the study in May 2018. Out of the 26 parents who received surveys,15 only 15 returned them to the researcher. In- formation on language and local background collected through these surveys provided further context for the linguistic patterns observed throughout the year.

3.5 Conclusion

Undertaking scholarly research in a public elementary school poses a complex set of ethical, legal, and practical issues. In designing a study, it is necessary to try to anticipate as many potential issues as possible, while also remaining flexible enough to adapt if unexpected problems arise. Moreover, research in schools departs from typical sociolinguistic research in having more complex relationships between the researcher, administrators, teachers, and parents that facilitate the project permissions and the researcher’s ability to give back to the community in a useful way. In the best of cases, the researcher relationship to the school community dovetails with the developing interests in the project from local stakeholders such as school administrators. In less than ideal cases, though, the differing researcher and school gatekeeper interests can perturb the scope, timing, and effectiveness of the methodology. Ultimately, the school’s primary job is to deliver their educational objectives, and outside researchers must work around their needs and schedule. 15Tanisha moved away from the district halfway through the school year and was considered to have left the study; thus no attempt was made to contact her family.

68 Working within the restrictions inherent to a school ﬁeldwork site, the data collection and transcription methodology described in this chapter provided a corpus comprising 82 hours of phonemically-transcribed spontaneous child speech from 27 individuals across ﬁve homerooms. Two homerooms, Sra. Marshall’s homeroom and Sra. Sierra’s homeroom, were selected for the analyses in this study. Sra. Marshall’s homeroom was selected because all participants were a pre-existing friend group, leading to the ability to look deeper into interactions and accommodation between friends in Chapter 4. Sra. Sienna’s homeroom was selected because in this homeroom the distribution of ethnicity of participants was roughly equivalent across the three broad ethnic groups captured in school records (3 Latinx participants, 2 Black participants, 3 white participants). While Chapter 4 will provide a qualitative analysis of interactions between the friend group in Sra. Marshall’s homeroom over the course of the year, showing phonetic correlates of the development of style among participants, Chapter 5 will track phonological change in both homerooms over the course of the year, showing a role for accommodation between friends as well as a role for ethnicity-based accommodation.

69 Chapter 4

The Development of Style

Examining how children use language in context can shed light on how they will eventually acquire the community system of sociolinguistic variables. The ability to assign social meaning to a linguistic feature or set of features is foundational to sociolinguistic competence. Although children are exposed at home, from birth, to input containing at least some of the sociolinguistic variation present in their wider community (Foulkes et al. 2005), there is not yet a clear consensus regarding the age at which children establish links between social meaning and linguistic form that have observable impacts on their speech. While Ladegaard and Bleses (2003; 228) assert that 4 to 6 year old children may be “unaware of the social connotations” of sociolinguistic variables, others ﬁnd evidence of sociolinguistic variables acquired as young as 2 or 3 years old (see Díaz-Campos 2005; Foulkes et al. 2005; Guy and Boyd 1990; Kerswill 1996; Roberts 1997; Roberts and Labov 1995) Work such as Gordon (2002, 2008) shows that children as young as 2 to 3 years old are capable of engaging in roleplay interactions where they take on another’s social identity, and, moreover, that these child roleplay interactions can be proﬁtably studied to advance linguistic and sociolinguistic theory. Very young children are not the typical focus of variation research. Within sociolinguistics, adolescence is often seen as the developmental and life stage where social forces emerge strongly among peers and motivate the conveyance of social meaning through language (e.g. Eckert 1988). Work in developmental psychology, meanwhile,

70 shows that young children (5 to 6 years old) are incapable of reproducing the variable patterns in artificial languages which are sometimes learned by older children (7 to 8 years old) and easily learned by adults (reviewed in Newport 2016, 2020). Newport and collaborators posit that this is due to a maturational constraint reflecting the extent to which it is computationally efficient to track variability in input at different ages (see Schuler, Yang, and Newport 2016). Alternatively, work such as Redford and Gildersleeve-Neumann (2009) suggests that children’s apparently limited capacity for adult-like style shifting may be due to their anatomical development and motor control rather than to an immature sociolinguistic competence or an inability to track linguistic variability in their input. Redford and Gildersleeve-Neumann’s study of 3 to 5 year olds finds that 5 year olds exhibit adult-like patterns of word-final stop release in formal speech contexts, which they relate to the maturation of articulatory control and articulatory planning. If very young children are indeed capable of learning and reproducing variation, they can only produce the variable features to which they are exposed. Work by Foulkes et al. (2005) and Smith et al. (2007) suggests that young children reproduce variable patterns present in child directed speech (CDS) from caregivers, which may even exaggerate the sociolinguistic variation of the community following the pattern of overall exaggerated linguistic input that CDS provides (Roberts 2018). Young children spend the bulk of their time in a home environment and within their caregivers’ closest social circles and are consequently not exposed to the full range of social complexity in the surrounding adult community. Foulkes (2010) notes that young children typically acquire sociolinguistic variables that vary with gender and age prior to those based on socioeconomic class or ethnicity, which is likely due to the fact that children are exposed to variation in gender and age as a result of interaction with caregivers and siblings and are only later exposed to features that

71 vary by ethnicity or socioeconomic class. The question of what children do when exposed to both variable linguistic input and a diverse community is an exciting area of current research (De Vogelaer and Katerbow 2017; Smith and Durham 2019), as the answer may indicate whether children are capable of attaching social meaning to variable linguistic features, which can be thought of as productive sociolinguistic competence, or whether children mimic linguistic variability in their input without assigning social meaning to when and how variable features are used. Chevrot et al. (2000; 297) extend to children’s stylistic variation the explanation from Foulkes et al. (2005) and Smith et al. (2007) that what seems like sociolinguistic variation in children is only faithful reproduction of the linguistic variation in input from caregivers without the acquisition of underlying social meaning, noting that “it is probable that stylistic skills precede stylistic awareness of the social meaning of variants and situations”. Full sociolinguistic competence in a child will not necessarily be similar to that of adults in their community (Eckert 1997). Because variable patterns in the speech of adults in the community cannot be reliably used as a reference point for sociolinguistic competence in children, a child’s own use of style in spontaneous speech must provide the evidence of assignment of social meaning to language; as Schilling (2018; 339) notes, “the social meaning of linguistic variation is located in the qualitative patterning of stylistic variation in interaction rather than the quantitative patterning of linguistic-social group variation” (Chambers and Schilling 2018). This dissertation broadly addresses the question of whether a developing sociolinguistic competence can be inﬂuenced by a young child’s exposure to robust ethnic and socioeconomic diversity accompanied by linguistic variability. This chapter qualitatively analyzes stylistic variation in the speech of participants in Sra. Marshall’s homeroom as evidence of capacity for productive sociolinguistic competence, ﬁrst showing that relationships between participants motivate intra-speaker stylistic vari-

72 ation. Section 4.1 introduces the problem of child acquisition of stylistic practice and reviews some common variationist approaches to understanding style in language. Section 4.2 then introduces the study participants in Sra. Marshall’s homeroom in more detail, before giving a brief example of how locally-constructed stylistic and social knowledge was acquired by participants during the school year. Finally, Section 4.5 examines roleplay among participants as a site of emergent stylistic practice over the course of the year, positing that their roleplay may precede and/or facilitate their development of a more complex sociolinguistic competence.

4.1 Stylistic Practice

This section begins with a brief introduction to the concept of style as used in this dissertation. Much of the introductory discussion of style and its history of study in sociolinguistics at the beginning of this section is adapted from Schilling (2018), who provides a clear account of the subject and brings together over half a century of research in sociolinguistics and related ﬁelds. The section then goes on to introduce the concepts of stance and indexicality and to motivate child acquisition of sociolinguistic variation through these phenomena. Additional work in variationist sociolinguistics on acquisition of stylistic practice is then reviewed, followed by an exploration of the special context of performance in child roleplay for sociolinguistic variation.

4.1.1 Style and Stylistic Variation

A speech style is a way of speaking that is shaped by an individual’s context of speaking, relevant identities, stances, or attitudes, their interlocutor, or the interaction itself. Under the ‘third wave’ approach to sociolinguistics, style in speech involves a coherent patterning of co-occurring sociolinguistic variants and is used as a resource

73 by an individual speaker to convey social meaning (Eckert 2018; though see Becker 2016 for examples in which place-linked variables show variable degrees of coherence in an interaction). Individuals are capable of style-shifting in keeping with changing contexts of speaking. During the course of a single day, or even a single interaction, an individual may use multiple speech styles to convey social meaning in a way that is dynamic and relevant to contexts of social meaning that are continually co-constructed by the individual and their interactants (e.g., Hindle 1979; Coupland 1980). Stylistic variation or practice, then, is an individual’s contextual use of a suite of variable linguistic features to convey social meaning through language.

4.1.1.1 Models of Stylistic Variation and Language Change

The earliest model of stylistic variation is that an individual may style-shift to produce a more standard sociolinguistic variant in more formal, careful, or self-conscious speech, and may produce a less standard sociolinguistic variant in informal or less careful speech (Labov 1966). This is referred to as the Attention to Speech approach to stylistic variation, where differing rates of stylistic variants are correlated to more formal or careful speech styles. The most well-known example of this is Labov’s Lower East Side study of post-vocalic /r/fulness (Labov 1966), which found that the presence of full /r/ increased with increasing attention paid to speech. It is clear, though, that the factors that influence style are much more multidimensional than just attention to speech. Even early variationist work noted the effect, for example, of different types of audience on speech (e.g., Labov 1966, 1973). To accommodate these facts, sociolinguistics borrowed Audience Design (Bell 1984) and Communication Accommodation Theory (CAT) (Giles, Taylor, and Bourhis 1973) models used at the time in other fields of communication sciences. Both models high- light the role of audience in influencing style of speaking, in addition to the role of

74 context ﬁrst captured by the Attention to Speech model. Audience Design and CAT, in particular, are discussed in greater detail in Chapter 5 in terms of their explana- tory power for the linguistic accommodation and phonetic convergence observed in this study over the course of the school year. A traditional CAT/Audience Design approach is compatible with quantitative methodologies for analysis of intra-speaker stylistic variation, but does not immediately suggest an individual’s ability for creativity and agentivity in their own speech. The current ‘third-wave‘ in modern sociolinguistics is focused on “how speakers use linguistic variation in interaction to shape personal identity, interpersonal interactions, and, as individual usages cohere into individual and group styles, to shape group identities” (Schilling 2018). The ‘third wave’ of sociolinguistics highlights the need for more qualitative approaches to the individual and their dynamic social and interactional purposes and positions that are constructed through their use of coherent patterns of multiple sociolinguistic variants along with other social behaviors and practices. The primacy of the individual as sociolinguistic actor overtakes the traditional focus of sociolinguistics on quantitative analyses of group patterns in a single sociolinguistic variable. This chapter, in particular, takes its assumptions and its methodology from this approach to stylistic variation as stylistic practice, where the assumption is that individuals exert at least some self-conscious and agentive creativity over their use of sociolinguistic variables to construct social meanings contextual to a given interaction.

4.1.2 Stance and Indexicality

Interactional meaning, or, more concretely, “a person’s expression of their relationship to their talk, and a person’s expression of their relationship to their interlocutors” (Kiesling 2009), is often referred to as stance (Du Bois 2007). The present chapter

75 benefits from previous work in variationist sociolinguistics that shows that young children’s interaction with peers can be, or come to be, imbued with stylistic complexity through stancetaking. Learning to use certain linguistic features or patterns of linguistic features (styles) in co-occurrence with stances is initiating a cycle of indexicality between stance and linguistic feature, where the linguistic feature can come to be imbued with interactional meaning in a given social/interactional context (Silverstein 2003). Kiesling (2009) argues that stancetaking by an individual in their interactions drives sociolinguistic variation in a self-perpetuating indexical cycle. This view that all style and style-shifting is stancetaking decomposes coherent styles produced by individuals into ‘repertoires of stances’ (Kiesling 2009). Kiesling (2009) also reviews much previous work in sociolinguistics and linguistic anthropology to show that exposure to stances and stancetaking is a developmental primitive for acquisition of sociolinguistic variation in early childhood, saying that “the main differentiation a child is likely to hear is not among many different speakers, but different ways of interacting among the relatively few speakers (compared to adults) with whom she or he is in direct contact in early childhood”. The terminology of stancetaking also captures what is elsewhere construed as the role of identity in sociolinguistic variation, since identity in this view is made up of an accretion of stances, with only stances relevant to an given interaction driving the variants and styles that occur. For example, Snell (2010) argues that 9 to 10 year old children at two school fieldsites in the northeast of England use possessive me /mi/, borrowed from the working-class vernacular common to the area but used rarely among younger speakers, to index certain stances or identities that are locally relevant. Snell proposes a “circular chain of indexicality in which meaning flows from local interactional stances to styles, personas, and macro-level identity categories, and then back to local in-

76 teractional use” (2010; 650). This proposal appears to align with Kiesling’s assertion that establishing an indexical relationship between variable linguistic features and local interactional stances, rather than higher-order indexicalities such as social class or style, is important for child acquisition of sociolinguistic variation. Indeed, Snell reports that “there is no a priori reason why social class should be a more immediate influence than social situation” (2010; 638), especially in the case of young children with extremely limited experience of non-immediately-local, abstractly-instantiated social difference. To summarize, in this approach, the development of a style occurs through ‘stance accretion’ in linguistic forms (Bucholtz and Hall 2010), which would then allow that style composed of stances to develop into a marker of group identity, rather than the other way around. This approach to identity matches Ochs’s conception that local stances are indexed by language and create identity meaning in aggregate, either directly or indirectly (Ochs 1992, 1993, 1996). Indexation can be either direct or indirect, and the “always already imminence” of the n+1st order indexicality (Silverstein 2003; 194) means that indexicality can move from indirect to direct over time. Irvine (2001) explains that indirectly-indexed stances, styles, or identities may become direct over time as the interactional acts that first create an index between linguistic form and interactional meaning fade from memory (erasure). With this approach to stancetaking and the cycle of indexicality, the performance of personae during child roleplay may be observed in order to discern (a) what linguistic features a child has already perceived to mark a certain social identity, and (b) what linguistic features may eventually come to be repurposed as stance- or style-marking features in the child or their peers’ own non-performative speech.

77 4.1.3 Acquisition of Stylistic Practice

To review what has been presented in this section so far, in adult language, wide- ranging semiotic resources are routinely brought together to shape coherent styles (Bucholtz 2009; Eckert 2002; Moore 2004), and the ability of a given linguistic feature to contribute meaning when used as part of a style is thought to be a product of the relationship between language and stances (Ochs 1993), and/or between language and social categories (Labov 1972). This subsection explores evidence for the ability to style-shift among young children. Young children have been previously found to be able to mirror their parents’ style-shifting by situation (Smith et al. 2007) as well as to code shift by addressee (Youssef 1991). If two dialect codes may, in some cases, represent the poles of a potential gradient stylistic continuum (Hazen 2001), we could interpret this finding as an early emergence of style-shifting motivated according to audience design (Bell 1984). Cameron (2010) elegantly ties together the developing capacity for audience-design style-shifting with the child’s ‘theory of mind’ which is believed to begin developing after approximately the first 2 years of life (Baron-Cohen, Leslie, and Frith 1985). Theory of mind is the ability to attribute mental states to oneself and others. Before developing theory of mind, it would not be obvious how a child would be capable of style-shifting to fit a perception of their audience. Another prerequisite to the ability to style-shift to express social meaning is the development of a sociolinguistic monitor to track variable patterns in language input. Labov, Ash, Ravindranath, Weldon, Baranowski, and Nagy (2011; 435) defines the sociolinguistic monitor as a cognitive mechanism that “tracks, stores, and processes” socially salient quantitative linguistic distributions in input. Labov et al. (2011) ex-

78 plored the online properties of the cognitive sociolinguistic monitor in a series of perception experiments, and posited the following six characterizations (457):

• Wide temporal range

• Logarithmic sensitivity (sharp reaction to diﬀerence between low frequencies of a marked variant, but less reaction to the same percentage diﬀerence at high frequencies)

• Attenuation is proportional to increase in number of marked forms

• Asymmetrical sensitivity favoring socially marked variant

• Gender diﬀerence (women show more negative reactions to deviation from norm)

• Logarithmic sensitivity comes about in adolescence, while there is much less social consensus in younger speakers

In their experimental study, Labov et al. found child results to diﬀer qualitatively from adult results, indicating that there may be a diﬀerence in the properties of the sociolinguistic monitor among children compared to the properties described above which characterize the adult sociolinguistic monitor. They conclude from their studies that sensitivity to frequency distributions within a variable develops gradually through adolescence, so that the adult-like logarithmic sensitivity to the presence of a marked variant — a sharp reaction to change in a sociolinguistically marked variant at low frequencies but less of a reaction to change in a high-frequency marked variant — is in place among young adults but not among younger speakers. They observe that there is more variation in the responses of pre-adolescents to the presence of a sociolinguistically marked variant, and that this may be due to not having fully developed an adult-like sensitivity to sociolinguistic variation. They posit that more

79 input to the sociolinguistic monitor is needed to reﬁne its performance, so that only by the young adult years has the speaker accumulated enough input to achieve an adult-like logarithmic sensitivity. Indeed, Labov has consistently said that children will acquire sociolinguistic norms of their community early but gradually (Labov 1964, 2001a). In addition to complexity and stability of a given sociolinguistic variable, the gradual acquisition of sociolinguistic competence also must encompass the developing capacity for style — Kerswill and Williams (2000; 105) tentatively state that “children slowly gain sociolinguistic maturity in a manner that involves a gradual increase in the number of styles that are perceived and treated in an adult way.” In the process of doing so, they will also participate in ‘stylistic reinterpretation’, which Labov deﬁnes as occuring when a variable or variables used for one stylistic purpose by adult members of a community is used as part of a style that indexes a novel social meaning by children in the same community.1 An example of the interaction of stylistic and linguistic acquisition underlying sociolinguistic competence may be seen in Slosberg-Andersen (1990), who found that children were capable of style-shifting in phonology at as young as 4 years of age during roleplaying activities, and that this phonological style-shifting capacity preceded style-shifting capacities at additional levels of language, such as prosodic style-shifting. Due to the possibility of stylistic reinterpretation as well as the generalization that all social meaning is constructed on a local level within a community of practice (Wenger 1998), Eckert (1997) advises scholars to resist assuming that children’s stylistic practices will converge on adult norms. As young children, in the course of development, move from an orientation to parents towards a community of peers (Kerswill 1996), the target stylistic practices to acquire will be those that convey

1Stylistic reinterpretation is a factor that can lead to language change (Labov 2001a).

80 social meaning that is salient and relevant to a peer group. While many results from sociolinguistic studies of very young children may seem almost contradictory — some studies find evidence of adultlike linguistic constraints on variable patterning, some do not; some find variation according to macro-social categories, some do not; some find stylistic variation, some do not — there is evidence that, prior to their estab- lishment as variables exhibiting a quantitative distribution that can be statistically verified, sociolinguistic patterns will emerge first as trending correlations between emergent identity and the use of certain linguistic features that will require a qualitative (discursive and ethnographic) understanding (Cameron 2010 citing Patterson’s 1992 dissertation; see also Romaine 1984). Eckert (1997) pointed out that “the younger the age group, the greater the chances that socioeconomic, and in some cases ethnic differentiation in language is not a matter of attending to sociolinguistic differentiation but of selective exposure”. That is to say, children in socioeconomically or ethnically homogeneous home environments and caregiver networks are not exposed to all possible language varieties present in their broader community, and therefore the stylistic variation of which they themselves are capable may not make use of as many linguistic features as children who are exposed to more variation in language use. Recently, Buson (2017) and Snell (2010) have each found evidence that children in sociolinguistically diverse communities are capable of ‘pluristylistic’ language – the use of multiple coherent styles. Buson finds through work with 10 to 11 year old children in Grenoble, France that a sociolinguistically and socially diverse social network predicts the patterns and extent of variation that that child then goes on to produce, linking stylistic dexterity, flexibility, and complexity to exposure to social and linguistic difference in the community. While some early theories held that children from socioeconomically or ethnically marginalized communities exhibited deficiencies related to language in interaction (Bernstein 1975), the

81 work by Buson and Snell follows in a long tradition of work in sociolinguistics that reveals the erroneous nature of the deficiency model of stylistic competence. In fact, Buson (2017; 86) observes that the exposure to diverse individuals and, consequently, sensitivity to variation in linguistic and social features leads a child sociolinguistic learner to exhibit “greater variational amplitude in repertoires and to more use of stylization” than their peers with more homogeneous networks. Any exposure during the course of linguistic and social development that has implications for stylistic practice may reasonably also have implications for other aspects of language development. The use or non-use of a linguistic feature depends on its acquisition into linguistic production, to be sure, but successful production may depend on a child’s “culturally-reflexive” understanding of what use of such a form means in local usage (Ochs and Schieffelin 1995).2 In any case, a microscopic lens on particular social interactions showing stylistic variation can help us understand how child language development and acquisition of variation proceed.

4.1.4 Performance

The way that adults and adolescents artfully and purposefully use socially-marked linguistic features to perform personae — identities other than their own — is well documented and studied in the sociolinguistic literature (Coupland 2001; De Fina 2007; Deppermann 2007; Rampton 1995). Just as adult performative speech can reveal the links that people make between linguistic practices and social identity, child roleplay can also reveal this deepening knowledge (e.g., Snell 2010). Studying child roleplay in school oﬀers the opportunity to examine stylistic practices that take place

2Ochs and Schieﬀelin (1995; 74) describe their language socialization approach to grammatical development as that “children’s use and understanding of grammatical forms is culturally reﬂexive— tied in manifold ways to local views of how to think, feel, know, (inter)act, or otherwise project a social persona or construct a relationship.”

82 among peers. Namely, instances of a participant’s performance of another social persona in play, accompanied by the phonetic variation that they use to enregister that persona (Agha 2003, 2006), are used in this chapter to show both the awareness of an association between language use and social practice and the capacity to change one’s linguistic production to signal a new social identity. The term stylization is frequently used to describe such performative language production (Coupland 2001; Coupland, Bishop, Evans, and Garrett 2006; Coupland 2007; Rampton 1995, 2006, 2009).3 Rampton (2006; 225) deﬁnes stylization as “a partial and momentary disengagement from the routine ﬂow of unexceptional business”. The context for stylized language production is commonly referred to in terms of ‘performance’ (Coupland 2001), based on Bauman’s 1975 work. Importantly, when Bauman lays out what he means by the term ‘performance’, he says that the performance frame is able to “operate with variable intensity” (Bauman 1975; 297). His full point is reproduced here, due to its importance for how I ultimately interpret participants’ use of performative roleplay.

Art is commonly conceived as an all-or-nothing phenomenon— something either is or is not art— but conceived as performance, in terms of an interpretive frame, verbal art may be culturally defined as varying in intensity as well as range. We are not speaking here of the relative quality of a performance— good performance versus bad performance— but the degree of intensity with which the performance frame operates in a particular range of culturally defined ways of speaking. When we move beyond the first level discrimination of culturally-defined ways of speaking that do not conventionally involve performance versus ways of speaking that

3The term stylization actually originally comes out of Bakhtin and Holquist (1981) and describes language and genre use in literature.

83 do characteristically involve performance, we need to attend to the relative saturation of the performance frame attendant upon the more speciﬁc categories of ways of speaking within the community.

Another potential context for stylization in speech mentioned by Rampton (2009) is the interaction ritual Goﬀman (1967). Interaction rituals are routine interchanges in which identities are enacted, such as everyday greetings. Stylization in performance can be seen as “the knowing deployment of culturally familiar styles and identities that are marked as deviating from those predictably associated with the current speaking context” (2001; 345). An example of stylization in performance is Coupland’s study of individuals performing stereotypical and inauthentic Welsh characters on BBC Radio Wales for the purposes of humor and listener entertainment. Stylization in interaction ritual can be seen as “aimed at preserving or restoring normal relations, re-stabilizing rather than de-stabilizing the ordinary world, escaping not into but out of less charted zones of experience” (Rampton 2009; 160).4 In child speech in particular, the line between performance and interaction ritual, if such a line exists, is especially blurry. This may be due to the simple fact that young children have not truly gained competence in rituals of interaction, but the lack of clear boundary between performance and interaction ritual is also present in adult speech, which Bauman (1975) attributes to a performance frame being more or less ‘saturated’ depending on which categories of ways of speaking it co-occurs with. This means that an utterance by an individual speaker may be both a performance and not entirely performative at the same time. The study in this chapter will therefore assume that there is not an absolutely dichotomy between performative and

4cf. Myers-Scotton (2000) who describes how the contextually ‘unmarked’ language choice emerges in the interaction ritual, or ‘conventionalized exchange’, among bilingual speakers, which is perhaps a diﬀerent framing on linguistic variation in interaction rituals from that advanced by a focus on stylization.

84 non-performative speech, and will show how the same linguistic variation that takes place when a participant is enacting diﬀerent social identities in play is also useful in stylizing talk that does not involve inhabiting an ‘other’. This chapter presents intra-individual variation during roleplay as a possible trajectory of child acquisition of stylistic practice and, thereby, sociolinguistic competence, though it does not speciﬁcally rule out other ways that acquisition of stylistic practice may take place.

4.2 Young Children as Social Actors

The preceding chapters detailed the broader regional context (in Chapter 2) and the context within their city and school (in Chapter 3) for language use and social positioning, awareness, and attitudes. The children’s neighborhoods of residence within the city were presented and discussed in terms of racial, linguistic, and economic residential segregation, illuminating how the school, as a place drawing from neighborhoods across the city, brings together students from local communities that may not have frequent opportunities to interact with one another otherwise. This chapter presents a case study of participants in one homeroom, Sra. Mar- shall’s, throughout the year of fieldwork. The case study exemplifies the kind of interactional and discursive stylistic and sociolinguistic variability that likely exists throughout the entire collected corpus of recordings and ethnographic fieldnotes. It will provide evidence of the development of stylistic and sociolinguistic competence. These datapoints will become a critical foundational analysis as the following chapter goes on to examine some possible social correlates for phonetic convergence. This largely qualitative examination of language use by four participants will also contribute generally valuable insight for Chapter 5 in which language variation is

85 quantiﬁed on a broader scale across a larger subset of study participants at multiple timepoints.

4.2.1 Participant Details

The students analyzed here — Ariana, Carolina, Laura, and Rebecca — are all members of Sra. Marshall’s homeroom. They are all girls, and were the only students in Sra. Marshall’s homeroom who were participating in the study.5 Rebecca’s parents did not complete the parent survey, so little can be said about her social background outside of what is captured on recordings, in interactions with the research team, or in observational ethnographic notes directly. Therefore this section will focus on background details pertaining to Ariana, Carolina, and Laura, while Rebecca will be incorporated into the discussion of some interactional moments captured on the recordings.

4.2.1.1 Age

In October 2017 when the individual recordings commenced, Ariana was 5 years and 3 months old (5;3), Carolina was 5 years and 11 months old (5;11), and Laura was 5 years and 9 months old (5;9). As context, the median age of all participating students at the commencement of the study in October 2017 was 5 years 6 months old (5;6). Carolina is, in fact, one of the two oldest participants in the study, while Ariana

5Broadly, though, over the course of the year participating girls were given lavalier microphones more often by the research team than participating boys across homerooms. The reason is logistical; participating boys did not talk as much or as often as girls did. A full account of gender difference in amount of spontaneous speech produced among the participating children is beyond the scope of this study, but women have been shown in much previous research in sociolinguistics to display a greater “linguistic flexibility” than men (Chambers 1992), due perhaps to the broader range of social identities they must control in their interactions (Eckert 1989). See Holmes (1997) for a review. The gender difference in the extent to which talk is used as a resource in social interactions by children of this age could be evidence of socialization to some adult gender norms.

86 is the second youngest participant. By the termination of the study in May 2018, Ariana was one of only four participants still not yet six years old, while Carolina and Laura were both approximately six-and-a-half. The recordings and conversations I had with students captured students’ pride in informing interlocutors of a recent or upcoming birthday– their own or that of a peer. Half-birthdays were also kept track of, and students tended to change the description of their age from, say, ‘six’ to ‘six-and-a-half’ after a half-birthday had passed. Over the course of the year, more than one participant wielded their birthday or half-birthday to mark social maturity and knowledge in conversation. In addition to its potential social meaning within the community of children, age is a factor to keep in mind in any linguistic study because it can often add some explanation– anatomical-developmental, cognitive- developmental, or social-developmental– underlying individual diﬀerences in language practices, especially when participants are young children. The National Center on Birth Defects and Developmental Disabilities at the Cen- ters for Disease Control and Prevention (CDC) provides checklists containing expected developmental milestones for children from birth until 5;0–5;11. Some relevant milestones for emergent social behaviors are reprinted in Table 4.1 to give the reader some context for the stages of behavioral and social development that may anticipate or interact with the development of sociolinguistic and stylistic competence. The table shows how roleplay (a type of ‘make-believe’) can be a diagnostic for social- developmental milestones. Friendship, in particular copying of friends and pro-social behavior with friends, is another major diagnostic. In addition to roleplay, the concepts of friendship and copying will be important for the analysis in this chapter as well as in Chapter 5. The emergence of an understanding of ‘same’ and ‘diﬀerent’ around the age of 4 should be noted as well. Achievement of these developmental milestones by the majority of children at this age sets up the ability to observe lin-

87 guistic and social diﬀerences as well as the motivation to use language as a resource in order to reduce social distance with friends.

Table 4.1: Select developmental milestones for 3, 4, and 5 year olds in the “Learn the signs. Act early.” checklists from the National Center on Birth Defects and Developmental Disabilities. From Centers for Disease Control and Prevention (CDC).

3 Year Olds 4 Year Olds 5 Year Olds

• Copies adults and • Plays ‘Mom’ and • Wants to please friends ‘Dad’ friends

• Shows aﬀection for • More creative with • Wants to be like friends make-believe play friends

• Can name a friend • Cooperates with • Aware of gender other children • Plays make-believe • Can tell what’s real with dolls, animals, • Understands the and what’s make- and people idea of ‘same’ and believe ‘diﬀerent’

4.2.1.2 Neighborhood and Background

Ariana, Carolina, and Laura resided in three different neighborhoods with different socioeconomic, racial/ethnic, and linguistic profiles.

Ariana: Saxonville The neighborhood where Ariana’s family lived at the time of the study was Sax- onville, one of the wealthier and whiter neighborhoods north of the Mass Pike6 from Framingham Center. She grew up at this family residence in Saxonville, and so had no experience of living anywhere else, even though her birth parents had divorced and

6Interstate I-90 extending west from Boston to the border with New York State.

88 the home was at that point occupied by her father and stepmother.7 It is unknown how long or whether Ariana’s mother had lived at the family residence and how long her step-mother had lived there. Ariana’s mother lived at a grandmother’s house, but Ariana did not visit or see her mother or grandmother very often.8 Ariana’s parents reported that she had no experience with Spanish or any language other than English prior to attending elementary school, and that both her father and her stepmother had ‘strong Boston accents’. Out of the four girls being recorded in Sra. Marshall’s class, Ariana’s transcripts showed the only discussion of money. In the conversation where money was discussed, shown in the transcript in Table 4.2, Laura compliments Ariana on her dress and asks where it is from, and Ariana answers that it is from the American Girl Doll Store, a very popular and expensive toy and clothing store for girls this age. Laura goes on to ask what else Ariana has from the store, but then cuts Ariana oﬀ once she begins listing items.

Laura: Framingham Center Framingham Center, where Laura’s family lived at the time of the study, is a socioeconomically depressed and largely Spanish speaking area of the city. Laura had lived in her residence in Framingham Center for her entire life. Laura’s entire family spoke to each other in Spanish. When asked in the parent survey what the language of their neighborhood was, they reported that the language spoken in Framingham Center was Spanish. This aligned with how the language of Framingham Center was described by parents of other study participants. The description Laura’s mother of- fered of home language use on the survey was “Everybody speak Spanish at home”,

7Parents were not asked to provide the locations they had lived in for the study, only the locations the child had lived in. 8At one point near the end of the year, Ariana was getting ready for a visit to her mother at her grandmother’s house and seemed to be very anxious about it. There were multiple times that day that the recording captured Ariana crying and asking to call her dad.

89 Table 4.2: American Girl. (2018-05-01 00:33:49).

Laura 1 Where did you get that dress and everything?

Ariana 2 Oh, I just got their clothes from the American Girl

3 Doll Store.

Laura 4 Woah. Cool.

Ariana 5 And all the American Girl dolls. And a hundred

6 dollars. All the American Girl dolls are a hundred

7 dollars.

Laura 8 Oh. And which — and which one dolls — and which

9 clothes, doll, uh— which clothes do you got?

Ariana 10 I have Catherine, I have—

Laura 11 Oh, how cute. You look beautiful.

showing non-use of the standard third person present verb suﬃx -s on speak that is obligatory in L1 English dialects that approximate an idealized educated and white ‘Standard’. The absence of the verbal marker provides evidence that Laura’s mother is either an English speaker with non-native competency or has grammatical access to a dialect where the marker is optional, such as dialects spoken in some non-white

90 communities (Wolfram and Schilling 2015).9 It is unclear where Laura’s near native proﬁciency in English demonstrated on the Kindergarten placement exam came from, but her mother’s response allows the possibility that the family are potentially bilingual outside of the home. Laura also may have attended preschool or daycare in English.

Carolina: Coburnville Carolina’s family lived in Coburnville, a middle class and ethnically diverse neighborhood in the southern part of Framingham, at the time of the study, and Carolina had resided there since birth. Carolina attended a Spanish-speaking preschool, as well as being surrounded by the Portuguese frequently spoken in her neighborhood. Car- olina’s mother wrote in her parent survey that “my kids hear many diﬀerent dialects”, but that “they hear Spanish all day at school, but not much outside of school”. Their two closest neighboring homes were, at the time of the study, occupied by Portuguese- speaking families, who Carolina’s mother also reported as speaking some English. Carolina’s father was described by her mother as speaking Standard American En- glish, while the mother described herself as having a Mid-Atlantic regional dialect from growing up in Delaware.10 Carolina’s mother also mentioned a study abroad experience in college from an institution with a study abroad program, suggesting that at least one of Carolina’s parents has at least some university education, a useful marker of, at the very least, a middle-class socioeconomic status for the family. It is not known where Carolina’s father has lived or what his level of education is. 9There is also potential that Laura’s mother has idiosyncratically reanalyzed everybody as a plural noun, and, in that case, standard verbal agreement is observed. 10“I am from Delaware and have a mixed accent — part Philadelphia, part New Jersey, and part Southern.”

91 To brieﬂy summarize the diversity of backgrounds at play even for just these three participants, there are three neighborhoods (Ariana: Saxonville, Carolina: Coburnville, Laura: Framingham Center), three language backgrounds (Ariana: Eastern New England English, Carolina: Mid-Atlantic English, Laura: Spanish), and, based on neighborhoods, there may be as many as three approximate socioeconomic proﬁles (Ariana: upper middle class, Carolina: middle or upper middle class, Laura: working class or lower middle class).

4.3 KIT, DRESS, TRAP, GOAT, GOOSE, and FOOT Vowels

The vowel classes that will be discussed in this chapter are the front lax vowels KIT, DRESS, and TRAP, and the mid and high back vowels GOAT, GOOSE, and FOOT.11 The canonical positions of these vowel classes in a vowel space quadrilateral are shown in Figure 4.1. These vowel classes are reviewed brieﬂy here for their use in the Eastern New England English regional dialect, as well as their subjectivity to ongoing change across multiple dialects of English in the United States and internationally.

4.3.1 Front Lax Vowels KIT, DRESS, and TRAP

The front lax vowel system in most dialects of English is comprised of the vowel classes KIT (/ih/), DRESS (/eh/), and TRAP (/ae/). In Eastern New England English, KIT, DRESS, and TRAP are pronounced similarly to surrounding dialects, with the exception that a pre-rhotic contrast is maintained in these vowels when they occur in an open syllable. For example, in many other dialects of American English, there is no vowel contrast between Mary and merry, or even Mary, merry, and marry, but Eastern New England English maintains a three way contrast in these pre-rhotic vowels (Dinkin 2005). Eastern New England English also has a nasal system in TRAP,

11Conventional vowel class names from Wells (1982).

92 Figure 4.1: The canonical positions of KIT, DRESS, TRAP, GOOSE, FOOT, and GOAT vowel classes.

meaning that vowels in TRAP subclass TRAMP are pronounced with a tense, raised vowel, and members of TRAMP are predictable based on nasal following context. The TRAP nasal system will be discussed in greater detail in Chapter 5. Anecdotally, a pronunciation of KIT that is lower (higher in F1) can be found in stereotypical Eastern New England English speech that shows up in popular culture but I do not believe this has yet been written about as a feature of the dialect.

4.3.2 Back Vowels GOAT, GOOSE, and FOOT

GOOSE (/uw/) and GOAT (/ow/) are the high-back rounded vowel classes, while FOOT (/uh/) is a high-back unround vowel class, as shown in Figure 4.1. In many dialects of English across the globe as well as in the United States, GOOSE, GOAT, and

93 FOOT are a site of language change in progress as they undergo fronting (an increase in F2) (Labov et al. 2005; Harrington and Schiel 2017). This fronting is sometimes analyzed to form part of a larger systemic vowel shift described further below. Fought (2002) observes that Chicano English-speaking participants in California had a tendency to articulate a higher as well as a fronter production of FOOT, more akin to the phonetic transcription [0] or [1]. Fronting of GOOSE or of multiple back vowels has been a sound change in progress in varieties of English across the globe (Metcalf 1972; Hinton, Moonwomon, Bremner, Luthin, Van Clay, Lerner, and Corcoran 1987; Gimson and Ramsaran 1970; Bailey 1997; Boberg 2008; Maclagan, Watson, Harlow, King, and Keegan 2009), but raised FOOT is not nearly as common. GOAT fronting is a phenomenon shared between the innovative chain shift in progress described below and a long-standing characteristic of Southern and Mid-Atlantic dialects of Ameri- can English (Labov et al. 2005; Kennedy and Grama 2012). Eastern New England English is particularly conservative among dialects of American English in that no change towards fronting of back vowels GOOSE and GOAT has been found in this dialect (Labov et al. 2005).

4.3.3 California Vowel Shift

The California Vowel Shift (CVS, also sometimes known as the Canadian Vowel Shift) is a vowel shift in progress in multiple dialects of North American English towards lowering and retraction of KIT, DRESS, and TRAP. In speakers possessing a shifted front lax vowel system, KIT moves towards the historical position of DRESS, DRESS moves towards TRAP, and TRAP backs in the vowel space (lower F2). It was ﬁrst noticed in Northern California (Hinton et al. 1987), and later in Canada (Clarke, Elms, and Youssef 1995). Eckert (2008b) describes the CVS as a chain shift caused by the merger of LOT and THOUGHT to a single low-back rounded class that pulls

94 the front lax vowels down and backwards, in tandem with a fronting of GOOSE and GOAT. The CVS as a change in progress has also been documented in many other dialects of American English, as reviewed in Fridland and Kendall (2019), as well as in most varieties of Canadian English, as reviewed in Sadlier-Brown and Tamminga (2008). A diagram of the CVS that appeared in Podesva (2011) based on Eckert’s account is shown in Figure 4.2.

Figure 4.2: A diagram of the California Vowel Shift from Podesva (2011) using the description from Eckert (2008b).

Studies of the CVS have shown that, despite being an instance of language change in progress across many dialects of English throughout North America, shifted vowels index locally relevant stances and identities that are dependent on speaker groups and speaker contexts, rather than any one uniform social meaning across communities. For example, Fought (1999) and Mendoza-Denton (2014) found among the Chicano/Chicana Californians they studied that local gang aﬃliation, rather than ethnic group, conditioned the presence or absence of shifted vowels, and Hall-Lew (2010) shows how Asian American San Franciscans used shifted vowels to index neighborhood membership. Podesva (2011) found that the conventional social meaning of ‘Californian’, which he describes as “cool” or “laidback”, was recruited to make up a

95 “partier” persona among a gay community in Northern California in speech styles that relied on features of the CVS, and Podesva, D’onofrio, Van Hofwegen, and Kim (2015) went on to show that features of the CVS could also be used to index a ‘town’ identity (in contrast to a ‘country’ identity) in the more rural inland Central California. Eckert (2008b), in a study of children in fifth grade (approximately ten years old) in Northern California, showed that use or non-use of features of the CVS was correlated to ethnicity (Chicano and Anglo) in one school and gender (boy or girl) in another, but also that children across ethnic groups used the variable to index “norms of coolness” to drive and maintain the peer social order. In many, but not all, of the studies of CVS, it is found to index whiteness and Californian-ness, along with “casual, fun-loving, affluent, free, and white” (Eckert 2008b; 29). Eckert (2008b; 29) also observes that CVS features have been “popularized, gendered, raced, and classed through their media associations with the male surfer and the Valley Girl — gendered icons of privilege, materialism, and empty-headedness, but also national trend-setters and the embodiment of white California”. D’Onofrio (2015) goes on to show in a series of perception experiments that the association between shifted vowels and a Valley Girl or Californian persona was available to non-Californians including participants from New England and the Mid-Atlantic, and that these participants from non-Western dialect regions were even more likely to associate CVS features with these personae than participants hailing from California who possessed CVS features in their own speech. My study presented in this chapter shows how features of the CVS may show up in the speech of my very young study participants as they enact stances and perform personae throughout the school year. I first focus on /uw/, the vowel in rude, showing that a fronted /uw/ is acquired in tandem with the word rude to enforce social norms, and that this fronted pronunciation, non-local to the Eastern New England English

96 dialect region, may stem from Carolina’s Mid-Atlantic dialect background. I go on to argue that performance of personae during roleplay is an important site for the study of stylistic variation, and that, remarkably, features typically ascribed to the CVS including /uw/ (GOOSE) and GOAT fronting and KIT, DRESS, and TRAP lowering and retraction, were used by my participants to construct persona during roleplay.

4.4 Case Study: Acquisition of ‘rude’

From the beginning to the end of the study, a period of nine months, each of the four girls seemed to undergo subtle behavioral shifts. This section posits that the frequency with which the girls observed and commented on ‘rude’ behavior from each other and from their peers at the end of the year compared to the beginning of the year is an example of a new social behavior that has been acquired. Along with this new social behavior comes a speciﬁc fronted phonetic realization of the /uw/ in rude that is not usually found in Eastern New England English, which has been found to resist language change towards a fronted pronunciation of /uw/ (Labov et al. 2005). A qualitative analysis of how and when rude is used, and by whom, suggests that it is Carolina who has introduced the practice of calling out peer rudeness into the friend group. Carolina’s pronunciation of rude, which appears to be inﬂuenced by her mother’s Mid-Atlantic English vowel system, appears to induce a fronted /uw/ in rude to the other participants who have parents with self-proclaimed ‘Boston accents’ and who otherwise exhibit an Eastern New English English dialect vowel system (as shown in Chapter 5). An increase in calling out rudeness among peers could emerge out of innumerable conditions and prerequisites. One prerequisite is linguistic and has to do with the

97 acquisition of the lexical item rude. An additional change leading to more calling out of rude behaviors could be a greater intimacy and consequent informality among the friend group of girls in Sra. Marshall’s homeroom as the time they have spent together increases over the course of the school year. Another is acquiring communicative competence (Hymes 1974), learning how their surrounding community uses rude. An increased understanding of politeness also likely emerges at this age, and may help to motivate the development of stylistic variation. Gleason (1980) observes in a series of experiments with 2;0 to 5;0 year old children and their parents in laboratory and non-laboratory conditions that very young children do not spontaneously initiate the politeness routines used by adults in their community (e.g., greetings, saying ‘thank you’), and must be prompted by their parents. She observes that “young children do not appear to be motivated to acquire politeness routines [. . . ] by contrast, there is a great deal of evidence that children are strongly motivated to acquire other kinds of language.” In a later study of how four 3;1 to 4;11 year old children use politeness routines at family dinner tables, Gleason, Perlmann, and Greif (1984) conclude that “learning politeness routines is one way of learning stylistic variation at an early age.” Work in developmental psychology has found that judgment and reactions from peers influences children’s socialization in helping them to link their own emotional regulation and expression with social consequences (Saarni and von Salisch 1993), or in other words, figure out what is appropriate and inappropriate. Fabes and Eisen- berg (1992) notably find that popular preschool-aged children (as measured through positive peer ratings) possess better emotional regulation in response to provocation during play time than their peers with less positive peer ratings, and that while the popular boys in the study responded to provocation with “active but nonaggressive resistance”, the popular girls in the study responded by “expressing disapproval of the

98 provocateur”. This is evidence from developmental psychology of the role of judgment, and especially of negative evaluation, in the social life of girls at this developmental stage. Out of the 40 adjectives occurring more than once across the year of transcribed recordings from Sra. Marshall’s homeroom12, there are 8 disparaging adjectives. They are, in order of frequency, bad (47), rude (11), gross (8), mean (5), bossy (3), disgusting (2), pushy (2), and terrible (2). Only 6 disparaging adjectives, bad, mean, gross, disgusting, bossy, and rude were used to describe peers. Their occurrences are depicted in Table 4.3, where only rude appears to be used consistently since its potential inception. Bad appears as a disparaging evaluation of a peer in November and March; mean in October, December, and May; disgusting in December and gross in March; and bossy in November. The word rude, on the other hand, does not appear in the transcripts until February13, and then reoccurs with increasing frequency in March and May, the two subsequent recordings.

12Excludes numbers, gerunds, and participles. Some adjectives are homologous or share stems with other parts of speech, such as verbs (e.g., clean), nouns (e.g., favorite), adverbs (e.g., hard), and discourse markers bleached of lexical content (e.g., okay), thus the counts may be somewhat inﬂated for those words that do not have an unambiguously adjectival usage. The word mean is one of them (e.g., I mean...), but in this case the transcripts were searched manually for mean used only in the adjectival sense. 13One time in the October recording Laura calls a peer ‘rude’ at lunch because he’s hurting her, but it is unclear from the context whether or not it is a case of a false cognate with Spanish, rudo (rough).

99 Table 4.3: A timeline of disparaging peer evaluation adjectives from the transcribed ﬁeldwork recordings.

October November December February March May

mean X(Table 4.7) X(Table 4.6) X(Table 4.8) bad X(x2, Table 4.5) X(Table 4.11) bossy X(Table 4.10) disgusting X(Table 4.4) rude X(Table 4.9) X(Table 4.11) X(x5, Table 4.12) gross X(Table 4.11) 100 The word rude serves to evaluate social interaction in a way that the other negative evaluatory adjectives used by the participants do not, according to the index of lexical units in FrameNet, a lexical database widely used to undertake Natural Language Processing of semantic frames in texts (Baker, Fillmore, and Lowe 1998). In FrameNet, rude is a member of the class Social interaction evaluation, where “an Evaluee is judged by a Judge to be of a certain character based on her or his Behavior towards other human beings”. Of the other four negative evaluation adjectives that are most frequently used by these participants — bad, gross, disgusting, and mean — mean is the only one that also belongs to the Social interaction evaluation class. Bad belongs to the FrameNet class Morality evaluation (“an Evaluee is described by a Judge with respect to the morality or rightness of his or her Behavior”), and disgusting belongs to the Stimulus focus class (“a Stimulus brings about a particular emotion or experience in the Experiencer”).14 In comparing definitions in the Oxford English Dictionary of the adjectives rude (Oxford English Dictionary, 2020b) and mean (Oxford English Dictionary, 2020a), mean is a general and broad social interaction evaluation of a person or actions that are “disobliging, uncooperative, unpleasant, unkind, vicious, cruel”, while rude has to do specifically with learned nuances of social norms and cultural competence as an evaluation of a person or behavior that is “devoid of, or deficient in, culture or refinement” or “unmannerly, uncivil, impolite”. In other words, rude may be more likely to be used by a participant after she develops both an understanding of the culture of her community and the social norms governing her interactions with peers, as well as a learned strategy of negative evaluation of a provocateur that may help her to maintain her social position relative to her peers.

14There is no FrameNet entry for gross, but I imagine it would fall into a similar class as disgusting based on similar deﬁnitions of the two terms.

101 Table 4.4: disgusting appears in a December recording. (2017-12-12 00:49:54).

Ariana 12 Do you know real sand is from ﬁsh?

Carolina 13 No, real sand comes from ﬁsh’s butt, they poop out

14 sand.

Ariana 15 Yeah, yeah.

Carolina 16 And then they land, and then it lands up on the

17 shore and then people—

Ariana 18 Yeah, it’s their poop!

Carolina 19 And then people play on it, right?

Ariana 20 Yeah, it’s disgusting. People play on ﬁsh’s poop.

102 Table 4.5: bad appears in two November recordings. (2017-11-14 00:72:21 and 2017-11-14 01:03:52).

Rebecca 21 (to Ariana) No, you’re bad right now, I know, I

22 heard—

23 Probably we need to be a partner never again.

(2017-11-14 02:29:53)

Carolina 24 Guys, guys, guys, guys!

25 You’re not making any rainbows, you’re just mak-

26 ing a tree.

27 [Peer] did that ’cause he’s a bad person.

28 That just makes it look bad.

(2017-11-14 01:03:52)

The following tables (Table 4.4 through Table 4.12) show the participants’ use of negative evaluatory adjectives over the course of the school year. As I did the ﬁeldwork, listened to the recordings, and studied the transcripts, I had the impression that the negative evaluatory adjective rude was increasing in frequency of use over the course of the latter half of the year. I posit the increasing use of rude to be an indicator of the girls’ development as social actors. A review of the excerpts suggests that the

103 Table 4.6: mean appears in a December recording. (2017-12-12 00:72:21).

Laura 29 Guys, stop spreading!

Carolina 30 We’re just trying to clean it up, okay? Stop. We can

31 do what we want, you don’t have to tell us what to

32 do, Laura, you’re not the boss.

Laura 33 I’m not the boss, I’m just telling you to stop.

Ariana 34 We’re trying to clean up the sand.

Laura 35 No, stop, I’m not a boss, when you grow up you

36 can be the boss but not now, I’m a kid right — I’m

37 gonna tell the teacher you’re being mean.

Carolina 38 You’re being mean too!

emergence of rude may track the development of the social practice of evaluating peers’ behavior along learned community social norms, which is one possible social and developmental motivation that can precede or occur in tandem with the acquisition of stylistic variation. Tables 4.4 and 4.6 depict two moments from a December recording when negative evaluations using the words disgusting and mean are made. In Table 4.4, Ariana and Carolina are playing with sand, and Ariana observes that it is ‘disgusting’ that sand

104 is made up of ﬁsh poop in line 13. The word gross is used similarly to the word disgusting in the recordings, in that both reﬂect a personal emotional response to a stimulus. It’s hinted from the usage of bad in Table 4.5 in two interactions in November that such an evaluation applies to something inevitable or extreme, like moral character or personality. Rebecca hesitates to partner with Ariana ever again because she is bad (line 23). Earlier that same day, Carolina calls a peer a “bad person” (line 27). Table 4.6 shows an interaction in December when Laura and Carolina accused each other of being mean. Even though mean could partially overlap in context with rude in that they both are used to express a negative evaluation of a peer’s behavior

(FrameNet’s Social interaction evaluation class), in December rude had not yet been used in the recordings. Importantly, this does not necessarily imply that the participants did not know in December what rude meant, but when Carolina told Laura to stop interfering with the sand she and Ariana were playing with, Laura called Carolina mean instead of rude (line 37). The criticism did not emphasize in the way that rude would that Laura’s behavior was contrary to community social norms. Additional examples of mean are given in Tables 4.7 and 4.8. In October, 4.7, some of the children were given stickers at lunch, and Ariana did not receive one, causing her to call the adults giving out stickers mean (lines 41 and 43). In May, excerpted in Table 4.8, Ariana called a classmate mean for shouting at her (line 46). In contrast, when rude was used by the girls in this homeroom, it specified a behavior that was contrary to the understood social norms. The first time rude occurred in the data, in February, Carolina was berating a peer about their inappropriate behavior of hiding a toy she was using. As shown in Table 4.9, it seemed that the other student was attempting humor with this behavior (line 47), but Carolina was offended

105 Table 4.7: mean appears in an October recording. (2017-10-11 00:01:21).

Carolina 39 Ariana, Ariana! I got little stickers! Ariana! I got

40 little stickers!

Ariana 41 I didn’t! Those are neat. They’re mean.

Carolina 42 Ariana, why do you really want these?

Ariana 43 I don’t know why they gave you stickers, but they’re

44 mean.

Table 4.8: mean appears in a May recording. (2018-05-01 01:01:44).

Teacher 45 I’m sorry that he shouted in your face.

Ariana 46 (crying) He’s really mean, he sh- shouted.

and told the peer that they did not ‘deserve’ to be able to play in her vicinity. Car- olina consistently enacted power and judgment of this type over her peers, but the excerpt in Table 4.9 shows how her use of rude in line 52 along with her declaration that her peer does not “deserve to be here” (line 50) assists her in establishing and articulating the social norms of behavior and positioning herself as having the power to enforce social norms.

106 Table 4.9: rude appears in a February recording. (2018-02-15 00:27:27).

Peer 47 (after hiding a toy that Carolina was using) You

48 fell for it! It is so funny.

Carolina 49 I don’t even want it! I guess — I think you don’t

50 deserve to be here.

Peer 51 What? I was just pretending! {LG}

Carolina 52 That is so rude!

Peer 53 No, it’s not. I {LG} — I did it —

Carolina 54 It is!

Carolina does not always get away with wielding the social power of enforcing norms and setting rules within her friend group without being subject to negative evaluations herself. Early in the school year, she is called bossy by her close friend Ariana in Table 4.10 (line 60). The friends are making a zoo out of blocks, and Carolina is not letting Ariana contribute to planning the design of the zoo. Carolina ﬁrst protests that she is not bossy in line 62, and then there is a pause of approximately one minute as the girls continue to play silently, before Carolina ﬁnally concedes some control of the design of the zoo to Ariana.

107 Table 4.10: bossy appears in a November recording. (2017-11-16 01:22:34).

Ariana 55 I know a better thing to build for the animals

Carolina 56 No, Ariana, stick to my plan, I know how to make

57 — a door will work.

Ariana 58 Then why did you say make a zoo?

Carolina 59 No, we’re making stairs to get to the zoo, you—

Ariana 60 Then if you’re gonna be so bossy, then I’m not

61 gonna be your friend.

Carolina 62 Ariana, I’m not bossy! Okay, Ariana! We can make

63 a zoo.

The next time rude is captured in the data from Sra. Marshall’s homeroom, in a March recording, it is during an argument between Rebecca and Ariana when Rebecca and Carolina are pretending to be on the phone with one another at lunchtime, shown in Table 4.11. Ariana tries to get Rebecca’s attention while Rebecca is on the phone with Carolina, and Rebecca rejects Ariana’s attempt to join the play conversation. Ariana uses rude to censure Rebecca (line 68) for making a ﬂippant remark about her to Carolina (line 67). After continuing play with peers (lines 72 through 77), Ariana and Carolina begin a phone conversation with one another and Rebecca interrupts

108 Table 4.11: rude, gross, and bad appear in a March recording. (2017-03-27 00:34:33).

Rebecca 64 Hi Carolina!

Ariana 65 Rebecca!

Rebecca 66 I’m not calling you, I’m calling Carolina! Hi Car-

67 olina, I’m so sorry about that, it’s Ariana.

Ariana 68 That’s rude, Rebecca.

Rebecca 69 You can actually call Carolina with these. Hi Car-

70 olina!

Ariana 71 Hi Carolina! Wait, what? This is—

Peer 72 Smell his hair, it smells so good. Smell his hair.

Laura 73 No, no, it smells—

Ariana 74 That’s gross. Hey, did you put the pants on your

75 head? That’s gross, now you have to take a shower.

Laura 76 It smells like yogurt, yogurt, yogurt.

109 Rebecca 77 Let me smell!

Ariana 78 That is so, so freakin’ gross. Carolina! Carolina,

79 I’m so happy to see you.

Rebecca 80 Hey Ariana! Hi, I’m talking! Ariana!

Ariana 81 I’m talking with Carolina.

Rebecca 82 (playful speech) How rude! How, how rude!

Ariana 83 No, because like, you said my name. So that was

84 just so rude that you said my name.

Rebecca 85 You’re so bad, Ariana!

Ariana while she is talking to Carolina in almost the exact same way as Ariana did to her merely minutes before (lines 78 through 81). In line 82, Rebecca mocks Ariana’s earlier use of rude by imitating Ariana’s use of rude playfully in a high- pitched voice and with an exaggerated intonation contour. It is unclear whether this parallel interruption was a coincidence or whether Rebecca had explicitly set out to replicate the earlier situation so that Ariana could understand why Rebecca felt the need to criticize her to Carolina, or to paint Ariana as silly for attempting to evaluate her negatively and/or enforce social norms. Ariana’s reaction to Rebecca’s taunting imitation was to explain what justiﬁed her use of the word (lines 83 and 84). Ariana’s

110 insistence that it was rude that Rebecca “said my name” may be taken as Ariana explaining that it was rude for Rebecca to talk negatively about her to Carolina. Rebecca rejects Ariana’s explanation by calling her bad at the end of the interaction (line 85). Importantly, the previous excerpt in Table 4.11 shows that the evaluation of behavior with rude can occur as a sidebar in play that involves voicing adults, such as pretending to be on the phone with one another. The way Rebecca apologizes for an interruption when “on the phone” with Carolina (“Hi Carolina, I’m so sorry about that, it’s Ariana.”) suggests an attempt at faithful reproduction of how they witness adults using phones, including conventional phrases. A large amount of performance of adult situations that involves voicing various adults occurs in the transcripts, and additional selections will be pulled out in the following section. The capacity to change the way one speaks to suit a context of play is a type of style-shifting, so the girls playfully putting on ‘phone voices’ by using conventionalized phrases suggests an awareness of the appropriate way of speaking in a given social context. When Ariana explains her use of rude, she does so by way of attempted met- alinguistic commentary on Rebecca’s oﬀending utterance. Ariana’s explanation is not only evidence of her awareness of the social norms regulating behavior among friends in a frame of play, but, furthermore, is evidence of her awareness of an appropriate way of verbally interacting in a given social context. In brief, this excerpt establishes a link between language and social competence — or, communicative competence (Hymes 1974) — in the data.

111 By May, rude had caught on as a descriptor of peer behavior, as the examples in Table 4.12 show.15 In fact, the word occurred six times in the transcript from May, and was used by Carolina, Ariana, and Laura. Overall, usage of rude in May conveyed an apparent awareness of social distance or difference between teacher and student. The word was applied to teacher behavior towards the students (lines 87 and 91) as well as student behavior towards the teacher (line 90). Carolina’s (line 86) and one of Laura’s tokens (line 94), centered on telling the teacher about inappropriate peer behavior, while the other three occurrences, one from Ariana and two from Laura, were calling out behavior perceived to be violating social norms between teachers and students. This additional evidence reinforces my claim that by the end of the year these girls have developed an awareness of socially normative interactions among social actors with different roles and a motivation to comment on it. An audience design model of style-shifting (Bell 1984) would rely on awareness of how social and interactional norms vary by social role (e.g., teachers must be spoken to differently than peers) in order for stylistic variation to occur based on perceived audience. Moreover, the framework common in modern sociolinguistics that stylistic practice is a way that social actors convey stances and construct identities interactively leads to the expec- tation that the girls are primed in the latter half of the year to use stylistic variation to maintain friendships, manage others’ perceptions, and enact social power.

15Because recording and observation was restricted to only certain days out of the year, I cannot rule out that the word rude may have occurred in an interaction between the girls prior to it appearing in a transcript. However, the increase in rude over the course of the year would still correlate to the development of new social behaviors over time.

112 Table 4.12: Tokens of rude in the May recordings.

Carolina 86 (To teacher) Uh, Rebecca was being really rude.

(00:54:59)

Ariana 87 ( Teacher: Go ﬁnish your garden!) So rude. I ﬁn-

88 ished my garden.

(00:58:11)

Laura 89 (Teacher waiting for attention from classmate)

90 Look at her! He’s rude.

(00:57:41)

91 (Teacher pairing up students) How rude! I wanted

92 to be with her. You crossed me. Please! You just

93 crossed me.

(00:34:00)

94 Oh my gosh! I’m telling. You’re rude. No! Oh my

95 gosh.

(00:16:04)

113 4.4.1 The Phonetics of ‘rude’

A close phonetic analysis of this single word may facilitate an understanding of the processes that underlie the phonetic convergence over the course of the year shown in the following chapter. If it is not already apparent from earlier examples, the following chapter will also elaborate on the extent to which the other girls in the study want to be liked by Carolina and to get Carolina’s attention. Some of the animosity that arises between Ariana and Rebecca is over the friendship triangle between the three girls, and importantly, who is the closest friend of Carolina at any given time (it is usually Ariana). This friendship dynamic leads to the hypothesis that the other girls will want to imitate not only the way Carolina acts, but how she speaks as well. Remember that Carolina’s main caregiver is from Delaware and has a self- described mid-Atlantic accent. Labov et al. (2005) describe the Mid-Atlantic dialect area as characterized by “strong fronting of both /uw/ and /ow/”, in both post- coronal and other contexts. In stark contrast, Eastern New England English, the dialect spoken by both Ariana’s caregivers, is conservative for back-vowel fronting. Eastern New England is one of only three distinct dialect areas in the US where post-coronal /uw/ is typically produced with a normalized F2 < 1550 Hz (Labov et al. 2005), in other words relatively back in the vowel space.16 Carolina’s February rude has an ANAE normalized F2 value of 1604 Hz at its midpoint,17 which is fronted compared to Eastern New England English, while Rebecca’s

16The other two isoglosses for conservative back /uw/ after coronals in the Atlas of North American English surround Wisconsin/Eastern Minnesota and Northern New Jersey. 17Findings from Hillenbrand, Getty, Clark, and Wheeler (1995) suggest childrens’ F2 in /uw/ should be at least 1490 Hz, compared to 1225 Hz for adult females and 1122 for adult males. The process of normalization applied to this dataset converts raw formant values to a scale that is based on adult North American averages so that interspeaker diﬀerences can be compared in a way that is not subject to vocal tract size. This brings participants’ formant values more in line with adult standards.

114 rude in March has midpoint F2 of 1721 Hz, which is even more fronted. Ariana’s and Laura’s March and May midpoint F2 means are 2115 Hz and 1880 Hz respectively, which are extremely fronted. Further analysis based on a large number of tokens will better capture each participant’s vowel space in Chapter 5, so that their production data can be statistically compared to support conclusions about phonetic convergence over time. Notwith- standing, the fronted pronunciation of the /uw/ in rude exhibited by Carolina, based on her presumably long-term and immersive exposure to fronted back vowels, may have spread to Ariana, Rebecca, and Laura along with her use of the word itself. If Ariana, Rebecca, and Laura are hyper-correcting towards an even more fronted rude, this may be an example of diﬀusion (Labov 2007) driving sound change among even very young speakers in this community. This sort of analysis would be consistent with Labov (2001b), which puts forth that it is the gregarious18 women who are both centrally located within an intimate local network and who take part in additional non-local networks who are most likely to be the disseminators of innovative language. Although those who study gregariousness in sociolinguistics do not apply the term to linguistic innovation in the speech of young children, through this small example of the single lexical item rude we begin to see the power of a popular and ‘bossy’ girl to bring about linguistic innovation in her peer community. Carolina brings fronted productions of /uw/ into the friend group from her non-local caregiver, and if she indeed introduces the word rude to her friends, and they go on to use rude in order to be more like Carolina, it makes sense that the girls front their /uw/ in rude, and perhaps even other words with this vowel, in line with Carolina’s production. In this way, this example of the adoption and pronunciation of the word rude among these

18‘Gregariousness’ is a word used often in reference to the leaders of a Labovian sound change through diﬀusion, but I believe only Denis (2011) attempts to operationalize the quality itself through his ‘Apparent Gregariousness’ metric.

115 friends can be taken as an early indication of employing stylistic variation to convey stances and identity through language.

4.5 Case Study: Stylization in Roleplay

This section focuses on performance speech during roleplay, in which the girls voice other imagined social actors. This behavior shows both the capacity for linguistic modification associated with a different social role, and offers the opportunity to track linguistic variation in speech in real time as a participant switches back and forth between pretending to be someone in another social role and any other ways of speaking they may use when not performing that social role. Cases of performance between two playmates were coded in NVivo in the transcripts of data from the year of fieldwork. This resulted in three cases of performance in roleplay occurring between Rebecca and Carolina. The first two are found in a recording of afternoon free-play time in February, and the third is from a lunchtime recording in March. In one of the February recording sessions, Carolina was not wearing a lavalier microphone,19 so her speech is only picked up by Rebecca’s microphone from time to time during lunch. Complete transcripts of the full roleplay interactions can be found in Appendix C. An example of how the roleplay was initiated appears below, from the roleplay session occurring spontaneously during lunch in March. Rebecca and Carolina find a doll in the cafeteria and Carolina suggests they enact mother and babysitter roles, with the doll being the baby.

19Carolina had asked for her lavalier microphone to be taken oﬀ immediately after putting it on at the beginning of lunch. On the second day of recording the same week in February, Carolina wore her microphone for the entire afternoon without complaint.

116 Table 4.13: Carolina and Rebecca play Babysitter and Mom. (2018-03-27 00:26:20–00:32:35).

Carolina 96 Uh, Rebecca, pretend like, um, pretend that you

97 wanted me to– No, pretend that you wanted me to

98 babysit her, okay? So she— so she was sneaky, so

99 she went wherever she wanted to without me seeing.

100 Uh, yeah. You talk through it, well no–

Rebecca 101 What are you doing?

Carolina 102 She went in it.

Rebecca 103 No, no, just pretend she’s eating the apple.

Carolina 104 No, no, how about we pretend– pretend I’m not

105 gonna let her get dirty, but I’m gonna go like this,

106 pretend this was a pool, but pretend this is my

107 lunch tray, and she’s like huh, cool, cool. And pre-

108 tend she thought she was swimming. My pool’s so

109 hot!

Rebecca 110 Hey Carolina! Carolina! Carolina I need to talk to

111 you.

117 Carolina 112 What?

Rebecca 113 How’s the babysitting going?

The full roleplay sessions from Feburary are shown in the transcript in Tables C.1 and C.2 in Appendix C. In the ﬁrst roleplay scenario the girls created, Carolina was The Mom, while Rebecca was The Baby who gets Carolina’s permission to cook. Other students helped Rebecca to bake cookies to bring to The Mom for approval. This play-acting situation was immediately followed in the recording session by a second scenario wherein Rebecca was a hairdresser washing and cutting Carolina’s hair, as other students pretended to be Carolina’s children who were waiting in the salon.We hear Rebecca frequently break character to give orders to peers and to complain about toys being taken. The roleplay interactions were separated into two tables to show the two distinct scenarios — mother and baby roles vs. hairdresser and client roles — occurring, but play is continuous between the two situations. A roleplay session occurring spontaneously in the March data, the full transcript of which appears in Table C.3 in Appendix C and the initiation of which is excerpted above in Table 4.13, is centered around a doll Rebecca and Carolina have found in the cafeteria. Carolina goes on to invent a scenario wherein Rebecca is The Mom of the doll and she is The Babysitter. As in February, other surrounding items were brought into play as needed to make up the objects of the pretend world. Play was interrupted when Rebecca and Carolina were asked by Sra. Marshall to return the doll to another student to whom the doll belonged. Notably, the authoritative roles Carolina took on during roleplay and her consistent directing of the roleplay was not entirely diﬀerent from the way she interacted

118 with classmates in non-roleplay activities, such as how she ‘bossed’ Ariana around while making a zoo out of blocks in November. Therefore, even at this young age, the stances Carolina took on and potentially used language to express during roleplay may be a further expression of an already familiar stance of power and being in charge that infuses her non-roleplay interactions with peers. If this were the case, it would link stylistic variation during roleplay even closer to the adult-like stylistic variation that is motivated by stancetaking and identity concerns. Taken together, the roleplay captured in the February and March recordings provides a testing ground for the hypothesis that children this age are aware of, and thus capable of making use of, locally-salient stylistic variables to index social characteristics in play where they take on different social roles. The analysis in this subsection follows Rebecca from February to March as she voices three different characters: The Baby, The Hairstylist, and The Mom. The use of stylistic variation to differentiate between different voices corresponding to different social roles and stances is evalu- ated. Rebecca’s production during the frequent asides to classmates where she ceases to roleplay form a kind of baseline against which to compare the roleplay performance speech. As a comparison, the March recordings are also analyzed for Carolina’s voice as The Babysitter versus when she interrupts the roleplay to talk to Rebecca, other peers, or Sra. Marshall.

4.5.1 Normalization

Figure 4.3 contains the vowel space of each of Rebecca’s characters, in addition to the vowel tokens taken from Rebecca’s assumedly ‘normal’ voice that is on display when she interrupts play to, for example, tell a peer not to touch her toys. While The Hairdresser and Rebecca share overall similarly sized and shaped vowel spaces, The Baby has a larger range in F1 and The Mom has a larger range in F2. The

119 Baby and The Mom differ from Rebecca’s voice in other characteristics as well. The Baby has a high-pitched, sing-song voice that is accompanied by a pronunciation of /ô/ as a labiovelar glide (in contrast to Rebecca’s usual acoustically adult-like rhotic production). This is likely a learned stereotype of baby-talk. The Mom has a higher- pitched voice than Rebecca, and a distinctly formal way of speaking (for example, less coarticulation and nearly all word-final /t/s are released). The Hairdresser does not share The Mom’s formal way of talking, but rather sounds largely similar to Rebecca overall, with some key vocalic differences to be explored here.

Figure 4.3: The vowel spaces of Rebecca and each of her three characters, with all tokens, vowel category means, and an ellipse representing an estimated normal distribution in F1 and F2 dimensions. Baby Cook appears as ‘Baby’ in the top left, Hairdresser top right, Mom in the bottom left, and Rebecca herself in the bottom right.

120 As the pitch differences are extremely auditorily salient in listening to the recordings, it is worth noting that these non-vowel differences between characters are evi- dently important for the girls’ construction of different roles during roleplay. Although this study focuses on measuring vowel differences in F1 and F2 space, there is much more stylistic variation in speaking that contributes, maybe even more forcefully than vowel difference, to the voicing of a given role during roleplay. It is not possible to normalize the vocalic measurements in order to directly compare the speech of Rebecca and Carolina, as normalization would lead to a distortion of the variability in how Rebecca’s various performances treat individual vowel classes in F1 and F2 space, and it is clear that Rebecca actually manipulates the shape of her vocal tract for these performances in a way that normalization would erase. Tech- niques for normalization will be discussed further in Chapter 5. Carolina’s character of The Babysitter, as well as Carolina’s ‘normal’ speech, is therefore not able to be directly compared to Rebecca’s characters, as this would require normalization across the two speakers. Instead, Carolina and her performance of The Babysitter will be discussed in brief after the discussion of Rebecca’s characters.

4.5.2 Performance Vowel Classes

If there is a distinct patterning of vowel classes that can be observed for each performed role, this may indicate the development of adult-like style-shifting, or even participation in a sound change, assuming that a role performed during a roleplay scenario is not qualitatively diﬀerent from the types of roles that emerge in everyday adult and adolescent speech. Overall distributions are shown in Table 4.14. All tokens with /r/ as their following phonetic context were excluded from analysis. Tokens outside of 1.5 standard deviations from the mean for each character for each vowel were excluded. Vowels with only one remaining useable token for a given persona are

121 not considered. Due to lack of robust data, all analyses presented in this section will remain descriptive and qualitative.

122 Table 4.14: Mean formant values (Hz) and ns for each character and vowel.

BABY HAIRDRESSER MOM REBECCA BABYSITTER CAROLINA

Vowel: F1 F2 n F1 F2 n F1 F2 n F1 F2 n F1 F2 n F1 F2 n

FLEECE 572 1836 12 493 1567 11 666 2024 8 649 1805 5 695 1768 5 KIT 894 1981 5 736 2028 17 840 1591 3 600 1807 5 950 1800 2 801 2478 3 FACE 647 2067 11 716 2125 21 883 2194 7 722 2118 12 772 1935 3 849 2375 5 DRESS 929 2021 11 799 2102 21 952 2137 6 769 1862 7 1106 1869 5 949 2122 10 TRAP 1067 2111 4 985 2212 8 1016 1991 5 1060 1997 4 LOT 999 1864 20 932 1628 17 1038 1635 3 930 1644 15 1029 1543 4 1090 1704 5 THOUGHT 984 1613 3 846 1619 2 1011 1479 4 931 1586 3

123 GOAT 916 1740 9 755 1685 35 785 1773 9 764 1589 13 838 1489 12 835 1385 6 GOOSE 626 1586 9 537 1454 12 762 1595 5 643 1503 13 737 1441 7 789 1522 2 FOOT 672 1576 11 637 1629 4 679 1334 2 737 1908 2 Importantly, any distributional analysis of vowel classes rests on the assumption that Rebecca and Carolina’s performances modeled imagined speaker vowel systems to some extent. Another possibility is that indexation of another identity in performative speech is done at the level of a marked20 lexical item or token that is produced as an outlier. Use of a single token to mark an identity is often discussed in terms of morphosyntactic or morphophonological variables (Silverstein 2003). Though this could be because the opportunity to use a marked morphosyntactic form occurs overall much less frequently than the opportunity to change vowel production and because ‘non- standard’ grammatical features are typically more overtly stigmatized than phonological ones (Cheshire, Kerswill, and Williams 2005), many studies have demonstrated the indexical power of a marked phonetic or phonological variant used as little as once (e.g., Johnstone and Kiesling 2008, among many others) or a proportionally small number of times as compared to the unmarked, expected variant (e.g., Labov et al. 2011). The small token count and wide variability within each performance vowel class examined here makes it impossible to even identify possible outliers that could be functioning as these special marked variants.

4.5.2.1 GOOSE and FOOT

The Baby and The Mom share what seems to be a merger or near-merger in FOOT and GOOSE, even though such a feature is absent from Rebecca’s own speech (Figure 4.4). The Hairdresser fronts post-coronal GOOSE tokens, so that those tokens appear in FOOT space. This merger or near-merger is noticeable and auditorily striking in the excerpted audio recordings representing these character voicing sessions. This matches

20The term ‘marked’ is used here, as in Labov et al. (2011), to mean socio-contextually marked, or unexpected.

124 Figure 4.4: F1 and F2 of GOOSE and FOOT per character. All characters have raised FOOT compared to Rebecca, and for some characters raised FOOT may even be merged with GOOSE.

with the distributions found in Rebecca’s performances during roleplay. Rebecca’s use of such a feature as FOOT-raising for performative purposes when voicing personae might imply that this feature is sociolinguistically salient and may be available for stylistic use.

4.5.2.2 KIT, DRESS, and TRAP

Two other surprising areas of diﬀerence among Rebecca and her roleplay personae were noted. The ﬁrst is a front lax vowel lowering, shown in Figure 4.5. All three

125 Figure 4.5: Front lax vowel lowering for Rebecca’s performances.

roleplay personae appear to have quite lowered KIT compared to Rebecca’s own speech. The Baby and the Mom additionally have lowered DRESS. In fact, The Hairdresser’s and The Baby’s KIT have lowered and backed to such an extent that they overlap with DRESS’s distribution. Rebecca and The Mom preserve a distinction between all three front lax vowels, but The Mom does so primarily in F2 space where KIT is retracted. It is not clear what a lowered KIT and DRESS could mean in the case of these personae, specifically whether these features index the same stance or identity in this stylized speech, or whether something about front lax vowel lowering could index different stances or identities for each of these different identities.

126 Carolina’s performance of The Babysitter also shows a divergence from her vowel quality in non-roleplay speech in the front lax vowels (Figure 4.6). Both KIT and DRESS are lowered, and KIT is also extensively retracted. Neither Carolina’s nor Rebecca’s roleplay personae quite fit the pattern for front lax vowel lowering and backing described under the California/Canadian21 Vowel Shift (CVS) (Boberg 2005, 2010),22 This is due to the lack of evidence of TRAP backing in any of the performed roleplay personae that took place on fieldwork days and were captured on the recordings. It is not strictly necessary that performance vowels exactly replicate the patterns found in chain shifts, and if this is indeed a case of diffusion it is not surprising that structural constraints are lost, but it is notable that Rebecca and Carolina both use the more shifted KIT and DRESS with all their performed personae, including roleplaying women at least a decade or two older than themselves.

21Mostly conceived as structurally identical for front lax vowels, but cf. Labov et al. (2005) who found no evidence of KIT lowering in Canada. 22The performances may match the more recent conception of the CVS as a regular sound change that begins with the lowering of KIT (push-chain, Kennedy and Grama 2012).

127 Figure 4.6: Carolina’s and The Babysitter’s front lax vowels.

128 4.5.2.3 GOAT

Figure 4.7 shows that while all roleplay personae overlap with Rebecca’s own pronunciation of GOOSE, the mid back vowel GOAT appears to have a larger range of production in F2 space for the characters than for Rebecca herself. All of the characters produce more fronted variants of GOAT than Rebecca does. Despite this, GOAT F2 means remain fairly close between Rebecca and her performances at 1740 Hz for The Baby, 1685 Hz for The Hairdresser, and 1773 Hz for The Mom, compared to 1589 Hz for Rebecca herself. The addition of multivariate t-distribution ellipses, which apply random vectors of Student’s t-distribution to make up for sparsity in the existing data, shows that it is not that the entire vowel category for GOAT has moved forward in F2 for the performed roleplay personae compared to Rebecca’s non-roleplay speech, but rather that the characters’ GOAT F2 space has expanded towards a fronter F2 dimension. This pattern is not present in the GOOSE distributions, but indicates that it may be particular fronted GOAT tokens that hold indexical power in enacting the roleplay personae. Carolina’s GOAT may show a similar pattern when she performs The Babysitter, though it is less clear with fewer tokens (Figure 4.8).

129 Figure 4.7: Distributions of GOOSE and GOAT for Rebecca and her performed characters. Ellipse represents a multivariate t-distribution with a .95 con- ﬁdence interval.

130 Figure 4.8: Carolina shows no sign of performative high- or mid-back vowel fronting as The Babysitter.

131 4.6 Discussion

Rebecca and Carolina vary their vowel realizations according to context, producing tokens that seem “California-shifted” (compared to their regular speech) in roleplay contexts. One possible account of these patterns is that the performative vowel qualities are enacted unsystematically or on a lexically specific basis, so that any pattern that emerges from the data is an artefact of the lexical items that happen to appear (but cf. Eckert 2008a on how important phonetic outliers in specific lexical items are for stance and identity work in stylistic variation, as well as their ability to drive language change). A close look at the distribution of individual tokens shows that there is not likely to be a difference in phonetic environments that is causing the apparent difference in distributions, though this explanation cannot be ruled out without statistical testing. For example, many of the vowel distributions in the performed characters are made up of the same lexical items appearing multiple times, such as little in all performed roleplay personae as shown in Figure 4.5, and this one lexical item is produced with variation in both F1 and F2 dimensions. Taking the patterns observed here as systematic, there are multiple possible ex- planations. One possibility is that vowel productions are just acoustically variable among these young child participants in a way that happens to mimic the CVS as a result of different levels of language development, attunement to variable patterns, or motor control, and not subject to the sociolinguistic monitor. It could also be that the acoustic quality of the girls’ roleplay personae vowel productions are attributable to a particular articulatory setting, such as lowered jaw or smiling, which have been described as embodied stances that may lead to and maintain the features of the CVS in adult speakers (Pratt and D’Onofrio 2017). Jaw setting or smiling during a performed roleplay persona would be an example of a type of sociophonetic knowl-

132 edge, though at an embodied articulatory level rather than primarily a segmental one. Finally, it is possible that Carolina and Rebecca are beginning to develop the roots of an adult-like stylistic practice that will continue to be shaped by the social, stylistic, and sociolinguistic experiences they have had and will have. Multiple roleplay personae have vowel productions that have been found elsewhere to index a Valley Girl (young female, fun, affluent, carefree) identity even among speakers from New England and Mid-Atlantic dialect regions (D’Onofrio 2015). For both girls, fronted GOAT — not a local dialect feature of Eastern New England English — could be taken as a indexical marker of a young affluent female identity already learned from media or from other speakers’ stylistic use even at this young age. Fronted GOOSE cannot be as clearly attributed to the CVS, as it is found across many dialects of English and could be so common or expected across input from other speakers of all ages and genders as to not deserve notice as an identity marker. Fronted GOAT as well as fronted GOOSE could also have their origins not in the CVS and its indexicality of a young affluent female identity, but, more immediately, from Carolina’s own production as a participant with a Mid-Atlantic English dialect background, where GOOSE and GOAT are systematically fronted, but this factor alone does not explain the lowering of KIT and DRESS in the roleplay personae from both girls. The case of raised and backed FOOT in Rebecca’s performed roleplay personae is deserving of much further thought and study, as this is a feature that Latinx speakers have been found to use previously to index a non-white identity as well as other locally-salient stances and identities (Fought 2002). The fronting of back vowels by these participants deserves much further study through additional individual performance datapoints in the corpus underlying this dissertation as well as through the collection of new data from child participants, particularly in the form of data from sociophonetic perception studies with children.

133 The case of KIT and DRESS lowering without TRAP retraction in Rebecca and Carolina’s performed roleplay personae is also complex and deserving of much further study, but could be taken as another feature of the emergent indexical relationship between shifted vowels and speaking style, along with GOAT and, possibly, GOOSE. It remains unclear whether the salience and indexicality of lowered KIT and DRESS and fronted GOAT would hold for adult speakers in the surrounding community or for the participants themselves outside of a roleplay interaction. In any case, it is clear from these cases of identity performance that an emergent sociolinguistic awareness and stylistic competence has begun to mediate playful interaction, even at an age when some later stages of linguistic and sociolinguistic development are still ongoing.

134 Chapter 5

Peer Affinity and Accommodation in Dialect Acquisition

In this chapter, I examine how friend groups in two of the five homeroom classes change vowel classes and sub-phonemic constraints over the course of the school year. The results presented in this chapter suggest that peer input affects not just phonetic production, but, when combined with peer affinity, can also precede rearrangement of the vowel system towards that of a liked peer, including the emergence of new vowel classes. The results of this study suggest that both phonetic convergence and higher-level phonological accommodation occur among peer groups at this age.

5.1 Background

This section introduces some key concepts with which this study engages. The central issue is that of accommodation and whether it is socially mediated, automatic, or some more complex combination of the two. First, I return to the concept of the sociolinguistic monitor (Labov et al. 2011) as introduced in Chapter 4, discussing how the social meaning to which a form may become correlated over time is dependent on both the form’s presence in input and attention to it. This brings up the problem of deﬁning salience, and, in particular, sociolinguistic salience. Some models that can explain phonetic convergence as well as higher-level linguistic accommodation patterns are introduced (or, in the case of some models discussed in Chapter 4, reintroduced) after a more extensive discussion of some foundational studies that have provided

135 some empirical evidence of how the sociolinguistic process of accommodation takes place.

5.1.1 Input

While the previous chapter showed the Framingham Kindergarten participants’ developing ability to wield linguistic features stylistically, this chapter theoretically foregrounds individual sociolinguistic perception in an attempt to understand participants’ motivation to change toward or acquire features of a second dialect through the process of sociolinguistic accommodation to peers. Speakers and listeners do not just passively absorb and replicate the input they get, but rather pay selective attention to certain parts of the input over others. Many studies of sound change have found a difference in phonetic production and phonetic perception of a change in progress, starting with early work by Labov. For example, Fridland and Kendall (2015) find that regional differences in production — namely, extent of the Southern Vowel Shift — do not imply differences in perception or any effect on speaker identification. Regional difference in production of vowels is thus sometimes, but not always salient in perception. Moreover, attention to a feature (or salience of the feature) is not easily determined by the linguistic level of a feature or inherent linguistic characteristics of the feature. Meta-analysis such as Cheshire et al. (2005) have found that salience may in fact be orthogonal to level of linguistic structure, and Levon and Buchstaller (2015) show that making generalizations about a feature’s inherent salience may be a fruitless pursuit through demonstrating the interaction of multiple features — morphosyntactic and phonological — in judgments of salience. The social meaning of a feature seems to play some role in salience, but it is not the case that every association between linguistic production and a social group,

136 style, or stance is equally salient. What comes to be salient for specific individuals depends on both their social and linguistic experience, as there has to be input that allows speakers to learn these associations. Wagner, Clopper, and Pate (2014) test perception of regional dialect phonological differences in 5–6 year olds, focusing on whether participants were able to tie linguistic differences between speakers to meaningful social factors. They found that children at this age show some ability to pair home dialect of English, a dialect of English from another region, and non-native accented English with relevant cultural items, but that the effect was stronger for their home regional dialect or another regional dialect of English versus non-native accented English compared to between home and regional dialects. A rigorous study of the linguistic patterns or stances found within ethnic communities is also benefitted by, as Noels (2014; 94) advocates, a ‘social psychological perspective’ on ethnicity and language in order to capture the social context of language use, as “identity and language use are interwoven with power and positioning within real and/or imagined communities”. A social psychological perspective foregrounds the individual as a construct in relationship to their accumulation of experiences in their environmental context, including with other individuals. Fridland (2003) succinctly sums up this idea:

These shared practices do not necessarily require individuals’ social co- hesion but merely require shared historical experience and a strongly cir- cumscribing environment that places speakers in a similar social position relative to the external social world. (296)

As discussed in Chapter 4, the sociolinguistic monitor is a posited mechanism for sociolinguistic perception that is logarithmically attenuated to variable input — that is, an adult listener is more reactive to a marked (unexpected and/or salient)

137 sociolinguistic variant when it occurs at a low frequency in the input than when it occurs at a high frequency, while a child listener may show less clear reaction patterns to variable input due to their limited experience of and exposure to sociolinguistic variables and their indexical relationship to social meaning (Labov et al. 2011). This is not surprising given that children are still in the process of building indexical relationships between language and social meaning based on linguistic and social input.

5.1.2 Accommodation and Second Dialect Acquisition

The sociolinguistic monitor, when given linguistic input, “outputs estimates of social distance [from the listener], aﬀect [of the talker], and social structure [of the context]” (Labov 2012; 24). Linguistic accommodation is one possible facet of a more general phenomenon of behavioral accommodation, where one person changes their speech as a consequence of the individual or group with which they are interacting, either to converge in speech and, in so doing, align themselves more closely with that individual or group, or to diverge in speech and bring about greater perceived social distance between themselves and that individual or group (Giles et al. 1973). For instance, in Bourhis and Giles’s (1976) study, Welsh participants who were enrolled in language and culture classes on Welsh for personal interest or as a hobby resisted accommodation to, and in some cases diverged from, an RP interviewer more than Welsh participants who were in Welsh language classes for professional purposes. Giles, Howard et al. (1991) explain this as an eﬀect of alignment of identity, where the Welsh participants who saw themselves as part of the same community/group as the RP interviewer converged in support of this shared identity, and the Welsh participants who did not see themselves as part of the RP interviewer’s community/group

138 had no impetus to converge, but rather, an impetus to enhance their oppositional alignment. In contrast, Trudgill asserts that “if a common identity is promoted through language, then this happens as a consequence of accommodation; it is not its driving force” (Trudgill 2008a). This frames accommodation as a somewhat automatic process in situations of language and dialect contact. Much other work, notably recent experimental work by Babel (2010), has reliably shown that accommodation, while underlyingly automatic, can be amplified or weakened by a participant’s perceived social distance between themselves and a target speaker for vowels with sociolinguistic salience. Although Trudgill believes that accommodation is not overall subject to considerations of group identity, on the notion of salience and indexicality, he does allow that certain features can come to be emblematic.1 Even so, his view of an almost entirely automatic accommodation process represents an extreme that is subject to controversy (see papers in Language in Society 37.2). If cities in the United States were to become less racially, ethnically, and socioeconomically segregated, perhaps there would be an eventual mixing of whatever different local standard, vernacular, and ethnicity-correlated sociolinguistic variants and dialect features exist, if indeed accommodation were an automatic gradual process. Labov (2001b), for one, suggests that language change is “mechanical and inevitable”, and that “social evaluation and attitudes play a minor role” (20).2 For example, Pur- nell (2009) correlates the amount of phonetic accommodation between whites and African Americans in Milwaukee to the amount of cross-ethnic contact the speakers have had over their lives. Labov (2007) allows a minor role for diffusion of new forms among adults in dialect change, but says that the primary driver of dialect change

1Yet he also adds that “it is well to be skeptical about the extent to which this sort of phenomenon does actually occur” (251). 2The density principle.

139 is transmission to young children acquiring language. If the main driver of change is transmission to children rather than diffusion among adults, the question becomes to what extent transmission to young children still in the process of acquiring a first language may also be mediated by adult-like identity, social category, and/or stance indexation concerns, or whether transmission is as automatic a process, dependent on extent of exposure more so than social evaluation and attitudes, as Labov (2001b) describes. A special issue of American Speech on accommodation in ethnic communities puts forward that a local identity construction is the ‘driving force’ of accommodation among face-to-face communities of speakers rather than broad supra-local categories such as ethnic identity (Purnell and Yaeger-Dror 2010). Previous work on ethnolinguistic variation by Laferriere (1979) found that the ongoing NORTH/FORCE merger was underway to different extents across different ethnic communities in Boston. A NORTH/FORCE merger would take place either through a regular sound change towards all words in the two lexical sets being produced with the higher, rounded standard variant (FORCE), or lexical bleeding of words from the unrounded NORTH class to rounded FORCE, but it was not immediately clear from Laferriere’s 1979 paper which of these was taking place in Boston at the time. Instead, her study focused on how speakers from segregated ethnic communities used a merged or non-merged NORTH and FORCE along ethnic lines, and how perception of the non-merged NORTH and FORCE tied it to an Irish ethnic identity. She examined speakers in three ethnic groups (Irish, Italian, and Jewish) and found systematic differences in rate of the local variant (distinct NORTH) both stylistically and in apparent time,

140 and in subjective evaluation of the variants by participants. NORTH was stigmatized at the time by her Jewish participants, as it was associated with an ‘Irish accent’.3 What she interprets as a stronger influence of the family in development of the child phonological system relative to non-family community members4 could also be attributed to the indexical power of the variant to convey alignment or disalignment with an ethnic identity. Laferriere introduces in this paper the term cultural force, which she defines as “the influence which an ethnic group may exert on the political, social, and occupational behavior of its members” (613), later commenting that “the larger sense of the ‘ethnic family’ does the primary job of language transmission”. Many researchers have spent time investigating what the cognitive processes are that lead to the acquisition of sociolinguistic variables rather than short-term accommodation (Chevrot et al. 2000; Chevrot and Foulkes 2013; Díaz-Campos 2005; Foulkes and Docherty 2006; Foulkes et al. 2001; Labov 1989; Nardy et al. 2013; Pierrehum- bert 2001; Roberts 1994, 1997; Smith et al. 2007). Chambers (1992; 686) is especially careful in laying out the differences between short-term accommodation and acquisition, positing that ‘long-term acquisition’ (Trudgill 1986) and dialect acquisition can likely be seen as synonymous terminology. Chambers finds that children immersed in a second dialect learn lexical replacements faster than phonology, and attributes the difference in rate of acquisition to the complexity of what is to be acquired.5

3This is despite the fact that the highest rate of use she reported was among her Italian participants. 4See also Labov (2014), who uncovers an ongoing divergence between white and African American Philadelphians in the split short-a system. He explains this through the lens of the high level of residential segregation along racial lines in Philadelphia, which leads to linguistic contact between white and African American Philadelphia English being restricted to diffusion among adult speakers rather than transmission intergenerationally through first language acquisition. 5Chambers’ remark on lexical diffusion of the second dialect phonological form

Phonological innovations are actuated by the acquisition of particular instances of the new rule or phoneme, and they only become rule-governed or

141 Even within phonology, Chambers (1992) finds that children learn simple phonological rules faster than complex ones. Payne (1980) is another example of how children acquire simple rules of a new dialect’s phonological system, but may not be able to acquire the more complex ones.6 Although she finds an age effect in the second dialect acquisition of the child participants, she does not believe there should be a defined age boundary that separates early and late acquirers of the second dialect. Hopp (2010) describes the ‘critical period’ myth, the contention that beyond a certain age language is not fully acquirable, as masking what actually may be attributed to interspeaker differences in processing resources and efficiency that are correlated with biological age as well as other factors. Other sociolinguistic factors may contribute to whether is new dialect is acquired (see discussion in Nycz 2011, 2015, 2016; who considers the possibility that awareness of a dialect feature may act as a “filter”, or attenuation mechanism, on acquisition of a new dialect). But what is understood by some as social influences on language is understood by others as categoricity of input. For example, in a study of the maintenance of the Southern Vowel Shift among Appalachians (Evans 2004), much of the resistance to change was correlated with density and multiplexity of an individual’s social network with other Appalachians. The reframing of a community as a social network, as examined in the foundational paper by Milroy and Milroy (1992), has predictive capability for diffusion of linguistic innovations, with conservative forms best entrenched by strong, close, and dense networks. Milroy and Milroy also note the role of oppositional stances in social systematic (if ever, in the first generation) after a critical mass of instances has been acquired.

seems to ﬁt well with exemplar models of sociolinguistic variation. 6Simplicity and complexity are deﬁned here by how featurally circumscribed the phonological, grammatical, and lexical contexts of use for a particular variant are.

142 networks, which they term ‘conflict’, in acquisition of or convergence towards versus resistance to linguistic innovations by speakers. Recently, computational modeling of language use and language change have entered into the variationist subfield and allowed us to see what happens when a naive learner, or even a learner with certain encoded biases, receives different types of input (for a good example, see Kirby and Sonderegger 2015). Similar findings about the role of social factors in dialect acquisition can also be captured under certain interpretations of exemplar theory. Evans and Iverson (2007) looked at accent change among university students in a new dialect area in the United Kingdom that differed from the dialect area in which they were raised. They tracked the adjustment of perceptual categorizations of vowels over time for speakers in a second dialect environment to see if changes in production were accompanied by changes in perception. Although the speakers started out with a correlation between production and perception of vowels, there was no significant change in perception accompanying the significant change in vowel production over time. The ability to recognize second dialect vowels in noise also did not change over time, suggesting no processing gains from increased familiarity (cf. Walker 2018 who finds an effect of length of exposure to a second dialect on the ability to transcribe sentences in noise in that dialect). Studies such as this one convey how complicated it is to enact experiments on accommodation and second dialect acquisition phenomena in natural language. Other recent experiments on accommodation specifically are equally as complex and enlightening. For instance, Babel (2010) provides an experimental result of accommodation that is both automatic and sociolinguistically-mediated. While she views phonetic convergence between two dialect vowel systems, in the lab and in conversation, as an automatic process and one and the same with the mechanism underly-

143 ing sound change caused by dialect/language contact (Trudgill 2008a), she resists a strictly automatist view that collapses extralinguistic individual differences. Through the inclusion of a validated assessment of social bias taken by subjects as a predic- tor of extent of accommodation, she nontrivially proposes that, even at the phonetic level, social biases can affect extent of phonetic convergence in addition to the phonetic priming observed in previous studies. This study, and other subsequent studies like it (see Campbell-Kibler 2012), show that the much studied topic of accommodation in sociolinguistics can also be profitably studied in the laboratory and through perceptual experiments. A close read of Babel (2010) and her previous work (Babel 2012) shows that she equally emphasizes the impact of shared identity and positive affiliation in promoting convergence along with hypothesizing the potential role of a blocking effect of a strong social bias that could go hand in hand with disjoint identities in interaction. Her results from the 2010 study of New Zealanders hearing an Australian dialect show that only the affiliatory stance assumed from a pro-Australia bias significantly mediated the underlying ‘automatic’ phonetic convergence process, with no significant effect of anti-Australian bias on blocking accommodation. It also seems likely that extent of convergence varies by vowel (Babel 2010, 2012; Babel et al. 2014; Walker and Campbell-Kibler 2015). The cause for this is somewhat opaque, but Nycz (2015, 2016, 2018), on adult second dialect acquisition, posits that the local social salience of a vowel in relation to a social identity can hamper or block the accommodation process. In experimental work, initial distance between model talker vowel (what is heard by the subject) and shadower vowel (what is subsequently produced by the subject) seems likely to also play a role as, with differing phonetic realizations of a vowel or differing phonological vowel systems, a larger distance in acoustic space between a model talker vowel and shadower vowel would give the

144 shadower vowel more space to move during convergence (Babel 2012, 2010; Walker and Campbell-Kibler 2015; contra Kim, Horton, and Bradlow 2011; cf. Mitterer and Ernestus 2008 on phonologically-mediated convergence). Various types of theories have been described to account for patterns of interpersonal accommodation. The social psychological models of accommodation that are discussed below are the mostly automatic forward processing model that was conceived by Pickering and Garrod (2013) coupled with the same authors’ interactive alignment theory (Pickering and Garrod 2004), and Communication Accommodation Theory (CAT) (Giles et al. 1973; Giles, Howard et al. 1991). The study also invokes a model of speech common to the ﬁeld of communication sciences, which is often referred to as ‘audience design’ model for stylistic variation (Bell 1984), as it is closely related to CAT and the two are often referred to in tandem in the sociolinguistic literature (e.g., Bucholtz 2003; among many others).

5.1.2.1 Interactive Alignment Theory

In this model, the listener constructs a probabilistic projection of what the speaker’s upcoming utterance will be simultaneously with the speaker saying it, and re-evaluates the probabilistic projection constantly over time with updated input from the speaker so that the projection is increasingly reliable. In this view, convergence is a by-product of increasing linguistic alignment over time between two speakers predicting one another’s upcoming output, and being inﬂuenced in their own speech patterns by that predictive model, with the result that ultimately successful dialogic speech is co- constructed between both speakers (Garrod and Pickering 2009). Figure 5.1 contains a diagram of the full model. The focus of this study will be the levels of phonological and phonetic representation, ignoring eﬀects from higher levels of representation

145 despite the model’s assertion that predictions from these higher representations, particularly at the syntactic and lexical levels, aﬀect predictions at the level of phonological representation. For the current study, this theory would predict that convergence occurs to some extent across all students in a classroom, with those students who produce the most speech showing the least convergence with peers and being the most converged-to by others in the class over time.

Figure 5.1: The interactive alignment model from Pickering and Garrod (2004).

146 5.1.2.2 Audience Design Theory and Communication Accommodation Theory

Communication Accommodation Theory7 foregrounds not just perceived listeners but the entire social context and history of an interaction. This can include how the speaker perceives themselves in alignment or opposition to their listener, the speaker’s attitudes about the listener’s perceived identity and group membership, the speaker’s evaluation of the context of the interaction and utterance, the speaker’s stance towards the content and meaning being negotiated (including towards the interaction itself), and the speaker’s experience of the social meaning indexed by particular linguistic forms and those forms’ associations with socially-salient stances and identities. Under this theory, any accommodation in speech can come about through alignment between interlocutors at one or many of these levels of socio-indexical structure. This model prioritizes neither the speaker nor the listener, but the interaction itself, with speaker and listener roles, and thus, patterns of accommodation, co-constructed and emergent. In Bell’s (1984) ‘audience design’ theory, as discussed in greater detail in Chapter 4, speakers custom-tailor their utterances at all levels, including content, discursive, morphosyntactic, phonological, and phonetic levels, to their addressees and other audience members. Rather than the listener’s model of the speaker being theoretically prior as in the Pickering and Garrod theory, the speaker’s model of the listener initi- ates the convergence process. Although the listener and topic may also motivate style shifting in this model, the central role of speaker agency rather than linguistic priming makes it easier to account for the maintenance of linguistic diﬀerences between social

7Giles’s (1973) and audience design both have Speech Accommodation Theory (SAT) as a precursor. The earliest work on the topic of SAT is published prior to Bell’s (1984) ‘audience design theory’, but the two authors’ work originally spoke to audiences in separate disciplines.

147 identity-based groups as well as between contextual registers/styles. This theory succinctly unites the concepts of convergence and diachronic change from above, where the uptake of innovative variants carries a social distribution (cf. Labov 1966; Biber and Conrad 2009; Bucholtz and Hall 2005). This theory predicts that speakers will accommodate their production towards that of others whom they like, or to whom they want to be more similar.

5.2 Affinity and Attention

This chapter argues that changes in the study participants’ vowel productions are due to interpersonal affinities as well as interactional experiences, in addition to salience of locally-embedded but non-locally relevant social categories and dialect awareness (as is discussed in Chapter 4). I hypothesize that the speaker social attributes influencing accommodation in this study potentially operate on both macro- and micro-levels, due to their instantiation in interpersonal relationships and interactions for the study participants. However, this analysis does not assume that the children are actually aware of macro-social factors that are characteristic of a traditional sociolinguistic analysis of adult speech. Methods for determining the external factors potentially influencing participant productions have been previously described in Chapters 3 and 4, but the affinity measure used in the following analysis is briefly reintroduced below to provide context for how the study hypothesis of socially-mediated accommodation between peers will be tested.

5.2.1 Testing the Role of Input

As reviewed earlier in this chapter, not all theories predict that social factors should have any inﬂuence on accommodation; some experimental results suggest that pho-

148 netic convergence is a straightforward perceptual-acoustic process that is not likely to engage higher systems of linguistic or social meaning (e.g., Pardo et al. 2017). If this is the case, then we might expect to see that it is simply the amount of input overall which has an eﬀect resulting in gradual convergence over time of all participants towards the speaker who provides the most input. Abstract linguistic knowledge or social biases would not be engaged under this hypothesis, so any restructuring of the vowel system that occurs would have to be attributed to drift in acoustic space towards input targets, rather than any top-down (rule-based) restructuring. In Sra. Marshall’s homeroom, this hypothesis leads to the prediction that Rebecca will be the target of phonetic convergence in acoustic space because she is the one who provides the most input (see Table 5.1), while in Sra. Sienna’s homeroom, the prediction is that both Sophie and Kendall will inﬂuence the target of convergence for each other and for their other two participating peers (see Table 5.2).

Table 5.1: Word counts per participant from two days of recordings in Sra. Marshall’s homeroom – one in October and the other in March.

October March Total Rebecca 1,322 3,874 5,196 Ariana 1,196 3,224 4,420 Carolina 1,234 2,811 4,045 Laura 844 1,676 2,520

Table 5.2: Word counts per participant from two days of recordings in Sra. Sienna’s homeroom – one in December and the other in May.

December May Total Sophie 1,707 1,098 2,799 Kendall 1,432 1,232 2,664 Sylvia 808 668 1,476 Beryl 865 530 1,395

149 5.2.2 Nardy et al. (2014)

Accommodation in children has been explored recently in a paper by Nardy et al. (2014). They wonder how the social interactions of young children interact with the accommodation process, in particular whether social network density and frequency of interaction are influential on development of sociolinguistic variation. Nardy et al. studied 11 French Kindergarteners and their teacher longitudinally over two months, and collected data through recording peer group interactions during free play. They focused on three sociophonetic variables in spoken French which had discrete standard and non-standard variants. They examined both children’s proximity to one another within a duration of time and children’s use of the standard and non-standard variants. They were also able to use proximity and affiliation measures as a metric for estimating which children were the most socially integrated and isolated within the class. Their results for rate of standard variants between their two measurement time points showed convergence towards use of the non-standard across the Kindergarten- ers. Across pairs of children, production distance and verbal interactions at the first observation time point were significantly correlated, but this correlation was not significant at the second observation time point. There was no correlation of verbal interactions and production distance between the children and the teacher. The teacher used a higher rate of standard forms than the children and, remarkably, the children diverged even further from the teacher’s rate of standard forms over time. Children’s evaluative judgments of standard variants did not change over the same time period, and production distances and evaluative distances did not correlate between pairs of children. There was also no relationship between production distance and their reciprocal interpersonal attraction measure.

150 At the first time point, the more socially integrated individuals produced the most nonstandard variants, but by the second time point integration scores were more homogeneous across the group, and the correlation was no longer significant. The authors note that it is the individuals who are the most integrated who have the most influence on their peers, so that the convergence towards the nonstandard is directly due to the most centrally integrated children using the nonstandard forms. They argue that this data favors “a process of convergence that is grounded in individuals reproducing variants that they have heard within the context of peer interactions” (289). The production-perception loop, when construed in this way, allows for “implicit interpersonal influences” (292) to be passed through the network of interactions. This aligns with Labov (2001b), whose view is that environment, social forces, and stances determine interlocutors, and density of communication propagates convergence. De- spite constant exposure to the teacher’s standard speech, though, the children do not converge towards the standard variants, but rather towards the speech of their centrally-integrated non-standard peers.

5.2.3 Affinity Mapping

In this study, I also used a measure of affinity to test the influence of peers on phonetic convergence, though one which differs from that used by Nardy et al.. Tables 5.3 and 5.4 present affinity mappings between peers in each of the two homerooms selected for analysis (Sra. Marshall’s homeroom and Sra. Sienna’s homeroom). In this dataset, the number of times a participant says another participant’s name is used as a proxy for unidirectional peer affinity. This measure was chosen over affinity measures used in other studies of child populations (e.g., the affinity surveys used in Chevrot et al. 2011) due to its reliance on the transcript data itself rather than a child’s self-reported

151 attitude towards a peer, which requires assuming a certain level of ability to self-reflect in child study participants. In nearly all cases a participant says a peer’s name in order to get the attention of that peer — a vocative use of the name. Rarely are names used in this dataset to refer to a peer while addressing another peer, the teacher, or the researcher. All vocative uses of a participant’s name were extracted from the year’s worth of transcribed data and counts tallied per participant to provide a proxy for affinity. The assumption underlying this affinity measure is that the more a child likes someone, the more they will try to initiate an interaction with that person or, more broadly, want that person to be paying attention to them.

152 Table 5.3: Unidirectional aﬃnity scores for Marshall homeroom.

Name Home Language/Dialect Neighborhood Ethnicity Carolina Ariana Rebecca Laura Carolina Mid-Atlantic English Coburnville white 96 24 8 Ariana ENEE Saxonville white 47 35 5 Rebecca unknown unknown Latinx 88 49 78 Laura Spanish Framingham Center Latinx 10 16 6

Table 5.4: Unidirectional aﬃnity scores for Sienna homeroom.

Name Home Language/Dialect Neighborhood Ethnicity Sophie Sylvia Beryl Kendall Sophie ENEE North Framingham Black 0 3 19

153 Sylvia unknown unknown white 0 0 3 Beryl unknown unknown Latinx 2 1 2 Kendall Haitian Creole Coburnville Black 2 1 6 5.2.4 Power and Conflict

If speakers converge towards peers with whom they have affinity, the predictions about who will converge towards whom differ from predictions of convergence based on who provides the most input. The concrete predictions from Table 5.3 are that Carolina and Laura will shift towards Ariana’s vowel production, and Ariana and Rebecca will shift towards Carolina’s vowel production. The extensive thematic coding in NVivo undertaken to support the qualitative analysis of the development of style through play in Chapter 4 enables additional nuance to the analysis of phonetic convergence across participants in Sra Marshall’s homeroom. Chapter 4 hints at the social power wielded by Carolina, the fruitless attempts at being the center of attention from Rebecca, and the effortless coolness of Ariana. Such qualities are conveyed through the excerpted transcriptions throughout that chapter. As a prerequisite for the analysis in Chapter 4, the full set of transcripts from Sra Marshall’s homeroom was coded and annotated following the methodology for thematic analysis recommended by Clarke, Braun, and Hayfield (2015). Essentially, this method of coding reflects how each of the girls is treated by their peers in interaction. Instances of talking to a participant were recoded into positive (e.g., apologizing, complimenting, asking for help) and negative (e.g., telling on, rejection, complaining) valences. The results of this recode for Sra. Marshall’s group appear below in Table 5.5. This table shows that Carolina is much more frequently talked to positively and Rebecca is much less frequently talked to positively than are Ariana and Laura, and that Rebecca and Laura are both more frequently talked to negatively than Carolina and Ariana, Rebecca much more so. Rebecca is the only participant in this homeroom that is more often talked to negatively in the transcripts than positively — almost twice as much.

154 Table 5.5: The number of references coded in NVivo across all transcribed data for positive and negative instances ‘talking to participant’.

Talking to. . . Carolina Ariana Rebecca Laura + − + − + − + − Carolina 18 4 6 11 2 2 Ariana 27 2 15 23 11 2 Rebecca 42 9 20 14 37 14 Laura 8 11 6 0 3 11 Totals 78 22 44 18 24 46 50 18

This richer classification of the negative and positive attitudes each participant in Sra Marshall’s homeroom displays towards their peers over the course of the school year supports the validity of the affinity measure described in 5.2.3 — a measure of affinity that is more useful because it is more easily scalable to larger datasets, as it does not involve full qualitative thematic coding of the transcripts but is possible to gather through a simple text search method. Using only the positive valence references as a proxy for affinity, the prediction is that Ariana, Rebecca, and Laura will shift in phonetic production towards Carolina, and that Carolina will shift in phonetic production towards Ariana. These predictions mostly agree with what the vocative affinity measures predict, though the latter actually predicts that Laura will shift somewhat more towards Ariana than Carolina. This qualitative analysis moreover shows not just lack of attention to Rebecca by the other participants, but a majority negative valence attention from each of the other participants. If, as some of the experimental research on accommodation has hypothesized (e.g., Babel 2012), negative attitudes block accommodation or even result in divergence, then any phonetic shift exhibited by Ariana, especially, will be

155 away from Rebecca’s phonetic production, as she has the highest count of references of talking to Rebecca negatively. Carolina and Laura may behave similarly, though they talk to Rebecca far less frequently overall than does Ariana.

5.3 Variables

The following variables are ideal test sites for the study of phonetic accommodation and phonological realignment between peers due to their variable presence in the participants’ speech at the beginning of the school year.

5.3.1 Low Vowel Systems

The low vowel space in Eastern New England English is distinct from all other dialects of English in North America. The low-back vowel space contains a separate, fronted PALM/START class with a pronunciation approximating [a] in addition to a low-back merger of LOT and THOUGHT with a pronunciation approximating [5] or [O]. A depiction of LOT/THOUGHT merger with PALM/START fronting in Eastern New England from the Atlas of North American English (Labov et al. 2005) is shown in Figure 5.2. This system is by no means stable, in that a rapid change in progress towards neutralization of the contrast between PALM and LOT/THOUGHT has been found near the northern dialect boundary (Stanford, Leddy-Cecere, and Baclawski 2012). PALM and START are increasingly backed for younger generations in North- eastern New England (Stanford et al. 2014), in tandem with lexical transfer from PALM to LOT. This instability in the Eastern New England dialect region is not new, given that the BATH class, which had historically shared the [a] phoneme with PALM/START, has shifted forward to match the /ae/ of TRAP in younger generations of speakers

156 and with only a few lexical exceptions.8 Though much work has been done on mergers and contrasts in low vowel space by researchers working on northern Eastern New England areas (Stanford et al. 2012, 2014; Nagy 2001), studies are sparser for variability and change in low vowel systems in the southern and urban areas of Eastern New England.9 Eastern New England English also contains a nasal split in short /a/ (TRAP), where tokens of TRAP with a following nasal (TRAMP) are fronted and raised (La- ferriere 1977). This diﬀers from the short /a/ split in both New York and mid-Atlantic dialect areas, where fronting and raising of TRAP also occurs before certain other phonetic contexts, such as before fricatives, and in certain lexical items (Roberts and Labov 1995; Labov et al. 2005; Labov, Rosenfelder, and Fruehwald 2013). The low vowel system of each participant is examined for relative frontness/backness and merger/split of vowel classes at the beginning and end of the school year for:

• No backness diﬀerence between LOT and THOUGHT

• Backness diﬀerence between PALM/START and LOT

• Backness diﬀerence between BATH and TRAP

• Backness diﬀerence between TRAMP and TRAP

5.3.2 Canadian Raising

The term ‘Canadian raising’ indicates a raised nucleus in front-gliding diphthong PRICE and back-gliding diphthong MOUTH before a voiceless consonant (Chambers

8For example, it is still extremely common in this area for people of all ages to pronounce aunt, a member of the BATH lexical class (Wells 1982), with the [a] vowel. Paj [a]mas is another common example. 9But see Johnson (2007) for work on this topic along the Eastern New England English dialect border with Rhode Island English.

157 Figure 5.2: These maps from Labov et al. (2005) shows the distribution of the LOT/THOUGHT merger (left), PALM/START fronting (center), and nasal short /a/ system (right) that sets Eastern New England English apart from nearby varieties.

1973). Raising of nuclei in both diphthongs is characteristic of the Eastern New Eng- land dialect area, while in neighboring Western New England, New York, and mid- Atlantic dialect areas, a raised nucleus occurs in PRICE but not MOUTH (Labov et al. 2005; Boberg 2010). Labov’s (1963) early Martha’s Vineyard study famously examined the local social meaning of the raised nuclei in these diphthongs. Cana- dian raising has also been found in Northeastern New England (Roberts 2007) but is reportedly also subject to change towards lowered nuclei in younger generations. As the nuclei of these two diphthongs have proven to be a site of variability that is indexical of ideological stance towards localness (Labov 1963) and ethnicity (Boberg 2004), they may be perceptibly subject to social awareness even at such an early age as that of the participants in this study. This study will particularly focus on raising of nuclei in the MOUTH diphthong preceding a voiceless consonant as a diagnostic of an Eastern New England English

158 dialect system, taken together with a low vowel system with TRAMP raising, BATH backing, PALM/START fronting, and a LOT/THOUGHT merger (see Figure 5.3 for a table which puts these features in the broader Eastern New England context). Though not the main focus of this study, the extent to which TRAMP raising is displayed by participants may also indicate the extent to which the Spanish language and Latinx varieties of English inﬂuence the dialect systems that form in this group, as found in Eckert (2008b).

Figure 5.3: Table of Eastern New England English lexical classes and phonemic approximations from Nagy and Roberts (2004).

5.3.3 Coding and Extraction

As shown in Tables 5.6 and 5.7, all tokens of the vowel classes of interest were coded for all participants in the two homerooms, excluding those which were reduced (not bear-

159 ing primary stress or of extremely short duration) or which occurred with substantial background noise. Coding took place in Praat with an aim to collect steady-state F1 and F2 formant values for every viable token in the transcripts of, for the Marshall homeroom, the first October fieldwork day (October 10th 2017) and the first March fieldwork day (March 19th 2018), and, for the Sienna homeroom, the first Decem- ber fieldwork day (December 13th 2017) and the first May fieldwork day (May 2nd 2018). Initially, a steady-state interval of each vowel token was fed into a script which extracted Praat’s predicted LPC formant values for F1 and F2 at the mid-point of each interval. The settings for each Praat formant object were a maximum formant value of 8000Hz and a maximum of 5 formants, following suggestions from Story and Bunton (2015). Steady-state F1 and F2 values assigned to each token through this automated method were then compared to the expected distribution of F1 and F2 values (mean & standard deviation) for American English vowel production in children of this age group (Lee, Potamianos, and Narayanan 1999). Close to 30% of tokens from the automated formant value extraction fell outside of the mean and standard deviation Lee et al. report.10 This large number of outlier tokens were manually recoded for steady-state F1 and F2 based on visual inspection of formant tracks in the recording spectrograms, with no reliance on Praat formant track LPC. A fully manual coding and extraction of steady-state formant values can therefore be suggested for future work on child speech recordings from a non-laboratory environment.

10In at least one vowel class, the low-front TRAP vowel, the discrepancy between the F1 and F2 values coded in the present study and the reported distributions for the same age population from Lee et al. (1999) may be due to ongoing phonetic change in American English towards an increasing amount of backing in F2 space.

160 Table 5.6: Tokens of each vowel class collected from Sra. Marshall’s class data.

Carolina Ariana Rebecca Laura October March October March October March October March PRICE 23 44 45 46 44 44 24 19 MOUTH 13 19 6 14 15 21 12 8 TRAP 17 32 35 31 25 37 23 11 BATH 15 20 7 16 14 13 9 1 PALM 0 4 0 0 0 4 2 1 START 1 9 6 10 5 9 1 0 LOT 23 33 11 31 25 35 9 14 THOUGHT 9 27 14 19 22 30 9 9 FLEECE 7 7 8 12 10 9 13 17 BOAR 1 6 1 12 2 8 7 1 Spanish a 3 4 5 5 6 5 5 5

Table 5.7: Tokens of each vowel class collected from Sra. Sienna’s class data.

Sophie Kendall Sylvia Beryl December May December May December May December May PRICE 39 19 22 13 6 17 13 22 MOUTH 10 7 8 6 6 10 5 8 TRAP 25 16 13 16 9 17 7 18 BATH 7 8 10 12 2 7 8 4 PALM 0 0 2 0 0 0 0 0 START 3 5 3 6 5 7 6 2 LOT 30 17 9 15 8 15 8 11 THOUGHT 29 12 10 19 4 8 7 10 FLEECE 14 8 7 8 5 6 4 6 BOAR 8 5 ? 5 2 4 2 4 Spanish a 1 1 6 1 1 2 5 1

161 5.3.4 Normalization

Analyses are presented in this chapter that use either inter-speaker normalized or non-normalized acoustic formant data as relevant. For any analyses of an individual’s vowel system at a single timepoint, the raw formant values of F1 and F2 are used. For analyses comparing formant values across individuals and/or across timepoints, such as the boxplots shown and any linear regression models, log-transformed normalized formant values are used. In order to normalize the data across speakers and timepoints, vowel classes representing highest and lowest F1 and F2 values per speaker per timepoint were extracted from the data. Following the suggested methodology from Kohn and Farrington (2012, 2017), who ﬁnd non-standard and non-generalizable changes in both sizes and shapes of child vowel spaces over the course of development, FLEECE and BOAR were extracted to stand as the highest (FLEECE) and lowest (BOAR) values possible in F2. In a departure from Kohn and Farrington (2012, 2017)’s recommendation to extract F1 and F2 of TRAP and LOT as well, a single high F1 (low) vowel was chosen (Span- ish /a/), forming an upside-down triangular model of the vowel space that captures maxima and minima in both F1 and F2. Many tokens of central Spanish /a/ were present in the recordings due to participants’ engagement in bilingual communication throughout the school day. The choice of a single vowel class to represent a maximum in the F1 dimension was made to avoid spurious variability in vowel space estima- tions due to ongoing sociolinguistic processes involving fronting, backing, or raising of TRAP and LOT that are the object of study in this chapter. The log-mean regression model recommended in Barreda and Nearey (2018) was used for normalization of log-transformed formant values. This new model was shown by Barreda and Nearey to outperform the Lobanov when dealing with highly variable

162 and otherwise sparse or non-orthogonal datasets, all of which accurately describe the qualities of a corpus of child-directed child speech. Under the Barreda and Nearey method, single parameter log-mean normalization aims to estimate a single parameter per speaker that, when applied, enables log formant values to be comparable with another speaker’s single-parameter normalized log formant values. The normalization is mathematically formulated as a linear regression equation, shown in 5.1. To paraphrase Barreda and Nearey in their description of this equation,

Gvks represents a single token log-transformed formant, which is the output of Ss the

overall displacement value by speaker and N vk the relationship between the vowel class and the formant number. The authors give clear instructions for the implementation of the equation as a linear regression in R, from which output the discovered (treatment coded) Ss speaker coeﬃcients are then extracted from the model and applied as constants to the log-transformed formant values to create new speaker-normalized log-transformed formants for all tokens.

Gvks = Ss + N vk + (5.1)

The present study used a diﬀering speaker displacement value by timepoint, as it can be assumed that substantial growth of the vocal tract will have taken place for at least some 5 to 6 year olds over the course of the 6 months which separate the two timepoints of this analysis. Raw and single-parameter log-mean regression normalized vowel space areas are shown per participant per timepoint in Figures 5.4, 5.5, 5.6, and 5.7.

163 Figure 5.4: Raw vowel space area in F1 and F2 dimensions per participant per timepoint (Marshall).

164 Figure 5.5: Normalized vowel space area in log F1 and log F2 dimensions per participant per timepoint (Marshall).

165 Figure 5.6: Raw vowel space area in F1 and F2 dimensions per participant per timepoint (Sierra).

166 Figure 5.7: Normalized vowel space area in log F1 and log F2 dimensions per participant per timepoint (Sierra).

167 5.4 Phonetic Convergence

Phonetic convergence in F2 space among the low vowels shows a pattern that is similar to the experimental results on vowel convergence discussed in the previous section. Normalized F2 measurements were extracted from all TRAP and LOT tokens occurring before alveolar oral stops.11 Figures 5.8 and 5.9 show median normalized F2 for these vowels occurring before alveolar stops along the y-axis, with positions near the top of the y-axis (lower normalized F2 values) being backer F2 and positions near the bottom of the y-axis (higher normalized F2 values) being fronter F2. Figures 5.8 and 5.9 show an overall convergence in F2 across the four participants in Sra Marshall’s homeroom. The range in normalized F2 across all participants decreases substantially for both vowels. While Ariana’s backing and Rebecca’s fronting of F2 in both TRAP and LOT could be accommodation towards any other participant, Carolina’s backing of TRAP and LOT brings her towards Rebecca’s production rather than Ariana’s. This suggests that amount of input plays a bigger role than aﬃnity in acoustic convergence. Laura seems more resistant to inﬂuence from her peers in straightforward phonetic convergence, judging by the minimal slope of change in F2 between October and March. This may be due to her social peripherality relative to the other three girls. As mentioned previously, Laura spends more time with her Spanish speaking peers than she does with the other participants in her homeroom. Figure 5.10 captures the apparent convergence in acoustic space in both F1 and F2 dimensions between Carolina, Rebecca, and Ariana from October to March. Laura is excluded due to low tokens. In sum, word class means get closer together over the two time points, and the ellipses (indicating standard deviation) get smaller over time.

11Only tokens preceding alveolar oral stops were used in order to control for eﬀects of following environment.

168 Figure 5.8: Normalized median F2 of TRAP tokens before alveolar stops by month for Marshall homeroom. Dots represent individual tokens, while dotted lines connect mean F2 values for each speaker across the two time points.

Sra. Sienna’s homeroom participants also converge on one another’s productions of TRAP and LOT in both F2 space and overall, as shown in Figures 5.11 and 5.12. For TRAP, Kendall has no tokens before non-nasal alveolar stops in the December data. The other three participants appear in Figure 5.11, which shows that they converge closely on one another’s productions in normalized F2 space. For LOT tokens before non-nasal alveolar stops, Sylvia, Beryl, and Kendall all begin and end with an extremely similar median in normalized F2 space, while Sophie must close a large gap in between her fronter LOT production and theirs. Figure 5.12 displays a contradictory ﬁnding for TRAP and LOT. For TRAP, ﬁndings align with the hypothesis that any convergence will largely be towards Sophie’s backer production due to her

169 Figure 5.9: Normalized median F2 of LOT tokens before alveolar stops by month for Marshall homeroom. Dots represent individual tokens, while dotted lines connect mean F2 values for each speaker across the two time points.

abundant speech input throughout the schoolyear, though she will be affected by her peer’s fronter productions. For LOT, it seems that Sophie’s production is not the target of convergence in F2. This could be the effect of a tipping point where the other three participants’ (and potentially other peers’) productions are so similar in normalized F2 space that it overwhelms Sophie’s influence, though this claim would have to be further explored in the dataset and in future work. Figure 5.13 shows that, similarly to the Marshall participants, the Sienna participants converge in both F1 and F2 dimensions towards one another. The appearance of Kendall’s TRAP non-nasal alveolar stops in May, not visible above in 5.11, shows that the median in F1 and F2 space closely approximates her peers’.

170 Figure 5.10: Mean F1 and F2 values by month for TRAP and LOT for Marshall homeroom, with ellipses indicating one standard deviation from the mean and individual tokens plotted in faded colors.

171 Figure 5.11: Normalized median F2 of TRAP alveolar stops by month for Sienna homeroom. Dots represent individual tokens, while dotted lines connect mean F2 values for each speaker across the two time points.

172 Figure 5.12: Normalized median F2 of LOT alveolar stops by month for Sienna homeroom. Dots represent individual tokens, while dotted lines connect mean F2 values for each speaker across the two time points.

173 Figure 5.13: Mean F1 and F2 values by month for TRAP and LOT for Sienna homeroom, with ellipses indicating one standard deviation from the mean and individual tokens plotted in faded colors.

174 5.5 Dialect Acquisition

Next the participants’ vowel systems are examined at the beginning and end of the school year for evidence of accommodation among peers, with the hypothesis that, even if peer affinity may not affect straightforward phonetic convergence in F1 and F2, it may factor into the phonological change involved in dialect acquisition. For Sra Marshall’s homeroom, the October timepoint is used as a baseline and the March timepoint is used as t+1. For Sra Sienna’s homeroom, the December timepoint is used as a baseline and the May timepoint is used as t+1. The low vowel system is classified in F2 space (frontness and backness only), while the presence of Canadian raising is indicated in F1 space (height only). For Canadian raising, the F2 dimension is not relevant to the hypothesis, thus any individual or sociolinguistic variation in F2 in PRICE and MOUTH vowel classes is not considered here.12

5.5.1 Low Vowel Systems

In addition to looking for phonetic change in the overall realization of vowel classes, it is also important to look at how the participants’ vowel class phonogies change over the school year. In this section, individual low vowel systems are mapped to nodes representing hierarchical clustering of tokens using recursive partitioning regression trees (Breiman 2017). The rpart and rpart.plot packages in R (Therneau and Atkinson 2019; Milborrow 2019) allow an unsupervised regression to make multiple hierarchical splits to the data based on a best ﬁt within a set of hypothesized predictors. This

12Although the nucleus of raised vowels does sometimes show fronting or backing in the F2 dimension as well (Chambers 1973).

175 method of classification of clusters of data is called a regression tree, a type of statistical learning. Each participant at each timepoint has their own regression tree, therefore raw F2 values are used instead of normalized F2 values. The set of hypothesized predictors are vowel class (TRAMP, TRAP, BATH, Span- ish a, PALM, START, LOT, THOUGHT, CLOTH) and potential influencing phonetic features of the following segment (voicing, place, manner, nasality, and whether the syllable is open or closed). Each hierarchical split in the data chosen by the model will maximize the between-groups sum-of-squares between nodes (ANOVA) along the F2 dimension.13 The fit of a given model to the data is conveyed by cp, a complexity parameter that represents the increase in the R2 of the model due to a given split. If a possible split would not increase the R2 of the model, it is not attempted. The model summaries in Appendix D report cp, means, mean squared error (MSE), and tokens per node. The hierarchical trees themselves are depicted in Figures 5.14 through 5.21 and 5.24 through 5.32. The figures show, from top, each of the factors selected by the model for classification and the splits chosen within those factors at each stage of separation of the overall tokens out into clusters in F2. They also show F2 value assigned by the model for each cluster after all hierarchical splits have taken place. The number of tokens per cluster is also given underneath the nodes containing the F2 values. In other words, the terminal nodes represent the phonologically relevant divisions in a speaker’s low vowel system.

13An ANOVA of linear regressions confirms that using F1 as a dependent variable, or a combination of F1 and F2 in a multiple regression, does not result in a significant performance improvement over a model that contains only F2 as a dependent variable, which is unsurprising given that all of these are low vowels differing primarily along the backness dimension.

176 5.5.1.1 Baselines

The models for Sra Marshall’s homeroom are visualized in Figures 5.14 through 5.17. The Marshall participants’ vowel systems at the beginning of Kindergarten show variation in vowel classes and constraining phonetic contextual factors on frontness and backness. Carolina’s vowel system in Figure 5.14 aligns with predictions for her low vowel system from her mother’s self-reported mid-Atlantic dialect. She exhibits a LOT/THOUGHT split without START fronting and no nasal short /a/ system (TRAMP is not separate from TRAP). Carolina backs BATH to a central position, the only feature of her vowel system that would not follow from being a speaker of Mid-Atlantic English. The regression kept the vowel classes TRAP and TRAMP together and found that tokens may cluster according to voicing, and, within voiced tokens, according to whether the post-vocalic segment manner is affricate or stop, but a close look at the number of observations in the affricate and stop categories (3 and 2 respectively) shows that the data is not especially robust for this following phonetic context in TRAP/TRAMP. The regression made a higher level split between TRAP/TRAMP and BATH, which the regression found to be produced roughly similar in the F2 dimension to Spanish /a/, central in the vowel space. The regression did not find a separate fronted START class, but rather instead that back vowels in LOT, THOUGHT, and START followed by lateral or rhotic segments were produced fronter than those followed by fricatives and stops. In the fricative/stop following phonetic context, Carolina produces a split between THOUGHT/CLOTH and LOT, with THOUGHT/CLOTH produced farther back in the vowel space. There are no tokens of PALM for Carolina in October.

177 Figure 5.14: Regression tree model of Carolina’s low vowel system from October.

178 Ariana displays all the features of a modern Eastern New England English low vowel system, including a fully central TRAP/BATH class in line with the front lax chain shift described in Chapter 4. Ariana’s low vowel system has only a single voicing constraint governing all vowel variation within classes, where a following voiceless consonant leads to a fronter vowel production.

Figure 5.15: Regression tree model of Ariana’s low vowel system from October.

Rebecca exhibits a similar vowel system to Carolina, with a LOT/THOUGHT split in all following contexts but velars, where the pattern is far less clear due to a small number of tokens. Rebecca’s caregivers did not complete the survey, so little is known about her home situation. It is unclear whether the lack of expected LOT/THOUGHT merger is due to Carolina’s immediate inﬂuence and Rebecca’s quick accommodation, or whether Rebecca herself hears a LOT/THOUGHT split in caregiver speech at home. There is some recent evidence that non-white Boston-area communities (speciﬁcally, in nearby Dorchester) may maintain a LOT/THOUGHT split (Browne and Stanford 2018), so even if Rebecca lacks a non-local caregiver, an entirely local caregiver raised in (and identifying with) a non-white English-speaking

179 community could also possess this feature. Rebecca has traditional Eastern New Eng- land English PALM/START fronting and a nasal short /a/ system like Ariana, but additionally shows BATH backing like Carolina.

Figure 5.16: Regression tree model of Rebecca’s low vowel system from October.

Our predictions for Laura’s baseline system are to see the inﬂuence of Spanish spoken in the home, with no distinct TRAMP, and many vowel classes sharing a production space with central Spanish /a/. These predictions do not entirely hold, as Laura shows a distinct TRAMP and a LOT/THOUGHT split in a voiceless following context. Her low vowel system also shows the local nasal short /a/ system, but has BATH, PALM, Spanish /a/, and TRAP all produced in shared a central F2 position. She also has no START-fronting. The girls show lots of inter-speaker variability at this initial time point, with individual systems largely consistent with what we’d expect given what we know about their caregivers. Notably, out of all the participants in Sra. Marshall’s homeroom, only Laura and Ariana share the backing of a merged TRAP/BATH all the way to the low central position where Spanish /a/ and PALM is produced. Out of all the participants in Sra. Marshall’s homeroom, only Ariana possesses the merged

180 Figure 5.17: Regression tree model of Laura’s low vowel system from Oc- tober.

181 LOT/THOUGHT that diﬀerentiates Eastern New England English from surrounding regional dialects in the Northeast. Regression models were also run to reveal splits and mergers in the low vowel system for Sra. Sienna’s homeroom participants, shown in Figures 5.18 through 5.21 as well as in Table D.2. Due to fewer tokens (shorter recordings and lack of playtime during recordings), a lower threshold cp value was used for Sienna participants than for Marshall participants (Sienna models have cp threshold set to .005 while Marshall models had it set to .01). This results in the tree having a larger number of branches in the Sienna data than the Marshall data. Closer examination of the trees will show that some branches only contain a single token, contributing to the overall sense that the tree contains more branches. In the December recording, Sophie has a merged CLOTH, LOT, and THOUGHT, except for velar and lateral tokens where there is phonetic backing of F2. START is not found to be distinct from THOUGHT. She has no BATH-backing, but does have TRAMP-fronting. This is largely in line with Sophie’s parents’ reported ‘Boston accent’ spoken in the home environment, but lacking the vernacular dialect pronun- ciations of fronted START (to the extent that START is fronted compared to LOT but not statistically distinct from THOUGHT) and backed BATH. Kendall has a LOT/THOUGHT distinction, but it is not clear that she produces a distinctly back CLOTH in line with THOUGHT.14 She has fronted START, the nasal short /a/ system (TRAMP), and backed BATH. Haitian Creole is reportedly spoken at home, presumably in addition to English given her L1 English competency. Similar to Laura, whose family spoke Spanish at home, Kendall produces TRAP in

14All CLOTH class tokens are followed by fricatives, making it diﬃcult to disentangle eﬀects of word class from following manner.

182 Figure 5.18: Regression tree model of Sophie’s low vowel system from December.

the central Spanish /a/ space. In Haitian Creole, like Spanish, the low vowel space has only one central vowel. Beryl similarly maintains a contrast between LOT and THOUGHT, but it is clearer to see than with Kendall that Beryl produces CLOTH backer than LOT, aligning with expectations for the overall low-back vowel space when there is a LOT/THOUGHT distinction. Similar to Sophie, velar and lateral tokens of both vowel classes are backer overall (Kendall similarly shows backing of laterals, along with nasals). Beryl exhibits fronting of START in addition to backing of BATH. Beryl’s parents did not ﬁll out the home language survey, so it is unknown what dialect or language is spoken in the home. Due to lack of a parent survey we do not know whether Beryl’s family spoke Spanish at home, but she shows a similar pattern

183 Figure 5.19: Regression tree models of Kendall’s low vowel system from December.

to Laura and Kendall in production of TRAP in Spanish /a/ acoustic space, and all three girls also show a distinct fronted TRAMP. Sylvia has a full LOT/THOUGHT/CLOTH merger with fronted START. She has a backed BATH separate from TRAP with velar fronting in TRAP, as well as a separate fronted TRAMP. Sylvia’s parents did not ﬁll out the home language survey, so it is unknown what dialect or language is spoken in the home. Given that it is unknown what regional dialect is spoken at home, Sylvia seems to show the typical Eastern New England English low vowel system pattern.

5.5.2 Canadian Raising

184 Figure 5.20: Regression tree models of Beryl’s low vowel system from De- cember.

Figure 5.21: Regression tree model of Sylvia’s low vowel system from De- cember.

185 5.5.2.1 Baselines

Figure 5.22 shows the normalized log F1 of PRICE and MOUTH in voiced/ﬁnal versus voiceless following contexts for each of the girls in Sra. Marshall’s homeroom in October. While all four girls have PRICE raising in voiceless contexts, as is common across most dialects of American and Canadian English, only three of the girls exhibit unambiguous Canadian Raising of MOUTH in voiceless contexts. Rebecca does not raise MOUTH. For everyone except Ariana, PRICE raises to more of an extent than MOUTH does, but for Ariana MOUTH is extremely raised.

Figure 5.22: Marshall October normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts.

The slight MOUTH-raising occuring in Carolina’s October speech is a departure from her otherwise typical Mid-Atlantic English dialect features, as most Mid-Atlantic English speakers should produce a raised PRICE but not MOUTH in voiceless contexts.

186 The December data from the Sienna homeroom in Figure 5.23 shows that only Beryl and Kendall substantially raise the PRICE vowel in a raising context, while Sophie and Sylvia show diﬀerent patterns. Sophie raises PRICE only very slightly, while Sylvia shows a comparatively raised PRICE even in the non-raising context.

Figure 5.23: Sienna December normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts.

As above, only MOUTH-raising is relevant to differentiating the Eastern New Eng- land English dialect from surrounding regional and supra-regional dialects. Sylvia’s December speech shows robust evidence of prominent raised MOUTH in voiceless contexts, with a striking median difference of 340 Hz between voiceless versus voiced and final contexts. Beryl shows some evidence of raised MOUTH in December as well (a difference of 100 Hz), while Sophie and Kendall show no evidence of MOUTH-raising.

187 5.5.3 Testable Hypotheses

Table 5.8 summarizes the presence or absence of each of the Eastern New England English features under study for each participant. Of the Marshall participants, Ar- iana exhibits the greatest number of traditional ENEE dialect features. In Sra. Si- enna’s homeroom, it is Sylvia, who even has the obsolescing distinct BATH. The other participants all have some features of traditional ENEE, but not all, with Car- olina having only two and lacking a LOT/THOUGHT merger, attributable to the presence of a caregiver with a contrastive mid-Atlantic dialect in the home. For the LOT/THOUGHT distinction exhibited by those other than Carolina in the October data, it is unclear whether this feature is due to adoption of another peer’s distinction that has already taken place prior to the October period of data collection, or whether the LOT/THOUGHT contrast is present in the phonological systems they are exposed to at home and in their communities. Table 5.8: The baseline vowel systems for each participant. (v) indicates the presence of a feature in a voiced context only.

Marshall Carolina Ariana Rebecca Laura LOT/THOUGHT merger X (v) START fronting XX TRAP/BATH split XX (v) TRAP nasal system XXX MOUTH raising XXX Sienna Sophie Kendall Sylvia Beryl LOT/THOUGHT merger XX START fronting XXX TRAP/BATH split XXX TRAP nasal system XXXX MOUTH raising XX

Taking the baseline systems together with the aﬃnity scores summarized in Sec- tion 5.2.3, we can make speciﬁc predictions about how the girls should adjust their

188 vowel systems over the course of the school year. These predictions are summarized in Table 5.9. For each participant, their predicted low vowel system is shown if only amount of input matters (change in low vowel system towards peer who provides the most input), or if affinity towards a certain peer plays a role (change in low vowel system towards peer speaker likes the most). Cases where the two expectations would lead to concrete differences in a participant’s vowel system by the end of the year are bolded. One potential outcome is that the vowel system of the peer who provides the most speech in the classroom will be taken up by the other participants before the end of the year. This translates to, for Marshall, the other three participants shifting to look more like Rebecca, and, for Sienna, the participants shifting towards Sophie, while Rebecca moves towards Ariana and Sophie moves towards Kendall. If accommodation takes place towards Sophie’s production, then Sylvia, Beryl, and Kendall will lose Canadian Raising in both PRICE and MOUTH. If Sophie accommodates to Kendall’s production, she will gain PRICE-raising but not MOUTH-raising. Because of Beryl and Sylvia’s lack of affinity for any of the participants, if they changed their low vowel systems to match Sophie’s production, this would be evidence that the role of overall input may be at play. If not only input but affinity plays a role, it is expected that Carolina will shift rapidly towards a full Eastern New England English vowel system to match Ariana’s October production, potentially also losing a TRAP/BATH distinction. Ariana is conversely expected to pick up some of Carolina’s mid-Atlantic dialect features, perhaps specifically the ones that bring her further away from Rebecca’s production. These are namely backing of START and moving away from her nasal short /a/ system. Rebecca is expected to shift to match Carolina’s system more closely than she already does, while Laura is expected to become an even closer match to Ariana’s

189 Table 5.9: For each speaker, their predicted vowel system by the end of year if only input matters for accommodation or if affinity for a specific peer plays a role. Different predictions from input and affinity measures are bolded.

Speaker Input Aﬃnity Carolina Rebecca: no LOT/THOUGHT Ariana: LOT/THOUGHT merger, START fronting, merger, START fronting, no TRAP/BATH split, TRAP TRAP/BATH split, TRAP nasal system, no MOUTH nasal system, MOUTH raising raising Ariana Rebecca: no LOT/THOUGHT Carolina: no LOT/THOUGHT merger, START fronting, merger, no START fronting, TRAP/BATH split, TRAP TRAP/BATH split, no TRAP nasal system, no MOUTH nasal system, MOUTH rais- raising ing Rebecca Ariana: LOT/THOUGHT Carolina: no LOT/THOUGHT merger, START fronting, no merger, no START fronting, TRAP/BATH split, TRAP TRAP/BATH split, no nasal system, MOUTH raising TRAP nasal system, MOUTH raising Laura Rebecca: no LOT/THOUGHT Ariana: LOT/THOUGHT merger, START fronting, merger, START fronting, no TRAP/BATH split, TRAP TRAP/BATH split, TRAP nasal system, no MOUTH nasal system, MOUTH raising raising Sophie Kendall: no LOT/THOUGHT Kendall: no LOT/THOUGHT merger, START fronting, merger, START fronting, TRAP/BATH split, TRAP TRAP/BATH split, TRAP nasal system, no MOUTH raising nasal system, no MOUTH raising Kendall Sophie: LOT/THOUGHT Sophie: LOT/THOUGHT merger, no START fronting, merger, no START fronting, no TRAP/BATH split, TRAP no TRAP/BATH split, TRAP nasal system, no MOUTH raising nasal system, no MOUTH raising Beryl Sophie: LOT/THOUGHT merger, no START fronting, no TRAP/BATH split, TRAP nasal system, no MOUTH raising Sylvia Sophie: LOT/THOUGHT merger, no START fronting, no TRAP/BATH split, TRAP nasal system, no MOUTH raising

190 October production. Sophie would be predicted to gain a LOT/THOUGHT distinction, a fronter START, and a backer BATH through uptake of Kendall’s low vowel system, and Kendall would be predicted to merge LOT, THOUGHT, and START, and merge BATH and TRAP through accommodation to Sophie. The predicted direction of change for the other girls is unclear since they direct relatively little attention to one another during the recording transcripts, though the ethnographic ﬁeldwork shows that Sophie and Kendall are friends who often play together.

5.5.4 Change to Individual Systems

Table 5.9 and Section 5.5.3 summarizes predictions regarding how the children in each homeroom are expected to change their vowel systems according to several hypotheses. This section describes the end-of-year systems for each child. It is found overall that, in the end-of-year data, each participant shows change towards their most-liked peer. This outcome suggests a role for aﬃnity in phonological accommodation.

5.5.4.1 Marshall

Regression trees for the March data for each of the four participants in Sra Marshall’s homeroom appear in Figures 5.24 through 5.27. Model statistics are in Appendix D. While the regression tree model for Carolina’s October data found a signiﬁcant distinction between LOT and THOUGHT, the March model does not distinguish these classes, suggesting that she has merged them over the course of the school year. In October, Carolina did not show a distinctly front START, but by March she has adopted a fronted PALM/START vowel class that is distinct from LOT/THOUGHT. While in October Carolina did not show any nasal fronting in TRAP (TRAMP), the march regression tree shows a signiﬁcant distinction between TRAP and TRAMP. Her BATH backing has also disappeared. These features culminate in her matching

191 closely to Ariana’s October vowel system. Carolina’s merged TRAP/BATH has velar fronting.

Figure 5.24: Regression tree model of Carolina’s low vowel system from March.

In contrast, in the March regression tree Ariana has not backed THOUGHT from LOT and retains this feature from October, though she has lost the fronted PALM/START that was in her October regression tree. This change in her back low vowel space brings her closer to Carolina’s October vowel system. For Ariana, the front of the low vowel space maintains both the nasal short /a/ system and the TRAP/BATH merger she had in her October regression tree, but the TRAP/BATH class in the March regression tree shows a constraint of velar fronting, similar to the velar fronting in TRAP/BATH that Carolina also appears to have developed by March. These adopted features mean that Carolina and Ariana’s low vowel systems adhere closely by March. Rebecca’s low vowel system has also changed between the October and March regression trees. In October, Rebecca had a LOT/THOUGHT distinction with a fronted START, as well as a TRAP/BATH split and a TRAP nasal system. In the March

192 Figure 5.25: Regression tree model of Ariana’s low vowel systems from March.

regression tree, her back low vowel system is characterized by a LOT/THOUGHT merger and a fronted START/PALM. She has also merged TRAP with BATH. Her nasal short /a/ system remains in place. The changes in her vowel system bring her closer to Ariana’s October vowel system, as well as the vowel systems of Ariana and Carolina in March. Laura has moved to a new low vowel system as well in the March regression tree compared to her October regression tree. She exhibited a LOT/THOUGHT contrast in voiced following phonetic contexts only in October, but by March exhibits the contrast in all alveolar and ﬁnal following phonetic contexts, with only dorsal and rounded phonetic contexts lacking the distinction. She retains the short /a/ nasal system she had in October and continues to back BATH. There are no tokens of START. Laura’s March vowel system looks similar to Rebecca’s in October. The March Canadian Raising data in Figure 5.28 shows that, while all girls have maintained Canadian Raising in PRICE, Canadian Raising in MOUTH has changed

193 Figure 5.26: Regression tree model of Rebecca’s low vowel system from March.

194 Figure 5.27: Regression tree model of Laura’s low vowel system from March.

195 since October. It is retained for Ariana and Carolina, and has been adopted by Re- becca.

Figure 5.28: March normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts for Sra Marshall’s homeroom.

5.5.4.2 Sienna

Visualizations of the regression trees for Sra. Sienna’s homeroom May recordings appear in Figures 5.29 through 5.32. As in the December Sienna data, the threshold cp in these models is set to .005, leading to the appearance of branches containing standalone outlier tokens and thus an overall greater number of branches. By May Sophie’s vowel system has lost its totally unambiguous LOT/THOUGHT merger from December, now showing the emergence of a LOT/THOUGHT distinction in a voiced context. This is hypothesized to be due to Sophie’s attention to Kendall’s LOT/THOUGHT contrast, though it could also be from the inﬂuence of Beryl and

196 other peers. Sophie has not acquired Kendall’s START fronting or TRAP/BATH split.

Figure 5.29: Regression tree model of Sophie’s low vowel system from May.

As in May Kendall retains her LOT/THOUGHT split from the December regression tree, Sophie and Kendall now share a constraint on the LOT/THOUGHT contrast that limits it to checked syllables (syllables with codas), which diﬀers from Beryl’s pattern of use where the LOT/THOUGHT contrast is present whether the syllable is open or checked. Kendall has also merged TRAP with BATH and backed START by May. Similar to the case of Carolina, Ariana, and Rebecca, Sophie and Kendall have also by May developed a shared vowel system. In May, Sylvia has a merged LOT and THOUGHT with a fronted START, a backed BATH, and a TRAP/TRAMP split with a fronted velar TRAP. This presents no change from her December system, and she continues to have the most Eastern

197 Figure 5.30: Regression tree model of Kendall’s low vowel system from May.

New England English features of all the participants in both homerooms. She has not moved towards Sophie’s vowel system. Beryl’s vowel system also remains unchanged between December and May, and she retains all Eastern New England English dialect features except LOT/THOUGHT merger; in both December and May, Beryl has produces distinct LOT and THOUGHT vowel classes. Similar to Sylvia, she has also not moved towards Sophie’s vowel system. The May Canadian Raising data from Sra. Sienna’s class appears in Table 5.33. The only MOUTH-raising shown is Beryl, while tokens with the appropriate phonetic context to trigger raising are not available from Sylvia’s May recording. As Sylvia and Beryl were the only participants with raised MOUTH in the December data, it can

198 Figure 5.31: Regression tree model of Sylvia’s low vowel system from May.

Figure 5.32: Regression tree model of Beryl’s low vowel system from May.

199 be seen that Sophie and Kendall have not introduced Canadian Raising into their vowel systems.

Figure 5.33: May normalized log F1 for PRICE and MOUTH vowel classes in voiced, ﬁnal, and voiceless contexts for Sra Sienna’s homeroom.

5.6 Discussion and Limitations

Table 5.10 summarizes the patterns found in all regression tree analysis, focusing on characteristics of the Eastern New England English dialect system. It is clear that Carolina, the only participant with a known non-local parent, has undergone the most vowel system changes by far. With the exception of her loss of the TRAP/BATH split, these changes have made her vowels more similar to those of the Eastern New England English vowel system. In doing so, she has taken up the low vowel system exhibited by Ariana in the October recordings. Ariana has largely not changed her vowel system to look more like Carolina’s Mid-Atlantic dialect system, but the two have developed a shared fronting of velar TRAP. Rebecca has also taken up Carolina

200 and Ariana’s March vowel system, gaining a LOT/THOUGHT merger and losing the TRAP/BATH split. Laura, as expected due to her more distant relationship with the other girls in the friend group, has not entirely converged on any of the other Marshall participants’ vowel systems, but does mirror Rebecca’s production from the October data. Table 5.10: Change between baseline and year end vowel systems for each participant for traditional features of ENEE dialect.

Marshall Carolina Ariana Rebecca Laura Oct Mar Oct Mar Oct Mar Oct Mar LOT/THOUGHT merger XXXX (v) START fronting XXXXX ? TRAP/BATH split XX (v) X TRAP nasal system XXXXXXX MOUTH raising XXXXXX Sienna Sophie Kendall Sylvia Beryl Dec May Dec May Dec May Dec May LOT/THOUGHT merger X (vl,f) XX START fronting XXXXX TRAP/BATH split XXXXX TRAP nasal system XXXXXXXX MOUTH raising X ? XX

Sophie and Kendall have both adjusted their low vowel systems in order to more closely match one another’s production, but otherwise the Sra. Sienna data is characterized by stability in vowel systems. While the participants in Sra. Marshall’s homeroom changed an average of two dialect features between October and March, the change in the Sienna low vowel systems between December and May seems rarer and perhaps more orderly. A reason for this could be the diﬀerence in timepoints, with the data analyzed from Sra. Marshall’s class occuring two months earlier in the schoolyear than the data analyzed from Sra. Sierra’s class. There is a possibility that by December any drastic changes that would aﬀect the participant vowel systems had

201 already taken place and remained largely stable for the remainder of the school year. Another explanation is an additive effect of close friendship between three out of the four participants in Sra. Marshall’s homeroom, where such a relationship only exists between two participants of the four in Sra. Sienna’s homeroom. The adoption of components of another speaker’s vowel system over a relatively long period of time is a difficult process to track when that target speaker is also potentially changing their vowel system. Therefore the data presented does not provide much insight into what the target actually is for the phonological change exhibited by participants, only that change indeed happens. Carolina and Ariana exhibit an increase in number of shared features between October and March, and Rebecca also exhibits a large increase in number of shared features with Carolina and Ariana (from 2 in October to 5 in March in both cases). Though Rebecca tries to get Carolina’s attention more often throughout the year as well as shows more affinity towards Carolina in what she says, she ultimately winds up with Ariana’s vowel system. This could be because Rebecca is tracking Carolina’s system as she changes towards Ariana’s production, or it could be the progression towards a regional norm that is not linked to Rebecca’s experience with any one speaker. The same can in fact be said of the change to Carolina’s vowel system. An argument for the role of attention to a peer’s vowel system is that there are similarities in Carolina’s and Ariana’s phonetic constraints on production by March, especially the emergence of velar fronting in TRAP, which is not a documented feature of Eastern New England English (Labov et al. 2005). Close inspection shows that velar fronting of TRAP is present in all four Sienna low vowel systems by May, though only Sylvia’s low vowel space model shows it in October. More work needs to be done to explore whether this is an understudied regional dialect feature, or whether perhaps this feature has arisen idiosyncratically in this community of Kindergarteners.

202 The lack of a more thorough qualitative discursive analysis of Sra. Sienna’s class means that there is less information overall on which to judge what is motivating convergence between peers. As noted earlier in this chapter, information from the ethnographic fieldwork shows that Sophie and Kendall are close friends, which is also apparent from the number of times Sophie attempts to get Kendall’s attention in the transcribed data from the months of December and May. The lack of additional transcribed months, the lack of playtime data in the recordings, and the shorter duration of recordings means that less is known about the relationships between the participants in Sra. Sienna’s class overall, but the ethnographic fieldwork suggests that neither Sylvia nor Beryl are as close to any of the participants as Sophie and Kendall are to one another. Based on the extent to which Sophie dominates speech in the recordings, the prediction that input from her vowel system will lead to change in Sylvia and Beryl’s vowel systems towards her does not hold up. This mirrors what is also found for Sra. Marshall’s homeroom about the lack of influence that straightforward frequency of speaking overall has on phonological change in peers’ vowel systems, where it would be predicted that the participants would converge on Carolina’s vowel system. Rather, in both homerooms convergence in phonological system may be subject to socially embedded attention to a target peer among other factors. The results here do not support a claim that certain vowel classes are more likely to change in such a variable sociolinguistic environment (e.g., that a merger is more likely than a new vowel class distinction), nor do they give a clue to salience or markedness of a particular dialect feature. The results also do not support a claim that overall talking frequency affects the direction of systemic change towards the most vocal peer. Even the convergence on a regional norm is not supported by the data, since participants seem equally likely to change towards a regional norm as away

203 from it. The simplest explanation that fits this data may indeed be the hypothesis of the large-scale adoption of a target peer’s baseline vowel system, the target peer being who each participant is both most intent on engaging socially, and, therefore, paying the most attention to throughout the school year. So far the possible effect of race or ethnicity on the patterns of dialect acquisition that take place over the course of the school year has not been discussed. Given that only 8 participants are analyzed, and that the type of fieldwork and data collection undertaken is necessarily without experimental controls, the study ultimately does not gather the extent or type of data needed to confidently conclude anything about the role of macro-level race/ethnicity categories in this setting. Nevertheless, there are some observed patterns across homerooms that loosely correspond to macro-level racial/ethnic categories. Though the reason for this correspondence is not clear, they are reported here with the hope that future work on a larger scale and with adult speakers will further explore characteristics of Eastern New England English that may differ between ethnic, racial, and cultural communities (see Stanford 2019). Ariana and Sylvia begin the year with a robust Eastern New England English system and do not change, while Carolina, the only participant known to have a non-local dialect background, adopts it. Rebecca also acquires this system, but in order to do so she must depart from a system that prominently features distinct LOT and THOUGHT vowel classes. In contrast, Sophie begins the year with this system, but moves away from it by May. A consideration of the ethnicity of all participants across homerooms reveals that it is only the white students (Ariana and Sylvia) who both begin and end the year with a LOT/THOUGHT merger, while Rebecca, Laura, and Beryl, the three Latina students in the study, all lack it at the beginning of the year. Laura and Beryl continue to exhibit a full LOT/THOUGHT contrast at the end of the year. Kendall, whose parents identify their family as Afro-Caribbean and

204 who lives in the Coburnville neigborhood in the predominantly Latinx south side of town, also both begins and ends the year with a LOT/THOUGHT distinction. Under the hypothesis of the current study, Sophie, who is African American and whose family lives in the predominantly white north side of town, begins to acquire the LOT/THOUGHT distinction as faciliated by her friendship with Kendall. The chapter makes clear why Ariana will not accommodate to Rebecca’s LOT/THOUGHT contrast at the beginning of the year, but it is not as clear why Sophie acquires Kendall’s, and Laura acquires Rebecca’s, LOT/THOUGHT distinction, while Kendall acquires Sophie’s non-fronted START and non-backed BATH. In line with the suggestion of Browne and Stanford (2018) that distinct LOT and THOUGHT vowel classes may in fact be the norm in non-white communities in the Eastern New England English dialect area, and with the knowledge that social development at the age of Kindergarten may also include developing awareness of social groupings in one’s community based on race and ethnicity, the results of this study may also show the beginnings of a potential development of LOT/THOUGHT as a salient ethnolinguistic variable within this local school community. That said, much more work beyond the scope of this dissertation should be carried out before this is put forward as a reliable explanation of the systemic vowel change that takes place among participants in this study. These ﬁndings do not support an accommodation model for phonological structural change based on input with no role for speaker agency or social motivation, even though a purely input-dependent model may indeed explain the straightforward phonetic convergence that takes place across peers. The stability of Sylvia and Beryl’s low vowel systems would be unexpected by this model, which predicts that change should occur towards Sophie or Kendall who provide more frequent input. Rather, the CAT and audience design models that take into account a speaker’s social motivation

205 for speaking in such a way that facilitates social closeness with, or social distance from, a target peer, predicts both that change will occur and the direction of change that does occur for the low vowel systems of these participants. Although the results of this study do not clarify the speciﬁc attenuation properties of the young child’s developing sociolinguistic monitor, the results do show that children at this age are at least at some level capable of attention to and socially-mediated change in complex structural properties when faced with interspeaker phonological variation.

206 Chapter 6

Conclusion

This chapter summarizes the ﬁndings presented in the previous sections and provide a general discussion which will bring the ﬁndings together and connect them to the foundational purpose of the project.

6.1 Contributions

The hypotheses of the study were that participants will recognize a link between

phonological production and social meaning (Hypothesis 1), accommodation will occur over the course of the school year (Hypothesis 2a), and that accommodation will be motivated by aﬃnity for and alignment between friends (Hypothesis 2b). Evidence was found to support each of these hypotheses. The project used a novel methodology for investigating dialect change and stylistic development during the latter part of the ﬁrst language acquisition process. It is rare for a research project to have ongoing access to a public elementary school to document children’s natural language productions with peers throughout the school day and the school year, rather than relying on interviews with a researcher or testing administrator. The study complemented the large amount of recorded speech data collected with caregiver language attitude and language background surveys, enabling a fuller understanding of the linguistic and social backgrounds of each of the individual child participants. The study suggested recommendations for how to go about

207 collecting sociolinguistic and naturalistic speech data in an elementary school among young children, as well as how to clean, code, and analyze the incredibly variable acoustic productions found within such a broad-ranging and naturalistic corpus. The findings from this study contribute to our understanding of the complex process of first language acquisition in a social context among the child’s initial peer group. In doing so, it responded to the issue identified in Eckert (1997):

Researchers have sought evidence of the social use of variation in adult- like correlations, particularly with gender and class, and in patterns of stylistic variation. Stylistic variation quite obviously requires some kind of awareness of the signiﬁcance of variables. But the younger the age group, the greater the chances that socioeconomic, and in some cases ethnic differentiation in language is not a matter of attending to sociolinguistic diﬀerentiation but of selective exposure.

The study used qualitative and quantitative approaches to stylistic variation and analysis of phonetic and phonological convergence among children, with an eye to situating the observed patterns within a regional, community, and institutional context. It examined full vowel systems on an individual level in order to be able to draw preliminary conclusions about the emergence, maintenance, and retention of shared community systems among a population still acquiring aspects of linguistic as well as social competence. The project addressed an understudied area in need of much additional research — namely, the eﬀect of multidialectal input and stance-taking, as well as variation in social, socioeconomic, ethnic, and racial identities and groups, on the development of sociolinguistic competence and acquisition of a regional dialect. It showed that

208 children, even at this young age and at the ﬁrst introduction to a diverse community outside of their parental and home networks, were beginning to correlate social meaning attached to particular vocalic variants, both locally and regionally, and potentially on an even broader level. It also showed that language is one of the areas in which children accommodate to one another and acquire community norms. Furthermore, the study set an example for similar research projects focused on understanding the sociolinguistic situations of diverse communities through its use of census data and historical segregation policy to illuminate the broad socioeconomic, racial, linguistic, and immigration status patterns at play in the adult community of the city and the surrounding region. It is hoped that future work will continue to address the complex interaction of social and linguistic competencies that results in variable and socially meaningful language practices among children as well as adults. It is important that research on child sociolinguistic development in diverse and underrepresented linguistic communities continues, and that the insights from such research continue to be communicated to early education teachers and speech pathologists.

6.2 Discussion of Findings

Chapter 4 showed how performative speech can be a site where stylistic development takes place during the ﬁrst year of interaction between diverse peers. D’Onofrio (2015) found that persona-based social meanings can inﬂuence perception and that information on personae facilitates the creation of meaning in interaction. Previous work on the development of style among young children also indicates that children use roleplaying scenarios to linguistically act out identities that carry social meaning within their local community context (Slosberg-Andersen 1990). Multiple performed

209 identities during roleplay, mostly older women, but in one case a baby, exhibited distinct vowel qualities from the participants’ non-performative speech. These vocalic differences included a fronter GOAT and a lowered KIT and DRESS. The stylistic variation exhibited during the performed identities of roleplay personae suggests certain vocalic variables carry stylistic and sociolinguistic meaning for the girls, shown by the girls’ propensity to alter these vowels but not other aspects of their vowel systems (particularly GOOSE and TRAP) in order to perform these female identities. Consistent with that sound change is driven by young women (Labov 2001b), this study shows how girls’ emergent social identities are conveyed through their language use even during Kindergarten. Baranowski (2008) finds that teenaged and young adult women lead the change towards back upgliding vowel fronting in both GOOSE and GOAT, while children remain relatively conservative in their production. While GOOSE fronting is common across the United States (Labov et al. 2005), incipient GOAT fronting has not yet been reported in the Eastern New Eng- land English dialect area, so it is possible that television and/or non-local speakers could be influencing the children’s uptake of fronted GOAT as part of the performed identity of a teenaged or young adult female. Front lax vowel lowering, as in the participants’ lowered KIT and DRESS lexical classes, takes place in numerous varieties of English across the English-speaking world (Hickey 2018). The lowering of KIT and DRESS and retraction of TRAP accompanies GOOSE and GOAT fronting and is associated with a young female identity (Eckert 2008b; Kennedy and Grama 2012). This association, that lowered KIT and DRESS may index a young female identity similar to GOAT, could explain why the girls use these shifted vowels to voice their performed characters. If the transition from performance to adult-like styleshifting proceeds in this case, these features could come

210 to be associated with a performed female identity within the community of peers local to the school (Eckert 1996). Chapter 5 tested for accommodation between peers in acoustic phonetic space and in the organization of vowel systems over the course of the school year. It uncovered a fairly straightforward pattern of overall phonetic convergence in each homeroom, with no observable role of aﬃnity or attitude in facilitating convergence or divergence. Where the role of aﬃnity and attitude in convergence and divergence does become apparent is in the acquisition of a peer’s vowel phonology to replace the baseline vowel system with which one enters the school year. Therefore it could be that the relationship between phonetic convergence and phonological change is not direct, with a role for abstraction in phonological change (under some theories) requiring a more intensive attention and/or motivation to align with an interlocutor than that required for phonetic convergence in acoustic space. The study used a proxy for focused attention paid to a peer (for reasons of friendship and/or popularity) and showed that this attention predicted to some extent the vowel system that a participant developed by the end of the year. In other words, some participants were found to replace their low vowel system with that of one of their peers. It was not the case that peers converged on a shared vowel system that was a departure from each of their original vowel systems, but rather one peer converged on another peer’s vowel system that remained relatively stable. In considering the directionality of the change in vowel systems, the discussion in Chapter 5 observed that an important feature in vowel system acquisition seemed to be the merger (or lack thereof) of LOT and THOUGHT. At both the beginning and the end of the year, white children in the sample seemed more likely to exhibit a low back vowel merger. It could be that non-white children in this community have some social incentive to not adopt this merged class if it is subject to sociolinguistic awareness, which study

211 results suggest it could be. This ﬁnding goes against the received wisdom that vowel mergers and non-mergers are below the level of awareness (Labov 1994), but is consistent with previous work on second dialect acquisition among adults that shows stylistic variation in mergers and near mergers, suggesting at least some correlation with social meaning on some level of "phonetic intention" (Johnson and Nycz 2015).

6.3 Limitations and Directions for Future Research

The results of the study suggest that much further research is needed on whether a developing racial or ethnic awareness influences the directionality of accommodation or acquisition between peers in a situation where much interspeaker variability is present. It is not inconceivable that race and ethnicity have some effect on the social groupings that peers sort themselves into in a residentially desegregated school that is still surrounded by thoroughly racially, ethnically, and socioeconomically segregated communities. This study was not able to unpack the intertwined interpersonal relationships from the broader social, community, contextual, and environmental forces that shape them. It is hoped that using the contributions of this study and the numerous others that have come before it on child acquisition of sociolinguistic variation, more attention can be paid to this critical age group for the development of social, linguistic, and sociolinguistic competence as complex interactional processes as well as maintenance and development of ethnolinguistic and ethnic distinctions and divisions, with consideration of how to lessen the pervasive force of such divisions. The limited scale of the study prevented conclusions about the role of macro-level social factors, given that it is complicated to even figure out what a child’s knowledge of macro-level social factors is at the age of the children in the study, and to what extent this could influence their linguistic knowledge and production. Future research

212 should investigate additional situations of linguistic and sociolinguistic variability encountered during this stage of developmental first language acquisition in order to continue to enrich the picture researchers, practitioners, school administrators, and pedagogy specialists have of the possibilites for social and linguistic perceptions and productions to influence one another and result in emergent trends and patterns. De- spite the focus in developmental psycholinguistics on a preadolescent population for studies of the final stages of first language development (Clark 2009), it is observed broadly in sociolinguistics that full development into an adult-like sociolinguistic actor continues to take place throughout the adolescent years. A view of acquisition of sociolinguistic variation as an aspect of first language acquisition suggests an extension of the domain of developmental psycholinguistics and potential for interdisciplinary cross-over with social psychology and sociolinguistics. Nevertheless, this study establishes that much can be learned about sociolinguistic development from the stylistic variation and accommodation patterns found among very young children.

213 Appendix A

Additional Demographics Tables

The data informing the representation index come from the Massachusetts Depart- ment of Elementary and Secondary Education Kindergarten Enrollment Report for the 2017–2018 school year, last updated on January 12, 2018. The equation for this measure, by district, is (LK + BK) − wK LK + BK + wK where LK represents reported enrolled Latino Kindergarteners, BK represents reported enrolled Black Kindergarteners, and wK represents reported enrolled white Kindergarteners. The result of this equation is a value between −1 and 1, where values > 0 are found in districts where non-white Kindergarteners outnumber white Kinder- garteners, and values < 0, conversely, are found in districts where white Kinder- garteners outnumber non-white Kindergarteners. Values close to 0 signal districts where non-white Kindergarteners enroll in equal numbers to white Kindergarteners.

214 Table A.1: Representation index ﬁgures for 2017–2018 Kindergarten enrollments of school districts in Suﬀolk, Norfolk, and Middlesex counties.

School Kindergarten Enrollment by Race/Ethnicity Representation Index District County Latino Black White Other Total Total for Index Index

Chelsea Suﬀolk 429 33 39 12 513 501 0.84 Boston Suﬀolk 1629 1187 680 505 4001 3496 0.61 Randolph Norfolk 43 86 37 66 232 166 0.55 Everett Middlesex 286 63 111 32 492 460 0.52

Revere Suﬀolk 304 28 208 37 577 540 0.23 Lowell Middlesex 372 69 311 386 1138 752 0.17 Marlborough Middlesex 182 19 160 30 391 361 0.11 Malden Middlesex 93 78 142 155 468 313 0.09 Waltham Middlesex 186 33 218 50 487 437 0 Somerville Middlesex 143 41 188 55 427 372 -0.01 Cambridge Middlesex 84 108 280 174 646 472 -0.19 Framingham Middlesex 204 58 389 69 720 651 -0.2 Avon Norfolk 7 11 27 3 48 45 -0.2 Stoughton Norfolk 35 45 133 30 243 213 -0.25 Lincoln Middlesex 25 11 68 17 121 104 -0.31

Holbrook Norfolk 10 16 53 16 95 79 -0.34 Norwood Norfolk 36 25 169 53 283 230 -0.47 Medford Middlesex 34 30 188 52 304 252 -0.49 Weston Middlesex 13 10 70 24 117 93 -0.51 Quincy Norfolk 35 54 289 376 754 378 -0.53 Ashland Middlesex 24 9 122 47 202 155 -0.57 Watertown Middlesex 35 8 161 38 242 204 -0.58 Canton Norfolk 19 18 150 34 221 187 -0.6 Brookline Norfolk 43 31 317 218 609 391 -0.62 Weymouth Norfolk 38 22 262 61 383 322 -0.63 Dedham Norfolk 21 8 133 11 173 162 -0.64 Hudson Middlesex 31 4 161 14 210 196 -0.64 Millis Norfolk 16 1 80 5 102 97 -0.65 Newton Middlesex 71 30 520 229 850 621 -0.67 Burlington Middlesex 19 15 180 85 299 214 -0.68 Acton-Boxborough Middlesex 29 7 192 124 352 228 -0.68 Winthrop Suffolk 21 1 120 4 146 142 -0.69 Bedford Middlesex 9 12 116 60 197 137 -0.69 Milton Norfolk 16 31 265 41 353 312 -0.7 Ayer-Shirley Middlesex 13 6 109 14 142 128 -0.7 Woburn Middlesex 17 23 241 43 324 281 -0.72 Stoneham Middlesex 15 6 129 23 173 150 -0.72 Sharon Norfolk 12 6 115 81 214 133 -0.73 Lexington Middlesex 17 15 206 174 412 238 -0.73 Concord Middlesex 18 7 164 31 220 189 -0.74 Billerica Middlesex 23 15 262 53 353 300 -0.75 Dracut Middlesex 21 15 256 21 313 292 -0.75 Foxborough Norfolk 14 4 134 21 173 152 -0.76 Chelmsford Middlesex 23 9 248 88 368 280 -0.77 Arlington Middlesex 34 11 362 115 522 407 -0.78 Natick Middlesex 31 5 304 86 426 340 -0.79 Wayland Middlesex 14 4 153 37 208 171 -0.79 Tyngsborough Middlesex 4 3 62 7 76 69 -0.8 Braintree Norfolk 13 14 250 79 356 277 -0.81 Bellingham Norfolk 9 5 131 11 156 145 -0.81 Belmont Middlesex 12 10 208 90 320 230 -0.81 Wellesley Norfolk 16 8 236 78 338 260 -0.82 Melrose Middlesex 13 11 245 52 321 269 -0.82 Franklin Norfolk 16 8 261 22 307 285 -0.83 Walpole Norfolk 12 7 212 29 260 231 -0.84 Holliston Middlesex 13 1 157 29 200 171 -0.84 Plainville Norfolk 4 3 79 6 92 86 -0.84 Dover Norfolk 0 4 47 10 61 51 -0.84 Needham Norfolk 15 11 314 64 404 340 -0.85 Sudbury Middlesex 12 3 187 40 242 202 -0.85 Carlisle Middlesex 4 0 51 8 63 55 -0.85 Winchester Middlesex 15 1 211 77 304 227 -0.86 Wrentham Norfolk 4 3 109 14 130 116 -0.88 Medfield Norfolk 6 3 154 11 174 163 -0.89 Wilmington Middlesex 7 6 233 23 269 246 -0.89 Wakefield Middlesex 8 4 220 27 259 232 -0.9 Hopkinton Middlesex 6 1 141 54 202 148 -0.91 Tewksbury Middlesex 6 4 214 10 234 224 -0.91 Cohasset Norfolk 1 3 90 1 95 94 -0.91 Reading Middlesex 6 5 249 33 293 260 -0.92 North Reading Middlesex 5 1 154 19 179 160 -0.93 Westford Middlesex 6 1 182 88 277 189 -0.93 Groton-Dunstable Middlesex 5 0 131 13 149 136 -0.93 Norfolk Norfolk 1 2 114 3 120 117 -0.95

215 Appendix B

Parent Dialect Background and Attitudes Survey Text

CHILD LANGUAGE EXPERIENCE QUESTIONNAIRE FOR RESEARCH PROJECT

If you choose to ﬁll out this online version of the questionnaire instead, you do not need to return the hard copy to your child’s homeroom teacher. Regardless, please ﬁll out either the online version or the paper version of the form prior to June 8th.

If you have any questions about any of the material contained on this survey, or would like guidance on how to complete it or to complete it over the phone instead, please reach out to the researcher Shannon Mooney at [email protected]. Thank you!

This survey should take approximately 15 minutes to ﬁll out.

PART A: YOUR CHILD

Please provide answers for this section about your child who is being recorded for the research project this year. Please give details for any or all questions you wish to answer, and feel free to ignore ones that you do not want to answer. Even partial information will be useful.

Child’s name:

216 Child’s age today in years and months:

• 5 years, 0–5 months

• 5 years, 6–11 months

• 6 years, 0–5 months

• 6 years, 6–11 months

Please provide the neighborhood name or location of the child’s current home(s) in Framingham by listing them below. Indicate which is the primary residence if the child stays at multiple homes.

Framingham neighborhood 1:

Framingham neighborhood 2 (optional):

Framingham neighborhood 3 (optional):

Please provide the town/city names (along with state and country names if outside Massachusetts) where your child has lived since birth, with approximate ages in each location. Please list below. (example: ”Framingham, age 4 to present”):

Did your child speak any Spanish before he/she attended Immersion Elementary School? If so, please indicate whether this was due to preschool (or language school) experience or Spanish being spoken in the home (circle the correct answer).

• Yes, my child spoke Spanish at home before attending Immersion.

217 • Yes, my child spoke Spanish at preschool before attending Immersion.

• No, my child did not speak Spanish before attending Immersion.

Does your child speak any languages besides Spanish or English? Please describe how they learned any additional languages (e.g., preschool, language school, church, a parent/grandparent/babysitter).

• Yes, my child speaks a language other than Spanish and English.

• No, my child does not speak a language other than Spanish and English.

If you answered ”yes” above, please ﬁll in the language and who your child learned it from (example: Cantonese — learned from church):

What are the accents/dialects/languages of the adults who look after the child? Please select and fill in below. (We seek info about parents/guardians more than teachers, babysitters, or occasional child-minders, but if you think a nanny or a long- term child-minder has had a significant influence on the way your child talks, please indicate this too.)

QUESTIONS ABOUT ADULT 1

Adult 1 (this is you) has what relation to child (example: mother)?

Please circle the accent/dialect/language below that most closely matches the way Adult 1 talks around the child? Be speciﬁc if you circle an option that contains a blank for more info.

218 • Standard American English — no Boston accent

• Strong Boston accent

• Weak Boston accent

• Accent from another part of New England (specify in more detail below)

• Accent from another part of the US (specify in more detail below)

• A speciﬁc ethnic or cultural variety of English (specify in more detail below)

• A variety of English inﬂuenced by a foreign language (specify in more detail below)

Specify your answer above in more detail here:

Any other comments on the way Adult 1 talks?

QUESTIONS ABOUT ADULT 2

Adult 2 has what relation to child (example: father)?

Please circle the accent/dialect/language below that most closely matches the way Adult 2 talks around the child? Be speciﬁc if you circle an option that contains a blank for more info.

• Standard American English — no Boston accent

• Strong Boston accent

219 • Weak Boston accent

• Accent from another part of New England (specify in more detail below)

• Accent from another part of the US (specify in more detail below)

• A speciﬁc ethnic or cultural variety of English (specify in more detail below)

• A variety of English inﬂuenced by a foreign language (specify in more detail below)

Specify your answer above in more detail here:

Any other comments on the way Adult 2 talks?

QUESTIONS ABOUT ADULT 3

Adult 3 has what relation to child (example: grandmother)?

Please circle the accent/dialect/language below that most closely matches the way Adult 3 talks around the child? Be speciﬁc if you circle an option that contains a blank for more info.

• Standard American English — no Boston accent

• Strong Boston accent

• Weak Boston accent

• Accent from another part of New England (specify in more detail below)

220 • Accent from another part of the US (specify in more detail below)

• A speciﬁc ethnic or cultural variety of English (specify in more detail below)

• A variety of English inﬂuenced by a foreign language (specify in more detail below)

Specify your answer above in more detail here:

Any other comments on the way Adult 3 talks?

PART B: INFO ON LOCAL ACCENTS AND LANGUAGES

What accent/dialect/language do most of the people in your neighborhood/community use most of the time?

Where do people start sounding diﬀerent from your local area? You can give a border like a street (e.g., “the other side of Rte 9”) or highway (e.g., “west of 495”), town boundary (e.g., “Wellesley”), state line (e.g., “NH border”), natural landmark (e.g., “the mountains”), etc. How do people speak diﬀerently there?

Do other communities in Framingham speak in slightly diﬀerent ways than your community? If so, what communities are they and how is their accent/dialect/language diﬀerent?

221 Any additional information that you think is relevant, and information about any particular accents/dialects in the area, your own accent/dialect, or you child’s accent/dialect would be welcome!

Thank you for your time and participation in this survey and research project. If you have any questions, please reach out to the researcher Shannon Mooney at [email protected]

222 Appendix C

Roleplay: Full Transcripts

Table C.1: Rebecca plays Baby Cook. (2018-02-13 00:50:08–01:00:28)

Rebecca 114 Mami! Where’s—

115 Where’s our mami?

116 Yay! Yes, yes.

117 I wanna be a cook!

Carolina 118 I want ﬁve babies!

Rebecca 119 I wanna cook!

120 Niño, niño, niño

121 I wanna cook! Mami I—

122 ’Kay, cook.

223 Carolina 123 Rebecca!

Rebecca 124 Mami, let me cook!

125 Now, now, now, now.

126 Ah-ha-hm.

127 You would be saying that anyway because no mat-

128 ter what, girl!

129 Don’t touch to things!

130 Mami, do you wanna hug me? Baby! {LG}

131 Okay mama!

132 Wait are you really gonna put it—

133 No, no, Mami! Wait, it’s cool.

134 Mami—

135 Mami said I could have cookie.

224 136 I’m making the soup.

137 Get some food, foods.

138 Pull it in, please, put it in this cup!

139 And I’ll—

140 This?

141 Ma!

142 Thank you, let’s mix.

143 I saw that.

144 Let me taste it.

145 Let me go tell Mami.

146 Mami!

147 Mami, taste this cookie that we made!

225 148 Taste it!

149 She says, a little sugar.

150 No, the other one sugar!

151 Let’s have some food!

152 Oh, it’s Mami!

153 Mami! Mami!

154 Mami, could we have cupcake?

155 No! No! Do not swallow that!

156 There! Let’s mix.

157 We need to add a little cup of this.

158 Wait, let me pour it. Wait.

159 Shh, there.

226 160 Yeah no I know!

161 It’s all done!

162 Mami, take, hm, a little, um, a little.

163 That’s it. You thought it needed more.

164 Let’s see if my mommy’s gonna marry somebody!

165 {LG}

166 Mami! Mami! Mami, are you gonna marry some-

167 body?

Carolina 168 No!

Rebecca 169 Okay! Let’s go eat cookies.

170 Lookit! She’s gonna marry!

171 Oh no! One piece of cookie!

172 Ay, no!

227 173 Mommy!

174 Food is ready, everyone!

175 Food is ready!

176 Hey! No, no! {LG} No! {LG} Mama!

177 I don’t know.

178 Food is ready everyone!

179 Beep beep!

180 Do you want this spoon?

181 Okay, who wants food?

Table C.2: Rebecca plays Hairdresser. (2018-02-13 01:00:46–01:13:24)

Rebecca 182 Hairstyle! Okay let’s pick a— it’s okay.

183 Oh, you have a little cute headband.

228 184 Let’s see— put that a little spray. Close your eyes,

185 I’m now you’re gonna spray! Close your eyes, I’m

186 gonna spray! Close your eyes and we’ll do it. Let’s

187 get wet.

188 Open your eyes! Now, do you want me to cut your

189 hair really short? Okay, I’ll cut it where I want to

190 cut it.

191 No, lookit! No hair! Let’s just do her hair. See, I’m

192 gonna cut it a little here, okay?

193 Oh my gosh. She’s actually very positive. Let me

194 see. Yes, I told—

195 Let’s use— let’s use the other one. Let’s see what’s

196 your— that hair looks silly.

197 Sweetie, food is ready here, go—

198 Mother, could you feed— (sarcastically) Oh, great.

199 Sit down or your hair’s gonna be ugly.

229 200 (to peer) It’s twelve o’clock you almost have to give

201 it to me.

202 No, this is gonna help you. And your hair, okay?

203 No, stop just keep touching it.

204 Now we really gonna see your face! Let’s see— let’s

205 see if can see you. Okay? Sure thing! Let’s see.

206 Food! Who wants this— (To researcher) Oh,

207 you’re back! (Classroom phone rings) Mira, tele-

208 fono. Señora Marshall! Telefono!

209 Stand up. Okay. Let’s sit down

210 Uh, are you sure about using mine?

211 Okay, are you sure you wanna use my hair salon

212 phone?

213 Let me set right now the password. Yes, uh, no.

214 ’Kay you are— you two are videos. Gonna have

215 you internet. ’Kay, well let me put games. Here.

216 You can’t use those stuﬀ okay? They’re important.

230 217 Now put your head up, I’m gonna wash your hair.

Carolina 218 Okay.

Rebecca 219 Ooh wait, your m—

Carolina 220 Do not take that out!

Rebecca 221 I’m not, I’m just putting it back.

Carolina 222 Hey!

Rebecca 223 Hey! Here, have a little blankie. Oh wait, for your

224 hair.

225 No, Peer threw it. So we’re using it. ’Kay. Hey, a

226 little damp please. And water, wouldn’t add water,

227 where’s the water?

228 Hey! I got– I got that ﬁrst!

229 Stop that!

230 No, I can get water if I want!

231 231 Carolina said that it’s okay if she’s wet.

232 Stop it!

233 Señora Marshall!

234 Hold this. You can’t use your phone anymore,

235 you’re gonna have to— I’ll bring it to you back,

236 okay? It’s just you’re gonna hold it so you don’t

237 get wet.

238 No, she said I could use it everyday!

239 I guess so. Keep holding it. No, no, hold it just like

240 that. Now we get water, and—

241 Stop it! I was gonna water here!

242 Stop it! If you do it one more time, then you get

243 wet.

244 You see that? Then you don’t listen. One more,

245 close your eyes. Let me get something else, stay

246 right there, okay? I’ll give it to you.

232 247 Give it back. We don’t need it, here.

248 Hey! You’re not gonna do— I’m not gonna be your

249 friend anymore!

250 Hairstyle! Hey! I’m using that!

251 Hairstyle! Who wants to be so pretty?

252 She’s ﬁrst because longest to short hair. And she

253 has long hair, and you have short.

254 No! Look, it’s even longer than you, so.

255 Sit down. No, sit down. Sit down, quick! No! Back

256 here. Hold this. Hold this, hold this! Sit down

257 quickly!

258 Who wants to do their hairstyle? Sit down quickly!

259 Oh! Stop it! Stop! Hair salon, yeah right! Hair salon!

260 Hold it please! Put your hair down. Sit down, quick!

233 261 I just wanted to do—

262 Okay. There, you’re done, go quick!

263 Hair salon is closed. Salon’s closing!

Table C.3: Carolina and Rebecca play Babysitter and Mom. (2018-03-27 00:26:20–00:32:35)

Carolina 264 Uh, Rebecca, pretend like, um, pretend that you

265 wanted me to– No, pretend that you wanted me to

266 babysit her, okay? So she— so she was sneaky, so

267 she went wherever she wanted to without me seeing.

268 Uh, yeah. You talk through it, well no–

Rebecca 269 What are you doing?

Carolina 270 She went in it.

Rebecca 271 No, no, just pretend she’s eating the apple.

234 Carolina 272 No, no, how about we pretend– pretend I’m not

273 gonna let her get dirty, but I’m gonna go like this,

274 pretend this was a pool, but pretend this is my

275 lunch tray, and she’s like huh, cool, cool. And pre-

276 tend she thought she was swimming. My pool’s so

277 hot!

Rebecca 278 Hey Carolina! Carolina! Carolina I need to talk to

279 you.

Carolina 280 What?

Rebecca 281 How’s the babysitting going?

Carolina 282 Uh, I don’t know where she is. Can she be a bit

283 sneaky sometimes?

Rebecca 284 Sure!

Carolina 285 Oh, so like, a lot?

Rebecca Oh, this is a little? It’s a lot!

Carolina 286 Okay, yeah, ’cause she’s being really sneaky right

287 now.

235 Rebecca 288 Okay bye!

Carolina 289 Trying to— ow! Ow! Ow! Oh, good thing I knocked

290 it over. Trampoline!

Rebecca 291 And then was what?

Carolina 292 Time to try to ﬂy, ow!

Rebecca 293 I’m not gonna do it. One! One, two, three, go!

Carolina 294 What are you eating? Your leftover food, oh yeah.

Rebecca 295 How’s the babysitting going?

Carolina 296 Uh, she, I’m eating her right now.

Rebecca 297 What are you feeding her?

Carolina 298 Um, my leftover food.

Rebecca 299 What?

Carolina 300 My leftover nachos.

236 Rebecca 301 Which is— where are you taking it? What did you

302 say?

Carolina 303 I’m feeding her my leftover nachos.

Rebecca 304 You’re feeding her your nachos?

Carolina 305 Yeah, my leftover—

Rebecca 306 Ew! What are you doing to her? Ew!

Carolina 307 I’m not doing anything, she just eat—

Rebecca 308 Ew, look at her!

309 Mommy, I missed you!

310 Great! Do you wanna go to— wanna show all

311 those people going there? Sure, but tomorrow when

312 you’re done with ballet, okay?

313 Now can we go?

237 314 Yeah sure. Knock, knock! Oh, here’s her! She only

315 likes to sleep over just for one day.

Carolina 316 Oh, that’s ﬁne. No! Two days!

Rebecca 317 Well, two days, I guess here. She can go to her

318 grandma— her grandma, she can go to a party,

319 anywhere she wants to go! Could I have a chair?

Carolina 320 Yeah, that’s a plastic one. Did they think it was

321 glass? It’s plastic.

Rebecca 322 Carolina!

Carolina 323 Uh, no!

Rebecca 324 It’s mine! Oh, she fell down! I’ll never let you out

325 again.

Carolina 326 I’ll get it, I’ll get it.

Rebecca 327 I’m gonna play with all my Barbie dolls.

Carolina 328 It’s hers, but she let me play with it.

238 Rebecca 329 I mean, I don’t have Barbie dolls but I have toys.

Teacher 330 No, give it to her now.

Carolina 331 Rebecca! Rebecca, she told me to give it back.

Rebecca 332 Señora Marshall! Señora Marshall’s here!

Carolina 333 Oh, I’m sorry that she threw up and she had to go

334 home.

Rebecca 335 Mhm!

Carolina 336 I’m so sorry.

Rebecca 337 Mm, no problem.

Carolina 338 Can you say— can you say that, um, to her?

Rebecca 339 Mhm!

Carolina 340 Kay.

239 Appendix D

Summary Tables for Low Vowel Systems Regression Tree Models

Table D.1: Statistics for the hierarchical regression tree of the October low vowel system F2 data for Sra Marshall’s homeroom.

split cp node mean F2 MSE n Carolina Split 1 0.065 Node 4 1653.857 78244.12 14 Split 2 0.012 Node 5 1769.238 28711.51 21 Split 3 0.010 Node 6 2121.588 32064.48 17 Node 7 2390.125 93120.11 16 Ariana Split 1 0.191 Node 4 1503.417 38153.41 12 Split 2 0.043 Node 5 1862.714 149478.1 14 Split 3 0.029 Node 12 2192.733 26552.2 15 Split 4 0.010 Node 13 2432.036 18166.11 28 Node 7 3058.111 69609.65 9 Rebecca Split 1 0.184 Node 5 1970 168237.1 7 Split 2 0.046 Node 7 2855.5 79235.92 6 Split 3 0.020 Node 8 1525.5 41743.85 20 Split 4 0.014 Node 9 1703.136 27066.57 22 Split 5 0.010 Node 12 2038.4 48868.4 25 Node 13 2188.765 58295 17 Laura Split 1 0.214 Node 3 2810.833 57852.14 6 Split 2 0.020 Node 4 1801.211 106996.7 19 Split 3 0.010 Node 10 2130.571 28579.96 21 Node 11 2276.917 14888.74 12

240 Table D.2: Statistics for the hierarchical regression tree of the December low vowel system F2 data for Sra Sienna’s homeroom.

split cp node mean F2 MSE n Sophie Split 1 0.222 Node 4 1435 41170 12 Split 2 0.018 Node 6 2259 26841 25 Split 3 0.011 Node 7 3314 118487 7 Split 4 0.009 Node 10 1479 39724 8 Split 5 0.006 Node 22 1638 41172 28 Node 23 1797 47316 15 Kendall Split 1 0.148 Node 4 1438 15006 2 Split 2 0.047 Node 5 1768 40072 21 Split 3 0.023 Node 7 2680 79144 8 Split 4 0.022 Node 24 1699 0 1 Split 5 0.011 Node 25 2038 13013 5 Split 6 0.010 Node 26 2052 54074 3 Node 17 2335 18548 15 Beryl Split 1 0.089 Node 4 1381 11062 4 Split 2 0.067 Node 10 1525 0 1 Split 3 0.036 Node 12 2104 18409 10 Split 4 0.014 Node 13 2237 8962 8 Split 5 0.010 Node 15 2870 0 1 Split 6 0.009 Node 22 1659 13339 3 Split 7 0.008 Node 23 1792 11020 7 Split 8 0.007 Node 56 2154 0 1 Split 9 0.006 Node 57 2415 4692 2 Node 58 2369 6629 3 Node 59 2695 0 1 Sylvia Split 1 0.058 Node 5 1892 16727 5 Split 2 0.034 Node 7 2625 11178 14 Split 3 0.020 Node 8 1367 0 1 Split 4 0.008 Node 12 2100 0 1 Split 5 0.002 Node 18 1652 32510 3 Split 6 0.001 Node 19 1715 124588 8 Split 7 0.001 Node 26 2305 25786 6 Node 27 2398 0 1

241 Table D.3: Statistics for the hierarchical regression tree of the March low vowel system F2 data for Marshall.

split cp node mean F2 MSE n Carolina Split 1 0.094 Node 5 1776.308 24879.29 13 Split 2 0.019 Node 6 2136.889 38174.68 45 Split 3 0.017 Node 7 2711.429 107545.4 7 Split 4 0.010 Node 8 1487.345 46247.26 29 Node 9 1640.706 79496.97 34 Ariana Split 1 0.164 Node 4 1567.929 17956.92 14 Split 2 0.082 Node 7 3104.7 175005.8 10 Split 3 0.022 Node 10 1911.846 91081.36 26 Split 4 0.016 Node 11 2131.739 146861.2 23 Split 5 0.010 Node 12 2301.207 47001.89 29 Node 13 2537.3 17859.21 10 Rebecca Split 1 0.049 Node 5 1912.111 147843.9 9 Split 2 0.025 Node 6 2236.49 65929.11 49 Split 3 0.020 Node 7 2745.286 62232.49 7 Split 4 0.010 Node 8 1483.1 151932.3 30 Node 9 1681.211 131340 38 Laura Split 1 0.023 Node 3 2467.75 158821.4 16 Split 2 0.017 Node 4 1375 5290.667 3 Split 3 0.010 Node 10 1575.5 22918.65 10 Node 11 1754.333 34626.72 12

242 Table D.4: Statistics for the hierarchical regression tree of the May low vowel system F2 data for Sienna.

split cp node mean F2 MSE n Sophie Split 1 0.094 Node 5 1776.308 24879.29 13 Split 2 0.019 Node 6 2136.889 38174.68 45 Split 3 0.017 Node 7 2711.429 107545.4 7 Split 4 0.010 Node 8 1487.345 46247.26 29 Node 9 1640.706 79496.97 34 Kendall Split 1 0.164 Node 4 1567.929 17956.92 14 Split 2 0.082 Node 7 3104.7 175005.8 10 Split 3 0.022 Node 10 1911.846 91081.36 26 Split 4 0.016 Node 11 2131.739 146861.2 23 Split 5 0.010 Node 12 2301.207 47001.89 29 Node 13 2537.3 17859.21 10 Beryl Split 1 0.049 Node 5 1912.111 147843.9 9 Split 2 0.025 Node 6 2236.49 65929.11 49 Split 3 0.020 Node 7 2745.286 62232.49 7 Split 4 0.010 Node 8 1483.1 151932.3 30 Node 9 1681.211 131340 38 Sylvia Split 1 0.023 Node 3 2467.75 158821.4 16 Split 2 0.017 Node 4 1375 5290.667 3 Split 3 0.010 Node 10 1575.5 22918.65 10 Node 11 1754.333 34626.72 12

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