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Winter 12-15-2017 Anglo and Hispanic Vowel Variation in New Mexican English Susan Brumbaugh University of New Mexico - Main Campus
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Recommended Citation Brumbaugh, Susan. "Anglo and Hispanic Vowel Variation in New Mexican English." (2017). https://digitalrepository.unm.edu/ ling_etds/54
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Susan Brumbaugh Candidate
Linguistics Department
This dissertation is approved, and it is acceptable in quality and form for publication:
Approved by the Dissertation Committee:
Caroline Smith , Chairperson
Chris Koops
Richard File-Muriel
Melissa Axelrod
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ANGLO AND HISPANIC VOWEL VARIATION IN NEW MEXICAN ENGLISH
by
SUSAN BRUMBAUGH
B.A., Spanish, Illinois State University, 2007 M.A., Linguistics, University of New Mexico 2009
DISSERTATION
Submitted in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy Linguistics
The University of New Mexico Albuquerque, New Mexico
December, 2017
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DEDICATION
For my partner in crime, Finnegan Lord Batman Squiggle Pants Brumbaugh
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ACKNOWLEDGEMENTS
I am incredibly grateful to so many people (and one ridiculous Chihuahua). I feel like I’ve won an Oscar, and now I’m about to deliver my speech on stage. It’s about time I put in writing how much you all mean to me!
(Note: I was just informed that the Acknowledgements section doesn’t add to the page count… so I’ll try to keep this as brief as possible.)
I would first like to thank my incredible dissertation committee.
Dr. Caroline Smith, the chair of my dissertation committee, is brilliant, kind, and has always encouraged me to study what is of interest to me. I have learned so much from her throughout the years, in terms of phonetics, phonology, and being a good person. She is also the very first professor I had class with upon moving to Albuquerque ten years ago for the master’s program. Thank you for seeing this through with me until the end! Without Dr. Chris Koops, I would still be making vowel plots with my colored pencils (no, really!). I have learned so much from you, and I am now a much more confident and independent linguist. Writing that book chapter together was the most fun I’ve ever had doing linguistics. Dr. Richard File-Muriel and Dr. Melissa Axelrod gave indispensable feedback and support throughout this entire process, and I truly appreciate all that you have done for me.
There are so many amazing people in the linguistics world at UNM. We have an incredible community of graduate students and professors in the Linguistics department. You guys have made my time in the department so fun and memorable.
I am sincerely thankful for the Global Education Office (GEO), and in particular the Center for English Language and American Culture (CELAC). I spent 8 fantastic years teaching English as a Second Language at CELAC, and I hope to put in another 8 or more in the future! I have developed so many incredible friendships through my time at GEO… you all know who you are!
I never would have ended up in a linguistics graduate program without two incredible professors at Illinois State University: Dr. K Aaron Smith and Dr. Susan Burt. Dr. Smith, also an a graduate from UNM Linguistics, said I would love the program and Albuquerque. How right he was!
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Thank you to my family, in particular my parents, Larry and Diane, and my bizarre little sister, Ronald. I mean, Marie. My entire family has been incredibly supportive of my seemingly never-ending academic endeavors; thank you to Grandma, De, Uncle Phil, Aunt Deedee, and my brother-in-law, Scott.
My very best friends from Illinois, Diane Christine Pueschel and Mallory Blaire Tarter. We have been and continue to be there for each other no matter where any of us is in the world. See you soon!
I was so lucky to join the greatest (read: most hilarious) women’s indoor soccer team not long after moving to Albuquerque in 2007. We are still together today. Lady X is truly the most incredible group of women, and I really can’t imagine my life in Albuquerque without you all. And yes, I know that this will be put in our next highlight reel. On that note, I’m still mad at Crystal for raising her hand and asking a question at my defense. It’s not funny, Milagro. X!
My other “team” is just as fierce: my lady-linguist crew. Laura Hirrel, Brittany Fallon, Keiko Beers, and Corrine Occhino are amazing women without whom there is no way I would have gotten this done. I blame both their peer pressure and their constant support.
I actually can’t figure out what to write about Laura and Phil Hirrel. They are genuinely two of the most incredible people on the planet, and I can’t make light of how much they mean to me and how much they have done for me and Finnegan throughout the years. If I had to sum it up into one word… Melanie!!
My biggest thanks go to Jack and our dogs, Finnegan and Mr. Grumbles. We live such a ridiculously happy life together. And it’s going to be even better, now that I’m done with this!
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ANGLO AND HISPANIC VOWEL VARIATION IN NEW MEXICAN ENGLISH
by
SUSAN BRUMBAUGH
B.A., Spanish, Illinois State University, 2007 M.A., Linguistics, University of New Mexico, 2009 Ph.D., Linguistics, University of New Mexico, 2017
ABSTRACT
This study examines vowel formant differences between English speakers in New Mexico that self-identify as Anglo versus those that self-identify as
Hispanic. Audio recordings were made of 16 New Mexicans reading short stories and carrier phases with embedded target words. F1 and F2 measurements were compared at the 50% point for monophthongs and at the 20% and 80% points for diphthongs. Mixed effects models assessed statistical significance of ethnicity, gender, and interactional effects on vowel formants and trajectory length.
All speakers showed a near-complete overlap of BOT and BOUGHT tokens, supporting a merger. Hispanic men and women patterned together to form a homogenous Hispanic group, and the Hispanic women patterned closer to the Anglo women than did the Hispanic men. The Anglo men and women did not present such a homogenous group. While Anglos shared some commonalities,
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namely the fronting and raising of BAN and the fronting of BOOT and BOAT, there were several cases in which the Anglo men patterned opposite to the Anglo women.
The data were then evaluated in terms of potential participation in the
California Vowel Shift (CVS) (Eckert 2008) and as a Western State (as described in Labov, Ash, & Boberg 2006). Findings support New Mexican English as a
Western State as well as advancing in CVS, both of which are Anglo-led shifts across the country and in New Mexico. Anglo women lead the way with advancement of CVS, Anglo men and Hispanic women follow (though in different ways), and Hispanic men do not participate except for the BOT-BOUGHT merger.
The findings from the Hispanic group were additionally compared with other studies on Chicano English from across the United States, primarily on the topics of diphthong trajectory, BAN-raising, and Hispanic participation in local
Anglo-led sound changes. Findings on diphthong trajectories were inconclusive, and it remains a question for further study. The BAT-BAN split, a commonly documented characteristic in Chicano English literature, was pervasive in the
New Mexican data as well. Lastly, the New Mexican Hispanics patterned similarly to other communities where Hispanic participants, primarily the women, participate in the local Anglo-led sound changes, albeit to a less advanced degree than Anglos.
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Table of Contents
List of Figures ...... xiii
List of Tables ...... xvi
Chapter 1: Introduction ...... 1
1.0 Overview ...... 1
1.1 Motivation for the current study ...... 2
1.1.1 Lack of research thus far ...... 2
1.1.2 Majority-Minority situation ...... 4
1.1.3 New Mexicans’ interest/awareness of this topic ...... 5
1.2 New Mexico: Past and Present ...... 6
1.2.1 New Mexico History ...... 6
1.2.2 Present Day ...... 9
1.2.2.1 Population ...... 10
1.2.2.2 Current rates of Spanish usage ...... 12
1.3 A few notes on certain stylistic choices made throughout this study ..... 14
1.3.1 Race and Ethnicity Terms ...... 14
1.3.2 Non-standard language variety ...... 15
1.3.3 Vowel description conventions ...... 16
1.3.4 Summary ...... 17
1.4 Literature Review ...... 18
1.4.1 Chicano English ...... 20
1.4.1.1 Pre-1970s ...... 21
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1.4.1.2 1970s-1980s ...... 21
1.4.1.3 1990s ...... 23
1.4.1.4 2000s ...... 24
1.4.2 California Vowel Shift and being a “Western State” ...... 28
1.4.2.1 The West ...... 29
1.4.2.2 California Vowel Shift ...... 30
1.4.3 English in New Mexico ...... 33
1.4.4 Issues of Majority-Minority situations ...... 36
1.4.5 Summary ...... 37
1.5 Research Questions and Hypotheses ...... 38
1.5.1 Question 1: Vowels across Gender and Ethnicity ...... 38
1.5.2 Question 2: New Mexico and the California Vowel Shift ...... 40
1.5.3 Question 3: Comparing Chicano English in New Mexico with
Findings in Other States ...... 42
1.6 Organization of the Dissertation ...... 43
Chapter 2: Methodology ...... 45
2.0 Overview ...... 45
2.1 Speakers ...... 45
2.1.1 Recruitment ...... 45
2.1.2 Background questionnaire and speaker selection ...... 46
2.2 Materials ...... 49
2.2.1 Tokens ...... 49
ix
2.2.2 Participant Speaker activities – short story, carrier phrase, picture . 51
2.3 Recording Procedures ...... 53
2.4 Tokens ...... 53
2.4.1 Correction/Cleanup ...... 54
2.4.2 Excluded Tokens ...... 55
2.4.3 Total numbers ...... 57
2.5 Normalization and Scaling ...... 57
2.5.1 Lobanov method ...... 58
2.6 Statistical Procedures ...... 59
2.7 Plotting techniques ...... 60
Chapter 3: Results ...... 62
3.0 Overview ...... 62
3.1 Monophthongs ...... 63
3.1.1 BEET ...... 63
3.1.2 BIT ...... 65
3.1.3 BET ...... 66
3.1.4 BAT ...... 68
3.1.5 BAN ...... 71
3.1.6 BOT ...... 74
3.1.7 BUT ...... 75
3.1.8 BURT ...... 77
3.1.9 BOOT ...... 78
x
3.1.10 Summary of monophthongal vowel space ...... 80
3.2 Diphthongs ...... 82
3.2.1 BOAT ...... 82
3.2.2 BOY ...... 84
3.2.3 BAIT ...... 88
3.2.4 BITE ...... 89
3.2.5 BOUT ...... 90
3.2.6 Summary of Diphthongs ...... 93
3.3 Conclusions ...... 95
3.3.1 Research Question 1 ...... 95
3.3.2 Hypothesis 1 ...... 96
3.3.3 Hypothesis 2 ...... 97
3.3.4 Hypothesis 3 ...... 98
3.3.5 Hypothesis 4 ...... 98
3.4 Summary ...... 99
Chapter 4: Discussion ...... 100
4.0 Overview ...... 100
4.1 Third Dialect, Western States, and California Vowel Shift ...... 100
4.1.1 Third Dialect ...... 100
4.1.2 Western Vowel Space ...... 101
4.1.3 California Vowel Shift ...... 102
xi
4.1.4 Summary of Third Dialect, Western States, and California Vowel
Shift...... 107
4.2 Chicano English ...... 109
4.2.1 BAT/BAN split ...... 109
4.2.2 Distance of Diphthongs ...... 112
4.2.3 Participation in local non-ethnic sound changes ...... 113
4.3 Chapter Summary ...... 115
Chapter 5: Conclusion ...... 117
5.0 Overview ...... 117
5.1 Summary of study and results ...... 117
5.2 Limitations ...... 119
5.3 Future Work ...... 124
5.4 Closing Comments ...... 127
Appendices ...... 129
Appendix A: Questionnaire ...... 130
Appendix B: Reading passages ...... 134
Appendix C: Carrier phrases ...... 136
Appendix D: Picture description task...... 137
Appendix E: Raw and normalized formant values ...... 138
References ...... 161
xii
List of Figures
Figure 1.1: Ethnic makeup of residents of New Mexico, by percentage ...... 10
Figure 1.2: States with the highest percentages of Hispanic inhabitants ... 12
Figure 1.3 Summary of Movements in Northern Cities Vowel Shift ...... 25
Figure 1.4: Summary of movements in California Vowel shift ...... 31
Figure 2.1: Hometowns of participants by number of participants in study 49
Figure 2.2: BAT vowel alignment in Praat ...... 55
Figure 3.1: BEET by Ethnicity and Gender ...... 64
Figure 3.2: F1 BEET by gender ...... 65
Figure 3.3: BIT by Ethnicity and Gender ...... 66
Figure 3.4: BET F1 by Ethnicity and Gender ...... 67
Figure 3.5: BET F2 by Ethnicity ...... 67
Figure 3.6: BET by Ethnicity and Gender ...... 68
Figure 3.7: F1 BAT by Gender ...... 69
Figure 3.8: F2 BAT by Gender*Ethnicity ...... 70
Figure 3.9: BAT by Ethnicity and Gender ...... 71
Figure 3.10 F1 BAN by ethnicity ...... 72
Figure 3.11: F2 BAN by ethnicity ...... 72
Figure 3.12: BAN by Ethnicity and Gender ...... 74
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Figure 3.13: BOT by Ethnicity and Gender ...... 75
Figure 3.14: F1 BUT by Ethnicity ...... 75
Figure 3.15: F2 BUT by Gender ...... 76
Figure 3.16: BUT by Ethnicity and Gender ...... 77
Figure 3.17: BURT by Ethnicity and Gender ...... 78
Figure 3.18: F2 BOOT by Ethnicity and Gender ...... 79
Figure 3.19: BOOT by Ethnicity and Gender ...... 79
Figure 3.20: Vowel diagrams for the four speaker groups ...... 81
Figure 3.21: F2 BOAT by Ethnicity ...... 83
Figure 3.22: F1 offglide BOAT by Ethnicity and Gender ...... 83
Figure 3.23: BOAT by Ethnicity and Gender ...... 84
Figure 3.24: F1 onset of BOY by Gender...... 85
Figure 3.25: F2 onset of BOY by Ethnicity ...... 86
Figure 3.26: F2 offglide BOY by Ethnicity and Gender ...... 86
Figure 3.27: Euclidean Distance of BOY by speaker group ...... 87
Figure 3.28: BOY by Ethnicity and Gender ...... 88
Figure 3.29: BAIT by Ethnicity and Gender ...... 89
Figure 3.30: BITE by Ethnicity and Gender ...... 90
Figure 3.31: F1 BOUT by Ethnicity and Gender ...... 91
xiv
Figure 3.32: Mean Euclidean Distance for BOUT by speaker group ...... 92
Figure 3.33: BOUT by Ethnicity and Gender ...... 93
Figure 3.12: BAN by Ethnicity and Gender (reprinted) ...... 96
Figure 3.34: Vowel quadrilateral by ethnicity ...... 98
Figure 4.1 BOOT by ethnicity and gender ...... 101
Figure 4.2 BOAT by ethnicity and gender ...... 102
Figure 4.3 F2 means by speaker for BAT and BAN ...... 110
xv
List of Tables
Table 1.1: Largest New Mexican cities, Hispanic & White percentages ...... 11
Table 1.2: Percentage of people 5 years and older who speak Spanish at
home, ranked by percentage of Spanish-speakers that speak English
less than “very well.” ...... 13
Table 1.3: Lexical set used to represent individual vowels in this study .... 17
Table 2.1 Participants and their hometowns ...... 48
Table 2.2: Words used in elicitation activities ...... 51
Table 2.3: Breakdown of final token counts by speaker group ...... 57
Table 3.1: Summary of main effects on BEET normalized F1 ...... 64
Table 3.2 Summary of main effects on BET normalized F1 ...... 66
Table 3.3: Summary of main effects on BET normalized F2 ...... 67
Table 3.4: Summary of main effects on BAT normalized F1 ...... 68
Table 3.5: Summary of main effects on BAT normalized F2 ...... 69
Table 3.6 Summary of main effects on BAN normalized F1 ...... 71
Table 3.7 Summary of main effects on BAN normalized F2 ...... 72
Table 3.8: Summary of main effects on BUT normalized F1 ...... 75
Table 3.9: Summary of main effects on BUT normalized F2 ...... 76
Table 3.10: Summary of main effects on BOOT normalized F2 ...... 78
xvi
Table 3.11: Significant effects for monophthongs ...... 80
Table 3.12: Summary of main effects on BOAT normalized F2 onset ...... 82
Table 3.13: Summary of main effects on BOAT normalized F1 offglide ...... 83
Table 3.14: Summary of main effects on BOY normalized F1 onset ...... 85
Table 3.15: Summary of main effects on BOY normalized F2 onset ...... 85
Table 3.16: Summary of main effects on BOY normalized F2 offglide ...... 86
Table 3.17: Summary of main effects on BOY normalized Euclidean
Distance ...... 87
Table 3.18: Summary of main effects on BOUT normalized F1 onset ...... 90
Table 3.19: Summary of main effects on BOUT normalized Euclidean
Distance ...... 91
Table 3.20: Summary of main effects for diphthongs ...... 94
Table 3.21 Euclidean Distances by group ...... 94
Table 4.1: Participation in 3rd Dialect and Western States Vowel
Characteristics...... 108
Table 4.2: Participation in California Vowel Shift ...... 109
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Chapter 1: Introduction
1.0 Overview
This dissertation examines vowel production in English by university-age
(18 to 28 years old) New Mexicans that self-identify as either Anglo or Hispanic.
It addresses the question of vowel variation based on ethnicity and gender in a historically understudied region of the country. I describe differences between
New Mexico vowel varieties and other varieties that have been labeled as
“Chicano English” throughout the United States, and I show that New Mexican speakers only participate partially in the California Vowel Shift (CVS). Finally, I share some suggestions for future research in both the realm of Chicano English as well as the context of linguistic research on English within the state of New
Mexico. Analysis of linguistic data from a number of Anglo and Hispanic speakers in this work show that English variation in New Mexico is multi-faceted and has not yet been fully described by current works in the literature.
This chapter first discusses the background and motivation for the study.
Next, I give a brief overview of the history of New Mexico, a necessity in order to understand the uniqueness of this state and provide context for the English variation amongst New Mexican speakers. That history will also frame the selection of current census data described in the following section. I then explain the nomenclature of languages varieties, ethnic groups, and vowels utilized throughout the dissertation. The literature review in this work surveys the topics
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of Chicano English, Western States vowels, and the CVS in relation to this study.
Finally, I state my research questions and their corresponding hypotheses.
1.1 Motivation for the current study
The topic of vowel production by English speakers in New Mexico merits research for a number of reasons. This section explains not only why this study is important, but also how it adds to the current body of literature on the topics at hand.
1.1.1 Lack of research thus far
Little linguistic research has been performed on English in New Mexico.
One reason may be due to the fact that English in New Mexico isn’t overtly distinctive, unlike the English found in Boston, New York, or the Great Lakes area. I believe a larger reason is due to the incredible linguistic diversity of the state. New Mexico is home to nearly a dozen other languages, all of which have a longer history in the state than English, and many of which have a shorter projected future.
The Spanish language has hundreds of years of presence in New Mexico, and one variety of Spanish is quite unique: whereas other states have Spanish brought with more recent waves of immigration, the traditional Spanish of northern New Mexico is, by and large, passed down through families with centuries of residence here (see section 1.2.2.2 for current census data pertaining to Spanish use in the home). This dialect includes unique characteristics at all levels of linguistics, from phonetics to morphology to lexical
2
items (see Bills & Vigil 2008). Many aspects of this dialect derive from long ago, dating back to the time of Spanish colonization, while others result from the high rates of bilingualism and extremely close contact between English and Spanish in New Mexican culture. Bills and Vigil (2008) explain that traditional New
Mexican Spanish is not impervious to change. Instead, Mexican Spanish has begun to displace some of the characteristics of New Mexican Spanish in recent years.
In addition to Spanish, much linguistic work within New Mexico also focuses on the rich and diverse indigenous languages throughout the state. New
Mexico is home to individuals of 19 federally recognized pueblos, two Apache tribes, and the Navajo Nation (New Mexico Indian Affairs Department 2017) who speak eight languages that span four distinct language families (New Mexico
Secretary of State 2017). In terms of language endangerment, one of these languages, Jicarilla Apache, is rated as shifting, meaning that children are not learning the language (Simons & Fennig 2017). The rest are rated as threatened, meaning that although all generations can use the language to at least some extent for face-to-face communication, the outlook is still grim (Simons & Fennig
2017).
In sum, it is easy to see how and why relatively little work has been done in regard to English in New Mexico, as there is a plethora of other languages to be studied here, many of which just do not exist outside of this state. Traditional
New Mexican Spanish as well as the indigenous languages of New Mexico are
3
all minority languages in contact with the linguistic powerhouse that is English. It makes sense that the majority of research in the state would be in relation to and in support of these languages and their speakers.
1.1.2 Majority-Minority situation
While the English of New Mexico may not be as saliently distinct as is found in Boston, New York, or the Great Lakes area, nor is it without many distinctive features that set it apart from other varieties of English throughout the country. This is likely due, in large part, to the linguistic and ethnic makeup of the state, both past and present. The unique ethnic composition in New Mexico is such that Hispanics make up the highest proportion of English-speakers within the state (U.S. Census Bureau 2010). Exact population and census figures will be discussed in section 1.2.2.1. While Chicano English has been studied in many locales across the country, very few places have a population that is nearly
50% Hispanic. This puts New Mexico in an unusual position for studies of
Chicano English, as the traditional school of thought in linguistics is that minority ethnic groups either do not adhere to local speech norms, or do so to a lesser extent (Labov, Ash, & Boberg 2006). These norms are created and maintained by the majority population. In the case of New Mexico, then, this may mean that speakers of Chicano English in the state feel less pressure to assimilate to local
Anglo-based linguistic norms, and Anglo speakers may adopt incoming Anglo-led sound changes more slowly.
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1.1.3 New Mexicans’ interest/awareness of this topic
Finally, I have continually been encouraged by interest in this topic on the part of New Mexican laypersons (i.e. non-linguists). When someone asks me what I study, I simply explain that I compare vowels in White and Hispanic people. (An oversimplification, but to-the-point and understandable). Inevitably, each person has an insight or comment about this topic as it relates to themselves, their family, or their classmates. I find it very heartening that this is a topic that community members are aware of.
This community awareness and appreciation for New Mexican English was brought to the forefront in 2012 when a local acting group put together two highly popular YouTube videos entitled “Shit Burqueños (New Mexicans) Say"
(Blackoutdigital 2012a; Blackoutdigital 2012b). These videos are of an actress portraying Lynette, a fictional Burqueña (person from Albuquerque) who uses local phonetic, phonological, morphological, and syntactic patterns and lexical items. These videos quickly became very popular throughout the state as New
Mexicans recognized and identified with these unique linguistic characteristics.
Lynette went on to achieve a local celebrity status, featuring on the local news multiple times, appearing as spokesperson of the 2012 State Fair, delivering numerous speaking engagements, and continuing to produce videos. The first two “Shit Burqueños (New Mexicans) Say” videos (Blackoutdigital 2012a; 2012b) have at present accumulated 2,031,294 views; just shy of the most current estimated state population of 2.085 million people (US Census American
5
Community Survey 1-year Estimates 2015). Currently, the two videos have a combined “thumbs-up” total of 9,042 and a combined “thumbs-down” total of only
312. For every 29 thumbs-up, there is just one thumbs-down, perhaps a record by YouTube standards! New Mexicans recognize and appreciate the uniqueness of the varieties of English present in the state, and this research has been encouraged by that fact.
1.2 New Mexico: Past and Present
This dissertation focuses on vowel formants, Chicano English, and the question of New Mexico’s participation in regional linguistic characteristics. As suggested above, the characteristics of language in New Mexico are a product of developments over the last several centuries of state history. The next section presents a brief overview of that history to contextualize the current linguistic situation in the state.
1.2.1 New Mexico History
Here I step away from linguistics and attempt to give a brief overview of the last nearly four and a half centuries in the land that is now New Mexico.
In 1598, the conquistador Juan de Oñate established the first Spanish settlement at San Juan Pueblo, today called Ohkay Owingeh (Travis & Villa
2011). Thus began the establishment of several Spanish colonies throughout the upper Rio Grande Valley (Carver 1987). For the next century or so, colonizers continued to focus their settlement efforts on this area; Santa Fe was founded in
1610 and Albuquerque in 1706, for example. It was not until the 1700s that
6
colonizers moved on to develop the second frontier area, Arizona (Nostrand
1970).
By the 1820s, many settlers from the United States were moving to the
Mexican lands that today make up the American Southwest, spanning from
Texas to California. However, they were, interestingly, almost never moving to the areas that would eventually become the state of New Mexico. In 1848, the
Treaty of Guadalupe Hidalgo was signed by Mexico and the United States, ending the Mexican-American War (1846-1848). In this treaty, Mexico ceded the land that would be New Mexico and other nearby states to the US. This led to
New Mexico officially becoming a territory of the United States in 1850. Perhaps surprisingly, this did not have much immediate effect on the ethnic or racial demographics of the new territory. Fernandez-Gilbert (2010) notes that New
Mexico is “the only former Mexican territory that remained overwhelmingly
Hispanic until well into the twentieth century” (p. 44). As an example, Nostrand
(1970) notes that by 1850, Non-Mexicans (i.e. Anglos, meaning those of
European descent) were already the majority in Texas and California. Yet, by that year, there were only 1,778 Non-Mexicans out of a total population of 61,547 people in New Mexico. In fact, New Mexico did not experience much of an increase in Anglo settlers until after the Civil War (1861-1865), particularly not until the railroad system connected New Mexico to the rest of the US in 1879
(Fernandez-Gilbert 2010).
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Until the establishment of the railroad, New Mexico was a rather isolated area. Carver (1987, p. 222) explains that the introduction of the railroad “not only altered the 300-year-old culture, but [it] revolutionized the regional economy…
[this] opened up new commercial possibilities, as well as integrative ties with the nation.” It should be clarified that this does not mean there was an abrupt shift in language use and values of those living in New Mexico. Rather, in the earliest years of the railroad in New Mexico, Moyna (2010) describes how monolingual
English-speaking newcomers learned Spanish (as cited in Travis &Villa, 2011, p.
130), and from 1879 through 1912 almost 100 different newspapers in New
Mexico printed editions in Spanish (Fernandez-Gilbert 2010).
Fernandez-Gilbert (2010) notes that the 1890s started the transition to
English, or as Spanish-speakers referred to it, el idioma nacional. New Mexico became a state on January 6th, 1912, and it is at this point that we see the
“shifted position of Spanish from a dominant role to a subordinate one in the new state” (p. 58). As further evidence, Fernandez-Gilbert (2010) refers to the census data from this time period. As of 1890, 69.9% of people were reported as can’t speak English. By 1900 this figure had lowered to 51.1% and by 1910 it was
32.5%. This is not, however, a case of abrupt language shift to English but is instead due to 1) an enormous influx of Anglo newcomers to the state and 2) the state constitution of 1912 requiring English-only education in schools. Thus, instead of a sudden shift towards English, “the turn of the 20th century merely
8
marked the beginning of a prolonged period of widespread Spanish-English bilingualism” (Brumbaugh and Koops in press).
Fast-forward to today, and we see that New Mexico is still situated in a very unique position both ethnically and linguistically. Nostrand (1970) notes that across the United States “Hispanic percentages tend to decrease with increasing distance from the international border” (p. 651), yet north-central New Mexico into south-central Colorado is one of just two areas in the United States where
“Hispanos had not been engulfed by non-Hispanos” (p. 650) by the 1960s. The other non-engulfed area was south Texas. Although very similar in terms of maintaining a high Hispanic proportion of the population, the New Mexico and
Texas communities are extremely different in terms of historical context. While the northern New Mexico/southern Colorado population is made up of “Spaniards and Mexicans (who) were the descendants of longtime colonists” (p. 650), the
Texas communities considered here have experienced high rates of much more recent migration from Mexico. This example highlights New Mexico’s unique ethnic and linguistic history; as we will see below, these trends continue today.
1.2.2 Present Day
This section describes the current population, ethnicity, and linguistic makeup of New Mexico and aims to situate the state within the larger context of the United States. Note that ethnicity and language use are considered separately; people who identify as Hispanic may or may not use Spanish.
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1.2.2.1 Population
New Mexico has a population of 2,085,109 people. According to the US
Census, 48% are categorized as “Hispanic or Latino” and 38.3% are categorized as “White alone, not Hispanic or Latino”. These are the two largest ethnic groups in the state (Figure 1.1). The “Hispanic or Latino” category also includes those that self-identify as Hispanic/Latino and White.
Two or more Black or African American Indian races, 1.7 American, 2 and Alaska native, 8.5
Asian, 1.3
White, not Hispanic or Latino, 38.3
Hispanic or Latino, 48
Figure 1.1: Ethnic makeup of residents of New Mexico, by percentage Source: US Census Bureau 2015 American Community Survey 1 Year Estimates
These percentages are similar to the demographics at the city level for the four largest cities within the state. See Table 1.1 below. Of the four largest cities in New Mexico, three have a higher percentage of Hispanic residents than non-
Hispanic. Rio Rancho is the only large city listed below that does not, as only
36.7% of its inhabitants are Hispanic, while 53.8% are White non-Hispanics. In
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contrast to the other cities listed in Table 1.1, Rio Rancho is very new: the first homes were built in 1962, and the city was originally marketed to retirees from the Midwestern and Eastern region of the United States (CivicPlus 2017).
Albuquerque, Las Cruces, and Santa Fe, each of which has a higher percentage of Hispanics than non-Hispanics, have much longer histories and are in many ways more representative of the historical demographics of New Mexico.
Albuquerque Las Cruces Rio Rancho Santa Fe New Mexico
Population 546,360* 97,643 87,394 81,153 2,059,198
Hispanic or Latino 46.7% 56.8% 36.7% 48.7% 46.3% White (Not 42.1% 37.5% 53.8% 46.2% 38.4% Hispanic/Latino) Table 1.1: Largest New Mexican cities, Hispanic & White percentages Source: 2010 US Census data, most recent city data available *This is the population for Albuquerque only. Note that the population of the Albuquerque Metropolitan Statistical Area (which includes Rio Rancho, among other locales) is 887,077, or 43% of the entire state population.
On a national level, New Mexico ranks #1 in the proportion of Hispanic people in the state population. While New Mexico is just shy of being half
Hispanic with 48% of the population identifying as Hispanic in 2015, the second- and third- highest ranking states, Texas and California, are just over one-third
Hispanic; 38.8% and 38.5%, respectively (American Community Survey 5-year
Estimates 2015). Put differently, nearly one out of every two people in New
Mexico is Hispanic, while just over one in every three people is Hispanic in
California and Texas (Figure 1.2).
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% of State Population that is Hispanic
60 48 50 38.8 38.5 40 30.7 28.1 30 24.5 21.3 19.7 18.8 16.9 20 10 0
Figure 1.2: States with the highest percentages of Hispanic inhabitants Source: 2015 American Community Survey 5-year Estimates
It is clear that the history and development of New Mexico (as described in
Section 1.3.1) has profoundly shaped the current-day demographics presented here. Most important for this study, New Mexico is nearly 50% Hispanic, and it is the only state in the country to have such a high Hispanic population.
1.2.2.2 Current rates of Spanish usage
Of course, identifying as Hispanic does not equate to speaking Spanish.
While Figure 1.2 above showed that 48% of the population of New Mexico identifies as Hispanic (US Census American Community Survey 5-year
Estimates 2015), the second column of Table 1.3 shows that only 26.8% of the state population speaks Spanish (US Census American Community Survey 1
Year Estimates 2015).
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% state population that % Spanish speakers that speak State speaks Spanish English less than “very well” Nevada 21.8 44.5 California 29 41.3 Texas 29.6 40.3 Colorado 12 36 Arizona 20.6 33.6 New Mexico 26.8 26.4 Table 1.2: Percentage of people 5 years and older who speak Spanish at home, ranked by percentage of Spanish-speakers that speak English less than “very well.” Only states in the West with at least 20% Hispanic population were included. Source: US Census Bureau 2015 American Community Survey 1 Year Estimates
Measuring proportions of Spanish-speakers is relatively straightforward.
Investigating the type of Spanish spoken, however, is not as simple. In the case of New Mexico, particularly the northern half of the state, Spanish is likely to be passed from generation to generation through several hundred years, unlike other states where newer immigration accounts for more of the current Spanish language use (Bills and Vigil 2008). While there is not a comprehensive tool in place to determine the variety of Spanish spoken by each Spanish-speaker, some of the US Census data can be interpreted in order to approximate an answer to this question. The third column of Table 1.2 lists the percentage of
Spanish-speakers that speak English less than “very well,” by state. It is likely that the majority of people that speak English less than “very well” in this survey would be newer immigrants who come from a predominantly Spanish-speaking country and have learned English later in life. If that is the case, then the fact that out of this group of states, New Mexico has the lowest percentage (26.4%) of
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less than very well speakers of English supports the idea that a lower proportion of Spanish comes from newer immigration than in other states. Therefore, it can be assumed that more Spanish is passed down generationally in New Mexico than in other states.
1.3 A few notes on certain stylistic choices made throughout this study
In working on this project, I have struggled with the appropriate terms for people, language varieties, and even vowels. Here I explain the terms I use throughout the study.
1.3.1 Race and Ethnicity Terms
Race and ethnicity are extremely complicated and personal subjects. To make matters more complex, race and ethnicity are often delineated for statistical or census-based purposes in one way, but used differently in the
“real world” by the people who are actually being described by such labels
(Zelinsky 2001; Alcoff 2005; Jaimes, Londono, & Halpern 2013; King 2013).
I primarily use the term Hispanic for the non-Anglo group of participants
(i.e. people that often identify as Hispanic/Latino/Mexican-American, and in northern New Mexico, Spanish). I will use the term Anglo to describe the white/Caucasian/“non-ethnic” participants. I acknowledge that this binary set of descriptors (Hispanic, Anglo) is not without its issues, but as other linguists have discussed (Frazer 1996; Gordon 2000; Kendall 2011) there is no perfect set of terms to describe these two groups, or any other ethnic/racial group for that matter. Of the eight non-Anglo participants in my study, all chose “Hispanic” as at
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least one of the race/ethnicity terms with which they self-identify. I have chosen to use the term Anglo over white in order to focus on ethnicity and/or cultural identity rather than phenotype.
1.3.2 Non-standard language variety
I refer to the variety of English used by the Hispanic participants in my study “Chicano English.” For much the same reasons as noted above, I recognize that this term is not accurate today for the population which it aims to describe. While Chicano was originally used in conjunction with Californian
Mexican-American/Latino/Hispanic people who did, in fact, use and self-identify with this term, today it is used rarely, if at all, outside of California. For example, none of the eight Hispanic participants chose “Chicano” as a term they would use to identify themselves. This lack of identification with the term Chicano is not an issue exclusive to New Mexico. Rather, other linguists similarly acknowledge that this is not a label their participants use, and they therefore question its utility within the field of linguistics (Williams 2010, Konopka 2011, as examples).
Nonetheless, Chicano English is the most commonly used and recognized term for this variety of English across linguistics research and literature. Further, many academic institutions today, including the University of New Mexico, have a department called Chicano/a Studies. Therefore, I recognize this norm of using the term Chicano, partly due to its wide use throughout the field, but also because of a lack of a better suggestion for this language variety. While my preference would be the term Hispanic English, there are number of valid
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arguments against it. One such argument is that it is a term created by the United
States government and in that way, it was potentially forced onto the minority by the majority (Taylor, Lopez, Martinez & Velasco 2012). Another issue is that some people that may identify as Hispanic, such as Puerto Ricans and Cuban
Americans, speak a variety of Spanish-influenced English that is distinct from the language variety being studied here (Gramley & Patzold 2004). I hope to expand on this topic in future research.
1.3.3 Vowel description conventions
In terms of vowel description, I will refrain, when possible, from using individual IPA vowel symbols and will instead use a word that includes the vowel sound in question in standard American English. This means that, for example, rather than listing a phoneme between forward slashes, such as /æ/, I will use the word BAT. Table 1.3 includes the complete list.
IPA Symbol Lexical Set Word i BEET ɪ BIT ɛ BET æ BAT æn BAN ɑ BOT/BOUGHT ʌ BUT ɚ BURT ʊ BOOK u BOOT ou BOAT ɑu BOUT ɔɪ BOYD ɑɪ BIDE eɪ BADE
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Table 1.3: Lexical set used to represent individual vowels in this study This practice of using lexical sets over IPA symbols comes with several advantages, particularly for sociophonetic studies that examine regional differences. Lexical sets became widely used starting with Wells (1982) and have continued to be used both in their original form (such as Hall-Lew 2011,
Kennedy and Grama 2012, and Holland 2014) as well as in modified versions. In this study, the lexical set consists of some of the words recorded by participants rather than the standard list from Wells (1982). Kennedy and Grama (2012) highlight two advantages to lexical sets. First, each vowel has “a multitude of regionally dependent realizations but the categorical dimensions of frontness, height, and tenseness are too coarse to capture such fine distinctions in some cases, and simply inaccurate in other cases” (p. 43). Second, the low back vowels BOT, BOUGHT, and even the more central BAT are difficult to specify due to the frequent variation and overlap among these vowels that occurs throughout several varieties of North American English.
1.3.4 Summary
It has now been clearly established that New Mexico has both a unique past and an equally unique present. It should come as no surprise then that New
Mexican English would not simply pattern as just another part of the Western
Dialect Region (see Section 1.4.2.1 for a description of Western Vowel Systems).
Nor does it seem likely that the English spoken by Hispanics, a minority ethnic group in the country as a whole, but almost half of the state’s populace in New
Mexico, would be accurately described by traditional accounts.
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1.4 Literature Review
In this section, I examine the previous research related to the primary topics in my study. First, I review the work on Chicano English, starting with its inception in the middle of the 20th century until the present day. The first few decades of work are understandably less focused than today's work, and the literature review I present for this time frame is wider in scope. The more recent decades of research have become increasingly fine-grained, and it is in these last decades that this literature review will focus on work specifically looking at vowel formants, trajectories, and overall vowel spaces. I then review the concepts of the Third Dialect, Western States, and the California Vowel Shift
(CVS). I consider both findings related to Anglos as well as those related to ethnic minorities and their participation (or lack thereof) in these linguistic phenomena. Next, I examine the previous research on English in New Mexico; much of it is situated within the context of Chicano English or Western Vowel
Space. Then, I present some of the findings and continued questions related to majority-minority situations (where less than 50% of a population is Anglo) including, but not exclusively considering, speakers of Chicano English. This is of interest because most linguistic research on ethnic minorities has taken place in locations where the group of interest is a minority of the population, but that is not the case in New Mexico, where Hispanics are proportionally the largest ethnic group.
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In each of the topics below, the theme of identity is central to understanding the distinctive linguistic features being considered. Humans use language to express membership in the groups with which they align themselves.
Key to the current study are social factors of gender and ethnicity.
Generally, women have been found to simultaneously use fewer stigmatized variants, adopt prestigious forms more quickly, and lead changes in progress (Labov 1990, 2001). At first glance, this combination of linguistic conservatism and linguistic innovation seems contradictory, particularly because new forms are necessarily non-standard early on. However, this can be reconciled by considering whether the variant in question is stable or evolving.
Women use fewer nonstandard forms of stable (e.g. non-changing) variables, and men use more (Wolfram & Schilling-Estes 2004). In terms of innovation, there are two types: change from above, and change from below. Changes from above involve the re-organization of a set of variables in terms of their associated prestige or stigma, and speakers are aware of the social meanings that different variants index (Labov 1990, 2001). In these cases, most of which are changes that originate outside of the community, women adopt the new non-standard variants of prestige more quickly than men. This is similar to changes from below, which also generally come from outside of the community, but importantly they do not index overt prestige, they usually take place below the level of social awareness, and they often impact several parts of a system (such as in a chain shift of vowels) (Labov 1990, 2001). In changes from below, it is again women
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who adopt the new forms first. Cheshire (2004) succinctly notes that changes led by men are both linguistically and geographically isolated.
Equally complicated is the case for ethnicity. The degree of linguistic variation from the local Anglo variety depends on the ethnic group in question.
For example, Wolfram and Schilling-Estes (2006) note that Jewish varieties of
English differ from majority varieties in terms of only a few variables, while
African American Vernacular English exhibits much more variation. Although it is often reported that ethnic minority groups do not participate in regional dialects
(Labov 1994), such a blanket statement is not true. Instead, some non-Anglo linguistic communities adopt some or all of the characteristics of their regional dialect, and some do not (Fought 2004).
Of course, the effects of gender and ethnicity are not independent of each other, and it is common to find interactional effects between these two factors
(Labov 2010; Wolfram & Schilling-Estes 2006). The majority of research described in the coming sections will consider both of these factors.
1.4.1 Chicano English
The study of Chicano English is a young but productive one. In just a few short decades, Chicano English has become much better understood, and attitudes towards it have greatly progressed. This literature review is organized by decades to highlight the different steps in the growth and trends of research on Chicano English.
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1.4.1.1 Pre-1970s
During this time, there were few studies on this topic, nearly all of which focused on the “inadequate and/or imperfect acquisition” of English by speakers for whom Spanish was their first language. Most notable are an article by Lynn
(1945) and a dissertation by Sawyer (1959) documenting the deficiencies of
Spanish-English bilinguals in Texas. A quote from one of those texts is not needed; the title of Sawyer’s work, “Aloofness from Spanish Influence in Texas
English” will suffice. Today, it is well-known that monolingual English speakers who have an “ethnic accent” are not, in fact, people who are unable to correctly or completely acquire English, but that was not understood in this era.
Fortunately, linguists would soon begin to address this misconception.
1.4.1.2 1970s-1980s
The 1970s brought with them an opposition and strong reaction to earlier studies, with researchers in defense and support of speakers of Chicano English.
Bills (1977) laments, “Vernacular Chicano English is generally perceived as a proper field of inquiry for Second Language Acquisition scholars, but not dialectologists” (p. 431). Important, too, are the clarifications made during this time that non-native speakers of English are not the same as native-speakers who speak a variety of Chicano English. Metcalf states, “… for a Spanish accent does not always mean a Spanish speaker” (1979, p. 1). Note that Metcalf is one of the first linguists who admits that “Chicano” is an ill-fitting name for this field of
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study, yet he uses the term because that is what others in the field do; an issue which will be discussed below.
Here we also see the beginnings of more systematic research on Chicano
English vowels. Various works by Metcalf note some of the differences between
Chicano English and the more standard English varieties throughout the
Southwest, such as stressed lax vowels becoming higher and more tense (yet still remaining distinct from tense vowels) (1972; 1979), lack of BET-raising pre- nasally (1972), and the “substitution” of BOT/BOUGHT in place of BUT (1979).
Until this point, vowel studies had been largely impressionistic in nature, until
Godinez and Maddieson (1985) measured F1 and F2 formant frequencies to systematically compare vowel qualities across three groups in the greater Los
Angeles area: Anglo monolinguals, Chicano monolingual speakers of English, and Chicano Spanish-English bilinguals. In terms of similarity across groups, the
BOT/BOUGHT merger was found to be present in all three populations. In addition to several differences between the two Chicano populations, they found that all Chicano speakers shared several features, in comparison to the Anglos:
1) higher BIT, BET, and BAT, 2) a more backed BOOT, and 3) less difference in duration between long and short vowels. They conclude by stating, “Chicano
English represents an autonomous social dialect with distinct characteristics” (p.
57). This study is still cited frequently today.
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1.4.1.3 1990s
The decade leading up to the turn of the century continued the discussion on the legitimacy and value of this variety of English as well as emphasizing
Chicano English as a dialect of American English (see, for example, Santa Ana
1993a and 1993b). Santa Ana proposed a “cross-regional unitary description of
Chicano English” (1993, p. 5), while other researchers tended to emphasize that their study, whichever one it might be, was regarding one group in one location.
In doing so they stress that their findings may not be true for other Chicano
English-using communities across the country. Both of these approaches have their own importance and value for the establishment and acceptance of the
Chicano English dialect as well as its users.
Hernandez (1993) was the first researcher to examine the Chicano
English of northern New Mexico. Through her own auditory perceptual evaluations of the monolingual English-speakers of her study, she finds lowering of BIT and BET before laterals, lowering of BOOT before consonants, and lowering of BUT. Hernandez began important work with her 1993 study of
English in New Mexico, and this appears to be the only published research on
English vocalic phonetics in New Mexico until 2017 (see below).
As the field of Chicano English continued to grow and more studies were conducted, Mendoza-Denton (1999) outlined a number of issues that must be taken into consideration by the sociolinguistic community when examining two dialects in contact, including, among others: the state of changes in progress with
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each contact variety; the historical, socioeconomic, and demographic conditions of the groups; the degree of contact with other ethnic and linguistic groups; language attitudes and local evaluations; and the possibility of local innovation within minority varieties. Studies that address these questions provide valuable and in-depth quantitative phonetic and phonological research. For example,
Fought (1999) discovered that a combination of variables (gender, socioeconomic status, and gang affiliation) affected degree of BOOT-fronting within a group of Hispanic students at a California high school. Further, she found that these social variables differed in importance for male and female students. For the female students, non-gang affiliation was the strongest variable, and social class was not significant. For male students, on the other hand, social class was the most important variable, and lack of gang-affiliation was much less central. These findings highlight the need to take into consideration a multitude of potentially interacting social variables, as Mendoza-
Denton (1999) emphasized.
1.4.1.4 2000s
By this time, both linguistic and educational communities have come to a consensus that Chicano English 1) is a valid dialect of American English, 2) is spoken by many monolingual individuals as well as many bilinguals, and 3) is not uniform across all Hispanic communities nationwide. Thus, studies of Chicano
English have become much more fine-grained across all disciplines of linguistics.
Here I continue to limit the discussion to the studies that focus on vowels. It is in
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these more recent studies that linguists begin to raise important questions about
Hispanic speakers’ potential participation in local Anglo-led changes.
In looking at the extent to which a given Chicano English community does
(or does not) share characteristics of the local language variety of the majority, it is found that Chicano English communities vary along a continuum in this respect. Several researchers have examined Hispanic participation in the
Northern Cities Shift (NCS) (Frazer 1996; Gordon 2000; Konopka &
Pierrehumbert 2008; Roeder 2010; Konopka 2011). The NCS is characterized by: BAT raising Northern(in all contexts, Cities Vowel rather Shift than just before a nasal), BOT fronting,
BOUGHT lowering, BET backing and lowering, BIT backing and lowering, and
BUT backing. These shifts are diagrammed in Figure 1.3.
BIT
BET BUT
BOUGHT
BAT BOT
Figure 1.3 Summary of Movements in Northern Cities Vowel Shift
Roeder (2009) discovered that Hispanics almost fully accommodate to the local variety of the NCS in Lansing, Michigan with regards to all vowel shifts except BAT-raising. As expected for changes that take place below the level of social awareness (Labov 1990, 2001), the younger women show more advanced
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stages of the NCS than do males or older people of either gender. Roeder’s
(2010) in-depth discussion views the lack of movement in the BAT vowel as a salient identity marker for the Hispanic community there, which highlights the significance of participation (or not) in BAT-raising. Konopka and Pierrehumbert
(2008) found variable participation in NCS among Chicano English speakers in
Chicago, Illinois, a location where NCS is also present. One vowel stood out as most differentiated across ethnicities: very little BAT-raising was observed among the Hispanic participants. As an aside, BEET and BOOT (vowels that are not part of NCS) were raised for Hispanic speakers while BIT and BOOK (as part of NCS) were lowered. While the speakers in Konopka and Pierrehumbert’s (2008) study do show the NCS pattern in vowels other than BAT, albeit at less advanced stages, the authors suggest that for this specific Chicano English community, lack of BAT-raising is a marker of ethnic identity, which is similar to the suggestion by Roeder (2010). In addition, they emphasize that there is no singular Chicano English dialect, and that individual communities will adopt different aspects of local non-ethnic sound changes, again similar to the findings from Roeder (2010). More recently, Konopka (2011) observed nearly identical vowel spaces for Anglos and Hispanics, and notes that it is the dynamic features of trajectory and length that differ between the two groups. In sum, there is variable participation in NCS features across communities of Hispanic speakers in the Great Lakes region.
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Fought (2003) also found partial participation by the Hispanic population in her study of the California Vowel Shift (CVS). As in her 1999 study, her 2003 participants show evidence of BOOT-fronting, BAT-backing and raising, but the distribution for each of these vowels differs for different combinations of the social variables of gender, social class, and gang status. The CVS will be discussed in more detail in the following section. In addition to CVS features,
Fought (2003) found that her Chicano English speakers showed a wider distribution of the BEET vowel, shortening of BAIT and BOAT, and variable production of glides.
A number of studies have also investigated Hispanic speakers in Texas, a welcome return to the topic in Texas since the early, and arguably misguided, works by Sawyer (1959) and Lynn (1945) more than 50 years ago. Variable
Hispanic participation in Anglo norms was again reported. Thomas (2001) found that Hispanics did not front BOAT like Anglos in the community did, nor did they produce any of the vowel features that are exclusive to Texas Anglo English.
Hispanics did show increasing BOOT-fronting and the merging of BOT/BOUGHT, features typical of the Anglo speakers. Thomas, Carter, and Cogshall (2006) additionally found a lack of BAN-raising in Hispanic participants, another difference from the behavior of Anglo speakers in Texas. Williams (2010), however, finds BAN-raising and tensing by both the Anglo and Hispanic speakers in his study of El Paso, which will be addressed in more depth in section 1.4.4.
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Of further interest and great importance is the fact that many of the more recent studies discussed above address the issue that the term “Chicano
English” is not necessarily an appropriate one. In fact, even some of the studies from nearly fifty years ago speak to this issue. Chicano is a term that, depending on the location and time frame in question, is used by virtually none of the people that it is purported to describe. Researchers have now started to use other terms more often. For example, Thomas (2001), Thomas, Carter, and Cogshall (2006), and Roeder (2009, 2010) describe “Mexican-American English,” Slomanson and
Newman (2004) use the term “Latino English,” Konopka and Pierrehumbert
(2008) and Konopka (2011) use “Mexican Heritage English.” Though no one term can perfectly capture this language variety or its users, it is heartening to see that researchers recognize this and are attempting to include this issue as part of their work. “When Labels Don’t Fit” (Taylor, Lopez, Martinez, & Velasco 2012) offers a concise yet powerful description of some of the complex factors surrounding appropriate label use to describe Hispanics and, by extension, their language varieties in the United States.
1.4.2 California Vowel Shift and being a “Western State”
Although English in New Mexico has received relatively little linguistic study, all evaluations categorize New Mexico (minus a small area described below) as a western state.
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1.4.2.1 The West
In Carver (1987), all but a sliver of the southeastern part of the state of
New Mexico is described as being part of “The West”. This evaluation came from the lexical choices and isoglosses identified in the speech of four speakers from different locations across the state who took part in the survey for the Dictionary of American Regional English (DARE). Similarly, Labov (1991) found New
Mexico to be part of the Third Dialect region, a region broadly characterized by not participating in either of the two largest shifts occurring throughout the US: the Northern Cities Shift and the Southern Shift. More specifically, the Third
Dialect is characterized by the BOT/BOUGHT merger, BAN-raising, and BAT- retraction. Labov, Ash, and Boberg (2006) describe the Western Dialect Region, of which New Mexico is a part, to include not only the features listed above, but also BOOT-fronting and slight BOAT-fronting, all of which are supported by the
New Mexican data used in the Atlas of North American English (ANAE).
While these newly added features from the ANAE description were found within the data for New Mexico, it is important to keep in mind that the ANAE includes only very sparse data on the state. In fact, of the six speakers included from New Mexico, the full vowel space was only analyzed for two of them: a
Hispanic female from Albuquerque and an Anglo female from Santa Fe. Both of these speakers showed complete shifts for BET-lowering, BAT-retraction, and
BOT-retraction, three of the vowel shifts that make up the CVS. The Hispanic female from Albuquerque showed no fronting of BOOT or BOAT. This absence of
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fronting is characteristic of Chicano English (Thomas 2001). The Anglo female from Santa Fe, on the other hand, showed BOOT-fronting and slight BOAT- fronting, both of which were newly described characteristics of the Western
Dialect Region in the ANAE (Labov, Ash, & Boberg, 2006) as well as being part of the CVS (Eckert 2008).
As a side note, of the two most significant linguistic studies that include
New Mexico, one utilized just four speakers (Carver 1987), and the other analyzed the full vowel systems for two speakers plus partial data from four other speakers (Labov, Ash, & Boberg 2006). When considering that New Mexico is the fifth largest state by area in the United States, it seems important to include more than a handful of speakers. If we consider the six speakers from New
Mexico that were included in the ANAE (Labov, Ash, & Boberg 2006), New
Mexico has been characterized by just 1 speaker per 20,235 square miles of land.
1.4.2.2 California Vowel Shift
Very popular in dialectology work in recent decades, the California Vowel
Shift (CVS) has been heavily studied throughout its namesake state (Hagiwara
1997; Fought 1999; Eckert 2008; Hall-Lew 2009; Kennedy & Grama 2012, among others). This vowel shift includes the lowering and backing of the front lax vowels (BIT, BET, and BAT), the raising of BAT before a nasal (hereafter referred to as BAN-raising), the merging of BOT and BOUGHT into the space represented by /ɔ/ in the IPA, the fronting of BUT, and the fronting of the high and
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mid back vowels BOOT, BOOK, and BOAT (Eckert 2008). These shifts are diagrammed in Figure 1.4.
BEET BOOT
BIT BOOK
BAN BOAT
BET BUT
BAT BOT/BOUGHT
Figure 1.4: Summary of movements in California Vowel shift
As with nearly all other linguistic phenomena, CVS is not as simple as it
may initially appear. First, it is debated whether these vowel movements are – as the name suggests – one vowel shift system, or whether they are the product of two smaller shifts working in tandem (Kennedy & Grama 2012). Second, all
California speakers do not show identical patterns for this vowel shift. Rather, there are regional, ethnic, and gender-based differences in CVS participation.
Kennedy and Grama (2010) note that the “English of California is by no means uniform” (p. 40). In terms of geographic differences, for example,
D’onofrio et al. (2016) found variable participation across the field sites in their study of the inland communities of Redding, Bakersfield, and Merced. With regard to variation relating to ethnic minority participation, Hall-Lew (2011) noted that Asian-Americans were not only participating in the CVS, but were sometimes even more advanced in their vowel shifts (especially BOOT-fronting) than
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Anglos. Cardoso et al. (2016) found Chinese-Americans participating in BAT- retraction and BAN-raising, but to a lesser extent than the Anglo population. As for gender, it is commonly found that women lead linguistic change (Labov 2001), and this has also been documented for the CVS: in Cardoso et al. (2016), above, the Chinese-American women led in BAT-retraction over Chinese-American men.
The CVS is, by name alone, a bit misleading, as we see participation in this vowel system in other states throughout the West. Just as within California, there is variable participation among different social groups across different western states. For example, Holland and Brandenburg (in press) found evidence of the CVS in Colorado, especially among women, even though men and women participate rather equally in the vowel shifts characterized by Labov
(1991). In fact, Holland and Brandenburg (in press) documented occurrences of all CVS movements in Colorado except for BUT-fronting. Instead, they found
BUT-retraction.
Of course, the CVS and the Western States Dialect are not the only varieties that occur in the West. There are other regional varieties as well, and participation in any language variety is dependent on a plethora of social variables. For example, Wassink (2016) found that all of the ethnicities (Yakama,
Japanese, Mexican, African American, and Anglo) in her study of Central and
Eastern Washington participated somewhat in at least some of the local features of Pacific North West English, such as pre-velar raising of BAG to BEG. As in
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other studies of shifts from below (Labov 1990, 2001), females were found to lead the change. In addition, Hispanics exhibited the BOT-BOUGHT merger but showed no evidence of widespread BOOT-fronting.
There has been only one study so far that examines the question of New
Mexico’s participation in the CVS (Brumbaugh & Koops, in press), which will be discussed in the coming section.
1.4.3 English in New Mexico
As can be seen from section 1.5.1, the majority of research (particularly the most well-known publications) on Chicano English has been located in just three areas: California, Texas, and a few locales within the Northern Cities Shift region (in and near Chicago, Illinois and Lansing, Michigan). Research on
Chicano English in New Mexico has been sparse in contrast, and the few studies that do exist lack in terms of number of participants. As mentioned earlier, I argue that this is mostly due to the incredible linguistic diversity throughout this state
(languages include New Mexican Spanish, Navajo, Jicarilla Apache, Mescalero
Apache, Zuni, Keres, Tiwa, Tewa, and Towa), in addition to the relative recency of the widespread use of English as compared to other states. The next paragraphs will highlight the fact that the majority of research on English in New
Mexico is situated in terms of its relation to Spanish. Recall that while 48% of the state population is Hispanic (American Community Survey 5-year Estimates
2015), just 26.8% of the state population speaks Spanish (American Community
Survey 1-Year Estimates 2015). Many Hispanics in New Mexico are English
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monolinguals, and this research focus exclusively about bilinguals may unintentionally or indirectly support the common misconception that Chicano
English speakers are always bilingual.
The earliest research on Chicano English in New Mexico followed similar themes to other contemporary investigations across the Southwest. That is, the focus was on the educational ramifications for Spanish-English bilingual children
(Rodrigues 1974), as well as factors and attitudes that influence choosing to use
Spanish or English for a particular interaction within a bilingual community or household (Timm 1975). In more recent decades, the focus on bilingual speakers throughout New Mexico has continued, with much work taking advantage of the
New Mexico Spanish English Bilingual Corpus (NMSEB, Torres Cacoullos &
Travis 2015a). Other studies have focused on lexical borrowing of English into
Spanish (Bills & Vigil 2008; Clegg 2009). In these grammatical and lexical studies, the focus almost exclusively concerns the uniqueness of New Mexican
Spanish, thereby strongly suggesting that the language contact effects involving
Spanish and English are unidirectional.
From a phonetic or phonological viewpoint, considerably less work has looked at English in New Mexico. As mentioned previously, Hernandez (1993) studied Chicano English vowels in Northern New Mexico using impressionistic analysis. She found that the high tense vowels BEET and BOOT lower, BET lowers to BAT before a lateral, and the lowering of BUT. The only study on
English consonants in New Mexico, to the best of my knowledge, is Balukas and
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Koops (2015), who examined Voice Onset Time (VOT) in the code-switching of
Spanish-English bilinguals. They found a clear substratum effect of Spanish on the English for the VOT of these Spanish-English bilinguals, which is in line with the types of effects that would be expected for vowels.
The most thorough study of Chicano English vowels in New Mexico, aside from Hernandez (1993), is Brumbaugh and Koops (in press). By comparing the vowel spaces of Anglo men, Anglo women, Hispanic men, and Hispanic women, a number of observations were made. First, they found Anglo participation in
Western/CVS traits, with women leading the change in the majority of cases.
Specifically, BET-lowering, BAT-retraction, BOOT-fronting, and peripheralization of BAIT are all led by women, while the other two sound changes, BOAT-fronting and BAN-raising, are led by Anglos but do not show a gender difference. On the other hand, Hispanics show little to no participation in Western features, with the exception of the BOT/BOUGHT merger. Lastly, the Hispanic groups show much less difference between genders than the Anglo group, wherein several significant differences between Anglo men and women were documented.
This dissertation is an effort to build on and expand the work of
Brumbaugh and Koops (in press). It is clear from the limitations of the existing literature that there is much potential for linguistic research on English in New
Mexico.
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1.4.4 Issues of Majority-Minority situations
All of the studies addressed so far, with one exception (Williams 2011), concern ethnic minority groups within larger communities of which they are numerically a minority group based on their population size. Yet groups that are minorities in the national context are not always minorities at the local level. For example, the city of El Paso, Texas reports a population that is 80.7% Hispanic and 14.2% White Non-Hispanic/Non-Latino (as reported in Williams 2011).
Similarly, the city of Miami is 70% Hispanic/Latino, while the state of Florida overall is 22.5% Hispanic/Latino (US Census 2010). What happens in communities such as these? In the case of Williams (2011), full participation in
BAN-raising was found across ethnic and gender groups. The issue of BAN- raising is particularly interesting because it is rarely documented in Hispanic communities. As mentioned earlier, Roeder (2010), found full participation on the part of her Hispanic participants across all vowel shifts typical of the Northern
Cities Shift except for BAN-raising. Only women under 25 showed complete raising of BAN, and Roeder believes it to be a change in progress. It may be that
BAN-raising throughout the Hispanic population in El Paso, a vowel quality for which the opposite (lack of BAN-raising) is normally characteristic in communities that speak Chicano English (Thomas 2001), relates to their majority position in their community. In El Paso, Hispanics are clearly the majority. This raises the question of whether New Mexico, where Hispanics and Anglos are much closer in number, exhibits a similar pattern.
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1.4.5 Summary
In the literature reviewed above, the majority of work on Chicano English and the CVS has occurred in their canonical geographical areas, and only recently has research expanded to include other locations and regions. For example, Chicano English has been studied most often in California and Texas, yet there are large Hispanic populations across much of the United States. We therefore have begun to see more work in other locales, such as North Carolina
(Wolfram, Carter & Moriello 2004; Kohn 2008), Chicago, Illinois (Konopka &
Pierrehumbert 2008; Konopka 2011), and Lansing, Michigan (Roeder 2009,
2010). Similarly, the CVS has been studied primarily in California. As more sociophonetic studies are done throughout the West, we see that it is not
Californians alone who are participating in this shift, but residents of other areas such as Colorado (Holland & Brandenburg in press) and Oregon (McLarty,
Kendall, & Farrington 2016).
Section 1.4.3 presented a review of research into English in New Mexico, and was notably short. New Mexico is sorely lacking with regards to linguistic investigations into the local varieties of English. As a western state, a better understanding of New Mexico’s participation (or potential lack thereof) in terms of
Western Vowels (Labov, Ash, & Boberg 2006), and the CVS (Eckert 2008) is desirable. Further, it is imperative that any work include considerations of ethnicity, specifically, the roles of the two largest ethnic groups in the state,
Anglos and Hispanics. This is particularly true, as addressed in section 1.4.4,
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when a group that is a minority in the nation is actually the majority population in a community.
Throughout this section, I highlighted questions relating to Chicano
English which my research aims to illuminate. Eckert (2016) describes much of this succinctly: “The dialectology of the United States has been a white Anglo dialectology, and interest in other groups has centered on the extent to which they conform to the narrowly defined regional patterns” (p. 3). The work at present aims to address these issues within the context of New Mexican English.
1.5 Research Questions and Hypotheses
Here, I aim to investigate the location of individual vowels, diphthong trajectory, and the overall vowel space of speakers in New Mexico. I specifically address the similarities and differences across gender and ethnic groups within the Albuquerque area, as well as comparing Albuquerque to other communities in the US. It is important to keep in mind that this is one of the first studies of this nature in the state, and thus I am obliged to ask simple research questions in some instances. Future works will, ideally, build upon the foundations established in the current study.
1.5.1 Question 1: Vowels across Gender and Ethnicity
I first address the locations of individual vowels and their trajectories, as well as a speaker’s total vowel space, and compare across the genders (male, female) and ethnicities (Anglo, Hispanic). The term “Anglo” here refers to non-
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Hispanics that identify as White or Anglo. I have four hypotheses related to gender and ethnicity.
Hypothesis 1. Anglos, but not Hispanics, will have different distributions for
BAT and BAN. Anglos will raise the BAN vowel to a higher position in the vowel space relative to their BAT vowel. In contrast, Hispanics will not raise BAN, and it will be located in the same (or very similar) space as their BAT vowel. This has been documented in numerous studies across various Chicano English communities (Thomas, Carter & Cogshall 2006; Konopka and Pierrehumbert
2008; Roeder 2009 and Roeder 2010).
Hypothesis 2. Broadly speaking, Hispanic females will pattern more closely to the Anglos than to the Hispanic males. Evidence of the California
Vowel Shift is expected in the Anglo speakers as well as slight participation from
Hispanic females (see Research Question 2, below). As CVS is a set of linguistic changes from below, women usually begin to adopt such new features before men (Labov 1990, 2001). This would support, then, that Hispanic women will produce features of the CVS to a greater extent than Hispanic men. Roeder
(2010) finds that Mexican-American women show more advanced and more complete participation in the local regional variety, the Northern Cities Shift, than do their male counterparts. Therefore, Hispanic females will pattern more closely to Anglo speakers in this study.
Hypothesis 3. There will be less change between the starting and ending points in the short diphthongs of Hispanics as compared to Anglos, similar to
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findings in Fought (2003). That is, there will be more monophthongization in the short diphthongs BADE and BOAT within the Hispanic group as compared to the
Anglo group.
Hypothesis 4. Hispanics will have a larger overall vowel space. Fought
(2003) noted that her Hispanic participants produced BEET and BOOT glides higher in the vowel space than Anglos. Additionally, Santa Ana and Bayley
(2004) and Fought (2003) report variable amounts of BOOT-fronting from none to moderate fronting. Therefore, higher BEET and BOOT vowels, coupled with less
BOOT-fronting, mean that the back of the vowel space for Hispanics may be further back and higher than that of Anglos, which would lead to a larger overall vowel space.
1.5.2 Question 2: New Mexico and the California Vowel Shift
My second research question addresses to what extent New Mexicans participate in the characteristics of Western Vowel Shift and/or the CVS. The first three hypotheses stem from descriptions of the Western Vowel Space (Labov,
Ash, & Boberg 2006).
Hypothesis 1. All participants, regardless of gender or ethnicity, will have a merged BOT-BOUGHT vowel space. This is commonly found across the West, regardless of ethnicity. Wassink (in press) reports Hispanic participation in the
BOT-BOUGHT merger in the state of Washington.
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Hypothesis 2. BAN-raising will only occur in Anglo participants, similar to results found by Thomas, Carter & Cogshall (2006) and Konopka and
Pierrehumbert (2008).
Hypothesis 3. Anglos will participate in BOOT and BOAT fronting,
Hispanic females will front these vowels slightly, and Hispanic males will show no evidence of fronting. Labov, Ash, and Boberg (2006) found exclusively Anglo participation in these shifts in New Mexico. Wassink (2016) reports no BOOT- fronting on the part of Hispanic participants.
Hypothesis 4. The lowering and retraction of the front lax vowels (BIT,
BET, and BAT), the possible fronting of BUT, and the fronting of BOOK will only occur in Anglo speakers, slightly in Hispanic females, and not at all in Hispanic males. Further, even the Anglo speakers that show the most advancement of features of the CVS will not be as advanced as is found in California. This is due to the relative recency of the CVS (as opposed to the characteristics of Western
States vowel descriptions), the location of New Mexico (separated from California by the approximately 400-mile-wide state of Arizona), and the small proportion of
Californians living in New Mexico. Of all of the states in the West, New Mexico and Wyoming report the lowest proportions of Californians, with just five percent of each state’s population originating from California (Gregor, Gebeloff, & Quealy
2014). This is in contrast to the states directly adjacent to California that have nearly double and triple the proportions of Californians: Nevada, Oregon, and
Arizona report 19%, 14%, and 9%, respectively. (Gregor, Gebeloff, & Quealy
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2014). Just as it took a great deal longer for language demographics to shift in
New Mexico than elsewhere approximately 100 years ago, I expect that it will take longer for New Mexico to undergo newer linguistic shifts as well. As for ethnicity-based differences in CVS participation, Hispanics have been documented as showing less advanced participation in local Anglo-led sound changes of this type (Eckert 2008; Roeder 2009 and 2010).
In sum, I expect that Anglos will show evidence of the Western Vowel Shift and the CVS, but their participation will be less than what is found in other states in the West, with the exception of BAN-raising and the merging of BOT and
BOUGHT, which will be similar to what has been documented elsewhere. That is, each vowel that has been identified as part of the CVS or Western Vowel Space/
Third dialect will be present in New Mexico, but the movement/location will be less dramatic than is found elsewhere. Further, I hypothesize that Hispanic women will participate only partially at most. Aside from a fully merged BOT-
BOUGHT space, I expect very little to no participation on the part of Hispanic men.
1.5.3 Question 3: Comparing Chicano English in New Mexico with Findings in Other States
Thirdly, I address how the findings for the Hispanic speakers in this study of New Mexico compare to those of other Hispanic communities across the US. I hypothesize that my findings will be similar to what has been observed in other
Chicano English-speaking communities throughout the country.
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Hypothesis 1. Hispanics will not have a pre-nasal BAT/BAN split, consistent with Thomas, Carter and Cogshall (2006), Konopka and
Pierrehumbert (2008), and Roeder (2009).
Hypothesis 2. The short diphthongs BADE and BOAT produced by
Hispanic speakers will be more monophthongal in quality, meaning a smaller trajectory/distance from onset to glide, than those produced by Anglo speakers.
This hypothesis is based on similar findings in Fought (2003).
Hypothesis 3. I expect to find less advanced participation in local Anglo- led sound changes from the Hispanic participants. Similar to findings in other locations (Labov 2001; Roeder 2010), if there is evidence of participation in local non-ethnic sound changes, then: 1) Hispanic participation will be less advanced, and 2) Hispanic women will participate more than Hispanic men.
1.6 Organization of the Dissertation
Chapter 1 has set the framework for this study with an overview of the historical and linguistic situation of New Mexico, motivations for the current research, review of the relevant literature, and research questions and their corresponding hypotheses. Chapter 2 explains the methodology used in this dissertation including experimental design, participant selection, experimental procedure, token selection, data analysis and statistical procedures. Chapter 3 presents the results of the experiment and discusses the answers to Research
Question 1 (Vowels across Gender and Ethnicity). Chapter 4 considers New
Mexico’s participation as a Western State and/or participant in the California
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Vowel Shift (Research Question 2) and compares the findings of the study at present with those of previous studies on Chicano English (Research Question
3). Finally, Chapter 5 includes a summary of results, a discussion of limitations, suggestions for future work, and closing comments.
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Chapter 2: Methodology
2.0 Overview
This chapter describes the experimental design, implementation, and subsequent data analysis for this work. Section 2.1 covers speaker recruitment and selection. Section 2.2 includes materials and elicitation techniques. Section
2.3 addresses the recording procedures. Section 2.4 covers token extraction and evaluation. Section 2.5 explains the normalization and scaling techniques, and section 2.6 describes the statistical procedures used to make comparisons across social factors, individual vowels, and the global vowel system.
2.1 Speakers
2.1.1 Recruitment
Speakers were recruited from Linguistics 101 classes on the main campus of the University of New Mexico in Albuquerque, New Mexico as well as by word of mouth. Participants chose the type of compensation they preferred for their involvement: either extra credit in their introductory Linguistics class or a Visa gift card valued at $20.
Recruitment efforts involved explaining to potential speakers that this study focused on individuals that 1) had lived all of their lives in the northern half of New Mexico, 2) self-identify as White/Caucasian/Anglo or
Hispanic/Latino/Latina, and 3) only speak English or both English and Spanish.
Northern New Mexico was defined as the region north of Los Lunas, NM, inclusive. See Table 2.1 and Figure 2.1 in section 2.1.2.
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2.1.2 Background questionnaire and speaker selection
Upon arriving at the Speech and Hearing Sciences laboratory, each participant first filled out a background questionnaire that asked questions regarding their linguistic background (as well as those of their parents and grandparents), where they had lived, and whether they had ever lived outside of
New Mexico for more than six months. This questionnaire was used as verification that the participant met the study background requirements. All speakers completed the questionnaire as well as the recording activities, regardless of their responses on the initial questionnaire. See Appendix A for the complete questionnaire, including listed options for race and ethnicity.
For the purposes of this study, speakers were categorized based on their own self-identification of ethnicity. As mentioned in previous chapters, there is no one agreed-upon term for people commonly referred to as “Hispanic.” Thus, a number of options were available for participants to select, all of which were considered as part of the “Hispanic” category. This included the terms: Hispanic,
Chicano/a, Hispano/a, Latino/a, Mexicano/a, Mexican-American, Afro-Latino,
Spanish, Spanish-American, and Coyotito/a. The last three terms, Spanish,
Spanish-American, and coyotito/a have specific meanings unique to New Mexico
(Gonzales 2005). Spanish and Spanish-American are often used in the northern part of the state as a way to identify someone whose family has resided for centuries in that area, as opposed to having more recently immigrated from
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Mexico. Coyotito refers to someone who is of mixed heritage, generally half
Hispanic and half Anglo.
Twenty-seven people participated in the experiment. Eleven of these were excluded for a variety of reasons. Two participants were excluded from analysis for having lived outside of New Mexico for more than six months, three participants self-identified as both Anglo and Hispanic, and one participant mentioned that his parents had put him in accent reduction classes when he was younger. Five Anglo women were not included in the analysis due to the abundance of Anglo women having participated in this experiment.
Consequently, sixteen speakers were included in the full analysis. This includes eight people who self-identify as Anglo (4 men, 4 women) and eight people who self-identify as Hispanic (4 men, 4 women). None of the 16 chosen participants identified as both Anglo AND Hispanic. Rather, each participant identified as either Anglo or Hispanic. Speaker demographics for those included in the study are listed in Table 2.1.
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Speaker Hometown Anglo female 1 Albuquerque Anglo female 2 Rio Rancho Anglo female 3 Los Alamos Anglo female 4 Los Alamos Anglo male 1 Albuquerque Anglo male 2 Edgewood Anglo male 3 Albuquerque Anglo male 4 Albuquerque Hispanic female 1 Albuquerque Hispanic female 2 Pecos Hispanic female 3 Los Lunas Hispanic female 4 Chama Hispanic male 1 Los Lunas Hispanic male 2 Los Lunas Hispanic male 3 Silver City Hispanic male 4 Los Lunas Table 2.1 Participants and their hometowns
Figure 2.1 shows the location of participant hometowns across the state.
The size of the diamond-shaped marker is proportional to the number of participants from that city. The capital, Santa Fe, is marked with a star; no participants are from there.
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Figure 2.1: Hometowns of participants by number of participants in study
All participants except for the one from Silver City originate from the northern half of the state. The speaker from Silver City was included in order to maintain an equal number of participants in each category.
2.2 Materials
2.2.1 Tokens
A total of 14 lexical classes were chosen for analysis in order to develop a complete picture of each speaker’s vowel space. This includes the monophthongs BEET, BIT, BET, BAT, BAN, BOT/BOUGHT, BURT, BUT, and
BOOT. Note that BAT and BAN were separated due to the expectation that these two phonetic environments will pattern differently between the two ethnic groups.
By preemptively separating BAT and BAN tokens, these expected differences can be taken into account in the process of normalizing the data. Previous
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studies having examined the potential merging of BOT/BOUGHT in New Mexico identify New Mexico as within the region of the COT-CAUGHT merger (Labov,
Ash, & Boberg, 2006; Brumbaugh & Koops, in press). This study builds off of those findings. Therefore, the BOT and BOUGHT vowels are collapsed together into one category, here referred to as BOT. This coincides with impressionistic evidence from New Mexico students’ difficulty in learning how to distinguish the vowels of BOT and BOUGHT as they occur in dialects of English where they have not merged. Diphthongs include BITE, BAIT, BOY, BOUT and BOAT.
BOOK was unintentionally omitted from this study. Target words were then chosen for each of the 14 vowels listed above.
All target words follow one of three syllable structures: bVt, bVd, or bVn.
For each vowel, there is a minimal triplet whenever possible across bVt, bVd, and bVn. For example, beat, bead, and bean are the three lexical items for the
BEET vowel. Within each following phonetic environment category, all words are minimal pairs as well to the extent possible within the English lexicon. For example, in the bVt word list, the words are beat, bit, Bert, bet, bat, ban, bought, boat, bite, bait, boytalk, boot, and butt. Additionally, all words are content words
(i.e. butt instead of but). All words are one-syllable words when possible within the confines of a standard American English lexicon. As mentioned previously, speakers in this dialect area have merged the vowels [ɔ] and [ɑ], so that
BOUGHT and BOTTLE have the same vowel, unlike some areas of the eastern
US.
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beat bead bean bit bid bin Burt bird burned bet bed Ben bat bad ban butt bud bun bought bottle bonfire boot boo'ed* Boone bite bide binders (no word) bowed bounced bait bade bane boytalk* Boyde boint* boat bode bone *denotes words and fake words that were eliminated from the study (see section 2.4.2 Excluded Tokens) Table 2.2: Words used in elicitation activities
2.2.2 Participant Speaker activities – short story, carrier phrase, picture
All recordings for any given speaker took place in one appointment. Each person completed the three activities outlined below twice.
First, speakers were asked to read several short children's stories out loud. They were instructed to read these stories in a slower pace, in the manner that children's stories are typically read aloud. Additionally, some words were bolded in the text, and the speakers were told to emphasize those words, as if they were the most important words in each sentence. All of the target words from Table 2.2 above were bolded throughout the passages. A variety of non- target words were also bolded, so that the speakers would not become aware of the similarities among the words of interest to the study. Bolding and emphasizing the target words was intended to cause the participants to produce
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longer, clearer vowels that would then be easier to analyze. Participants read a total of five passages. The first passage was simply a practice activity to ensure that the speakers were following the guidelines and becoming accustomed to the task. The target words were divided across the four remaining reading passages.
See Appendix B for the complete short stories.
The second activity was reading aloud the target words of the bVd group in the carrier phrase X. I’m saying X again. See Appendix C for full list of carrier phrases.
The last activity was for a speaker to look at a drawing and tell the researcher all of the things that they could see. This drawing was created to elicit approximately one-third of the list of target words; the data from this activity could then be evaluated as a more natural form of speech and be compared against the data produced from the reading activities. This activity was ultimately not used in the analysis at present due to variable participant behavior and production. See appendix D for the drawing activity.
After completing each of the three activities once, the participant was offered a short break. Then they repeated each activity an additional time. The order of activities remained constant for each speaker.
It should be mentioned here that there are both advantages as well as some possible disadvantages with regard to using a reading passage or reading- based activities to elicit data. First, a reading passage guarantees that all speakers are performing the same task and, therefore, giving very similar data in
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terms of the words that they read and their surrounding contexts. Activities such as reading passages do, though, create the possibility that participants will see this as a more formal activity and therefore speak in a more formal register (here formal meaning more standard, which may erase some non-standard vocalic features). Reading words in a carrier phrase is even more likely to elicit citation forms that reflect the participants’ notion of “correct” speech. However, this activity was included in the study in order to provide data comparable to other studies that elicited citation style productions. In addition, some participants may be more or less comfortable with reading activities, which could also affect their vowel production.
2.3 Recording Procedures
All recordings took place in a soundproof room in the Speech and Hearing
Sciences building on the main campus of the University of New Mexico. Audio files were recorded into .wav format onto a compact flash drive using a Marantz solid state recorder and Shure head-mounted microphone. These recordings were digitized at a 44.1Khz sampling rate and 16-bit resolution. Files were then transferred to a personal computer as well as an online storage cloud, with all files password-protected for confidentiality.
2.4 Tokens
Target words were marked onto a Praat Textgrid (Boersma & Weenink
2017). The total number of tokens varied across participants for several reasons.
First, some of the earliest speakers participated in the experiment before the
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creation and implementation of the second and third activities (the word list and picture description). Additionally, these earliest speakers read from a previous version of the short stories that included 9 vowels, rather than the full 14. It should be noted, however, that this reduced vowel set for the first four speakers in this study still contained BEET, BOOT, BAT, and BOT/BOUGHT. These four vowels are the extremes of F1 and F2 measurements, and are the most important when normalizing data (see section 2.5 below for more information on normalization). Secondly, several audio files were unusable due to technical issues. This affected the data for just three speakers: one Anglo woman and two
Anglo men.
2.4.1 Correction/Cleanup
The .wav file and its corresponding text grid were processed through
FAVE-align (Rosenfelder, Fruehwald, Evanini, & Yuan 2011), an online interface to the Penn Forced Aligner (Yuan and Liberman 2008), which automates phonetic alignment for American English. FAVE-align adds boundaries to a Praat
TextGrid that delimit each consonant and vowel within a word or phrase that has previously been identified. The resulting output from the program was hand- checked and adjusted when necessary in order to insure accurate delineation of the onset and endpoint of each target vowel. This procedure is illustrated in
Figure 2.2. Next, the .wav file and the corrected text grid were fed through FAVE- extract (Rosenfelder, Fruehwald, Evanini, & Yuan 2011), an online interface that
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uses Praat to extract a variety of measurements for each vowel. Default configurations were used.
Figure 2.2: BAT vowel alignment in Praat
Figure 2.2 shows a token of the word BAT visually represented within
Praat. The word was marked by hand in Praat and individual sounds were labeled using FAVE-align. The alignment was then checked by hand and adjusted when necessary. The sound file and text grid were then processed by
FAVE-extract, which automatically extracted values for F1 and F2. This process resulted in 1,745 total transcribed tokens.
2.4.2 Excluded Tokens
Tokens were excluded for a number of reasons. As previously mentioned, the recordings from the third activity, the picture description, were not used because of variable speaker production. The data from those recordings is not reflected in any of the raw data or analysis in this dissertation. All other causes for exclusion occurred after the FAVE-align and FAVE-extract process.
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The F1 and F2 formant measurements for each of the 1,745 vowels were extracted at 20%, 50%, and 80% of the duration of the vowel and plotted in order to identify any outliers or other issues.
First, participants often hesitated or stumbled over the word BOO’ED and the made-up words BOYTALK and BOINT. All tokens of these words were excluded from analysis for all speakers. This totaled to 132 omitted tokens.
Measurements for other target words were, for the most part, distributed into compact clusters. Questionable tokens were reexamined in Praat and either corrected or omitted. These potential outliers were hand-measured and corrected appropriately if the automated procedure had erred. Tokens were excluded when obtaining clear formant measurements across the three time points was impossible or when the formant measurements were far outside the canonical vowel space of that specific vowel (that is, when an outlier was simply an outlier, and no correction was necessary or appropriate). A total of 19 tokens were excluded for these reasons.
Finally, all words that included a diphthong followed by a nasal were excluded. Plotting the formant measurements revealed that the following nasal consonant changed the trajectory of the diphthong too much for those tokens to be grouped with other tokens whose vowel did not precede a nasal consonant.
This resulted in the exclusion of 106 total tokens of BANE, BINDER, BONE, and
BOUNCED. The tokens of the fake word BOINT had already been removed. For monophthongs, words including a coda nasal were retained.
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2.4.3 Total numbers
A total of 1,488 tokens were analyzed out of 1,745 tokens that were processed with Fave-align and Fave-extract, meaning that 257 tokens were excluded from statistical analysis. See Table 2.3 for a breakdown of final token numbers by speaker group.
Speaker group Final token count Hispanic female 421 Hispanic male 426 Anglo female 331 Anglo male 310 Total: 1488 Table 2.3: Breakdown of final token counts by speaker group
The grey column in Table 2.3 shows the final number of tokens that were used from each participant category, which sums to 1,488 tokens. Anglo speakers had fewer tokens, as there were more speakers from the Anglo groups in the earliest stages of this experiment, which included fewer vowels. F1 and F2 measurements of the 1,488 tokens are included in Appendix E.
2.5 Normalization and Scaling
Normalization has become standard procedure in sociophonetic studies
(Fabricius, Kendall, & Watt 2011). Among other reasons, normalization of the data was necessary in this study due to having multiple male and female participants. Without such a procedure, it is impossible to make appropriate vowel formant comparisons across speakers for a variety of factors, such as the variability that comes from size differences among vocal tracts. There are a
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number of common methods by which normalization can be achieved. This section details the choices and procedures followed throughout this study.
2.5.1 Lobanov method
After extraction and cleanup, the resulting F1 and F2 measurements at
20%, 50% and 80% of a vowel’s duration were normalized using Lobanov (1971) methods through the online normalization suite, Norm (Kendall & Thomas 2010).
The Lobanov (1971) method calculates z-scores for the F1 and F2 of each speaker. This standardization uses Eqn. (1) where n is an F1 or F2 formant of vowel V, N is the normalized value or z-score, � is the average value of all formants of all vowels in the same dimension (F1 or F2), and � is the standard deviation for formant n.
� − � � = (1) �
Lobanov (1971) is a vowel-extrinsic manner of normalization, meaning that
“vowel spaces across speakers are set to a normalized range and each individual vowel is placed within the range in reference to a central measure” (p.
2238). In this way, comparisons can be better made across the pool of speakers, as the use of standard scores removes differences due to gender and individual variation.
While there are numerous newer techniques for vowel normalization,
Lobanov (1971) is still regarded as one of the best (Adank, Smits, & Van Hout
2004, Flynn 2011, Clopper 2009). Although all normalization procedures have advantages and disadvantages, the Lobanov method has been ranked highly in
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comparisons of vowel normalization techniques for reducing physiological variation while simultaneously preserving phonemic and sociolinguistic variation
(Adank et al. 2004). The scaling of z-scores back to Hertz was originally considered, but it altered the data in misleading ways. See Appendix E for normalized individual speaker F1 and F2 measurements, in z-scores, for each vowel included in this study.
2.6 Statistical Procedures
Once normalization procedures were completed, a separate statistical comparison was performed for each F1 and F2 dimension of every vowel in this study. For monophthongs, analysis occurred with data extracted at the midpoint, or 50% time point, of the vowel. For diphthongs, the F1 and F2 measurements are each analyzed at two time points within the vowel: 20% and 80%. Statistical tests were in the form of linear mixed effects regression models. The normalized formant value (F1 or F2 z-score) was the dependent variable. Independent variables were the social variables of gender, ethnicity, and their interaction.
Word and speaker were treated as random effects. Statistical tests were performed and significance values calculated using functions from the lme4 and lmerTest packages (Bates, Maechler, Bolker & Walker 2015; Kuznetsova,
Brockhoff & Christensen 2015) in the statistical software package, R (R
Development Core Team 2016). Group means and standard deviations were obtained from normalized data by using the vowels package (Kendall and
Thomas 2010). Results are considered statistically significant when p is less than
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or equal to 0.05. Results are reported as trends when p is greater than 0.05, but less than 0.1.
In order to measure the amount of movement across the F1 X F2 vowel space that is traversed during the production of diphthongs, the Euclidean
(straight-line) distances were measured in F1and F2 formant space for all tokens of BITE, BAIT, BOUT, BOAT, and BOY. This took place after the normalization process; therefore, the calculations were accomplished using z-scores (Lobanov
1971). Euclidean distances were tested for significance in the same manner as the F1 and F2 formants. This included linear mixed effects regression models wherein the Euclidean distances were the dependent variables. Independent variables were gender, ethnicity, and their interaction, and word and speaker were random effects.
For F1, F2, and Euclidean Distance, box plots were produced in order to better visualize the behavior of the statistically significant data, particularly in situations where there existed predominant effects due to gender, ethnicity, and their interaction.
2.7 Plotting techniques
Vowel plots, boxplots, and vowel polygons were created through the programming language Python (Python Core Team 2015), along with the
Anaconda interpreter (Anaconda Software Distribution 2016) and the toolbox matplotlib (Hunter 2007). For box plots, the box itself encapsulates plus and minus one standard deviation, with the median delineated by a light horizontal
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line. The whiskers above and below the box each represent one standard deviation from the mean. Any outliers, e.g. tokens beyond two standard deviations from the mean, are represented by small circles. The map of New
Mexico showing speaker origin (Figure 2.1) was created in R (R Development
Core Team 2016) using ggplot2 (Wickham 2009), ggmap (Kahle and Wickham
2013), and grid (Murrel 2016). All other visuals were created in Microsoft Excel.
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Chapter 3: Results
3.0 Overview
This chapter compares the vowel formant findings across the four groups included in this study: Anglo females, Anglo males, Hispanic females, and
Hispanic males. The first section covers 9 monophthongs. The second section examines 5 diphthongs. Then the complete vowel space is discussed and the overall results and trends are considered. The chapter closes with a brief summary of my findings.
For each vowel, statistically significant findings of gender, ethnicity, or the interaction of gender and ethnicity will be presented, accompanied by the corresponding regression table and boxplot. If there are main effects on the
Euclidean Distance of a diphthong, then the regression table, a magnified image of the trajectory and a table of trajectory distances will also be given. In all cases
(monophthong formant measurements, diphthong formant measurements, and
Euclidean Distance), two separate statistical comparisons were done for each vowel; one assessing significant findings in the F1 dimension and one in the F2 dimension. With the exception of the first vowel, BEET, each vowel section will conclude with a F1/F2 plot showing individual speaker means in relation to the overall vowel space. For BEET, the plot is presented earlier in order to orient the reader to the framework of the chapter.
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3.1 Monophthongs
The results for the analysis of the monophthongs starts with the BEET vowel and then examines each monophthong in turn, ending with BOOT. Note that BAIT and BOAT are grouped with the diphthongs in section 3.2.
3.1.1 BEET
Figure 3.1, and all subsequent plots of this kind, show the normalized formant values for all speakers, with each plot symbol showing the mean for one speaker.
The four speaker groups (Anglo Female, Anglo Male, Hispanic Female, and
Hispanic Male) are distinguished by different symbols. The individual speaker means for other monophthongs are shown with light grey + symbols so as to situate the vowel of interest within the entire vowel system. Measurements along both axes are marked in terms of z-scores, or number of standard deviations from the mean (middle) point of the vowel space, which is labeled zero in both the first and second formant dimensions. This means that a vowel located near -
2 in the F1 direction is higher in the vertical vowel space than a vowel at -1, and a vowel near -2 in the F2 direction is further back in the horizontal vowel space than -1. The vowel plot for BEET is presented before the statistics in order acclimate the reader to the z-scores and how they relate to vowel space. For further vowels, the statistical data will be presented before the vowel plot.
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Figure 3.1: BEET by Ethnicity and Gender
In the F1 dimension, there is a main effect of gender (p<.001). Males produce BEET with a lower F1, thus higher in the vowel space. The average z- score of males can be ascertained from Table 3.1 by adding the z-score for genderMale under the Estimate column (-0.26205) to that of the Intercept (-
1.36943), which sums to (-1.63418). As (-1.63418) is further from zero than is the intercept score of (-1.36943), that means males produce BEET further from the midpoint of the F1 vowel space, or higher than do the females.
BEET f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) -1.36943 0.10384 5.514 -13.19 2.22e-05 ***
genderMale -0.26205 0.05564 11.876 -4.71 0.00052 *** Table 3.1: Summary of main effects on BEET normalized F1
Interestingly, this gender difference remains statistically significant even though the values for the male speakers are broadly dispersed. That is, while
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men overall have a lower F1 for the BEET vowel, there are also a number of outliers for the male group that have higher F1 values. See Figure 3.2, where the median is indicated by a light horizontal line, the box encloses the first standard deviation above and below the mean, the whiskers encapsulate the second standard deviation above and below the mean, and outlying data points are represented by open circles.
Figure 3.2: F1 BEET by gender
There were no significant effects for BEET in the F2 dimension.
3.1.2 BIT
No significant effects were found for this vowel. BIT appears in its canonical position across all four speaker groups. See Figure 3.3.
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Figure 3.3: BIT by Ethnicity and Gender
3.1.3 BET
The main effects of ethnicity, gender, and their interaction were all statistically significant (p<.001) in the F1 dimension. See Table 3.2, below.
Specifically, Anglo females have a BET vowel lower in the vowel space than do the other groups. Figure 3.4 highlights this difference.
BET f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) 0.86341 0.09868 2.81 8.75 0.00402 ** ethnicityHispanic -0.39539 0.05994 134.09 -6.596 8.94e-10 *** genderMale -0.35525 0.06288 134.06 -5.649 9.25e-08 *** ethHispanic:gendMale 0.34234 0.08477 134.05 4.038 9.01e-05 *** Table 3.2 Summary of main effects on BET normalized F1
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Figure 3.4: BET F1 by Ethnicity and Gender
In the F2 dimension, Table 3.3 demonstrates that only ethnicity was significant (p<.01). Anglos have a BET vowel located further back in the vowel space than Hispanics, as can be seen in Figure 3.5.
Std. BET f2 Estimate Error df t value Pr(>|t|) (Intercept) 0.2665 0.04726 13.856 5.638 6.36e-05 *** ethnicityHispanic 0.21481 0.06608 14.129 3.251 0.00575 ** Table 3.3: Summary of main effects on BET normalized F2
Figure 3.5: BET F2 by Ethnicity
Figure 3.6 shows the mean BET vowel measurements for each speaker.
In the F1 dimension, Anglo females are almost completely set apart from all other
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speakers. The ethnicity difference in F2 whereby Anglos produce BET closer to the central point of the vowel space than do Hispanics is also evident.
Figure 3.6: BET by Ethnicity and Gender 3.1.4 BAT
There was a strong trend (p=.0562) for gender as a main effect in F1, such that females tended to have a BAT vowel with higher F1, that is, lower in the vowel space. Table 3.4 and Figure 3.7 show the gender difference in the first formant.
BAT f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.608 0.128 1.534 12.563 0.0157 * genderMale -0.1799 0.0859 13.144 -2.094 0.0562 . Table 3.4: Summary of main effects on BAT normalized F1
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Figure 3.7: F1 BAT by Gender
For F2 measurements, there were significant main effects of gender
(p<.01), the interaction of gender and ethnicity (p<.05), and a trend for ethnicity
(p=.09059). See Table 3.5.
BAT f2 Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.3364 0.106 10.886 -3.173 0.00899 ** ethnicityHispanic 0.2502 0.1362 12.266 1.837 0.09059 . genderMale 0.5762 0.137 12.525 4.207 0.00111 ** ethHispanic:genMale -0.4519 0.1926 12.245 -2.346 0.03657 * Table 3.5: Summary of main effects on BAT normalized F2
Females, particularly, in the Anglo group, have an F2 positioned further back in the vowel space, as can be seen in Figure 3.8. The figure also shows that Anglo women have the lowest F2 of the four speaker groups, while Anglo men have the highest F2. The boxplot highlights that there is virtually no overlap between Anglo men and women.
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Figure 3.8: F2 BAT by Gender*Ethnicity
The speaker means for BAT are located in the center of the lower part of the overall vowel space. Women of both ethnicities positioned BAT more towards the back of the vowel space while men of both ethnicities had more central vowels, or perhaps even slightly fronted. See Figure 3.9. The Hispanic speaker groups pattern similar to one another and have much less difference than between the Anglo men and women. This split across the Anglo participants, but not the Hispanic participants, is quite interesting. Anglo men appear to be not only conservative in their production of BAT, but they are perhaps even resisting
BAT-retraction.
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Figure 3.9: BAT by Ethnicity and Gender
3.1.5 BAN
There is a main effect of ethnicity in F1 (p<.001) for the BAN vowel. Table
3.6 highlights that the Anglo F1 value for this vowel is .2896, while that of the
Hispanic group is .2896 + 1.1791, or 1.4687. The boxplot in Figure 3.10 demonstrates this as well.
BAN F1 Estimate Std. Error df t value Pr(>|t|) (Intercept) 0.2896 0.1695 14.101 1.709 0.109416 ethnicityHispanic 1.1791 0.2393 14.025 4.926 0.000222 *** Table 3.6 Summary of main effects on BAN normalized F1
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Figure 3.10 F1 BAN by ethnicity
The main effect of ethnicity is also found in the F2 dimension (p<.001) for
BAN. Table 3.7 and Figure 3.11 work to show the near-total lack of overlap in the
F2 dimension for these two speaker groups. Hispanic speakers produce BAN closer to the middle of the F2 vowel space.
BAN F2 Estimate Std. Error df t value Pr(>|t|) (Intercept) 0.8758 0.1177 14.038 7.439 3.11e-06 *** ethnicityHispanic -0.8586 0.1663 13.96 -5.164 0.000145 *** Table 3.7 Summary of main effects on BAN normalized F2
Figure 3.11: F2 BAN by ethnicity
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The BAN vowel in Figure 3.12 shows the most striking ethnicity-based difference in this study, as there is no overlap between ethnicities. Note that while the Hispanic participants of both genders cluster together, the Anglo participants vary widely, along both the F1 and F2 dimensions. All Anglo participants show evidence of the pre-nasal BAT split, whereby the BAT vowel raises before a nasal consonant (Labov, Ash, & Boberg, 2006; Eckert 2008).
Hispanics, on the other hand, did not participate in this phenomenon. That all
Anglos participate in BAN-raising, but do so to varying degrees, is interesting.
This could mean that the target location for BAN for Anglos is changing; yet if that were the case, one would expect that women would be leading the change and there would therefore be a visible gender difference. Alternatively, it may be that any raising at all of BAN, no matter the degree, is marked as Anglo-sounding in New Mexico. In any case, this variation is very apparent in Figures 3.10 and
3.11; while the boxplots for Hispanic productions of BAN are compact, the Anglo boxplots are much longer, indicating more variation among Anglo participants.
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Figure 3.12: BAN by Ethnicity and Gender
3.1.6 BOT
No significant effects were found for this vowel. Note the very dense cloud of speaker means in Figure 4.13, which further supports the presence of just one low back vowel for these speakers, as opposed to a BOT/BOUGHT distinction.
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Figure 3.13: BOT by Ethnicity and Gender
3.1.7 BUT
There is a main effect of ethnicity for F1 (p<.05). Table 3.8 and Figure
3.14 show that Anglos have an F1 lower in the vowel space than Hispanics.
BUT f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) 0.66822 0.08988 6.558 7.434 0.0002 *** ethnicityHispanic -0.20347 0.07816 14.53 -2.603 0.0204 * Table 3.8: Summary of main effects on BUT normalized F1
Figure 3.14: F1 BUT by Ethnicity
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There was a main effect of gender for BUT in F2 (p<.001), with women having higher normalized values for F2 (more fronted vowels) than men. See
Table 3.9 and Figure 3.15.
BUT f2 Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.45819 0.05149 9.324 -8.899 7.39e-06 *** genderMale -0.2256 0.05243 14.27 -4.303 0.000699 *** Table 3.9: Summary of main effects on BUT normalized F2
Figure 3.15: F2 BUT by Gender
The position of BUT appears in an expected location within the overall vowel space in Figure 3.16. Note that the four groups in this study are each quite easy to distinguish due to the nearly complete lack of overlap among the groups.
The speaker means for BUT thus fall into four quadrants in this plot: Hispanic women are the top left values, Hispanic men the top right, Anglo women the bottom left, and Anglo men the bottom right.
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Figure 3.16: BUT by Ethnicity and Gender
3.1.8 BURT
No significant effects were found for this vowel. BURT appears in its expected position across all four speaker groups. See Figure 3.17.
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Figure 3.17: BURT by Ethnicity and Gender
3.1.9 BOOT
There are no significant effects in the F1 dimension. In the F2 dimension, there are main effects of ethnicity (p<.01), gender (p<.01), and their interaction
(p<.05). See Table 3.10.
BOOT F2 Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.4398 0.1999 1.9610 -2.200 0.16130 ethnicityHispanic -0.6574 0.1577 12.2280 -4.169 0.00125 ** genderMale -0.5405 0.1581 12.3620 -3.420 0.00488 ** ethHisp:gendMale 0.4988 0.2233 12.2950 2.234 0.04479 * Table 3.10: Summary of main effects on BOOT normalized F2
Anglo females again pattern rather separately from the other speakers. In this case, they produce BOOT more fronted, as can be seen in Figure 3.18.
There is very little overlap between the F2 values of Anglo females and all other
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speakers. Anglo men appear to pattern more similarly to the Hispanic speakers than to Anglo women.
Figure 3.18: F2 BOOT by Ethnicity and Gender
Figure 3.19 highlights how Anglo female speakers produce BOOT more centrally in the vowel space, followed by Anglo males and Hispanics.
Figure 3.19: BOOT by Ethnicity and Gender
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3.1.10 Summary of monophthongal vowel space
This section has covered the monophthongs BEET, BIT, BET, BAT, BAN,
BOT/BOUGHT, BUT, BURT, and BOOT. There were nine significant findings for monophthongs. In five of the nine cases, ethnicity alone was statistically significant at p<.05 or less: Anglos have a more backed BET, higher and more fronted BAN, and a lower BUT vowel. Gender alone was significant in two cases: men produce a higher BEET as well as a more backed BUT. Finally, in three cases a combination of two or more factors among gender, ethnicity, and their interaction were significant: Anglo women have a lower BET, Anglo women have the furthest back BAT while Anglo men have the most fronted BAT, and
Anglo women have the most fronted BOOT. These findings are summarized in
Table 3.11.
Vowel F1 F2
BEET gender -
BIT - - ethnicity ethnicity BET gender interaction ethnicity BAT - gender interaction ethnicity ethnicity BAN
BOT - -
BUT ethnicity gender
BURT - - ethnicity BOOT - gender interaction Table 3.11: Significant effects for monophthongs
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Figure 3.20 below includes the monophthong vowel diagrams of the 4 speaker groups. Note that the values for BOAT are plotted in the graph, as this vowel is traditionally included in vowel plots. However, the patterning of BOAT for the different speaker groups will be discussed in more depth in the coming diphthong section.
Figure 3.20: Vowel diagrams for the four speaker groups
Several of the findings discussed above are particularly prominent in the diagrams. First, Hispanic males pattern most distinctly from all other groups. This is especially salient with BAN, which is located lower than all other vowels in the vowel space, and BOOT, which shows virtually no fronting. Second, the
BAT/BAN split across ethnicities is clear. While Anglos have a BAN vowel located higher and more fronted than BET, Hispanic speakers show no such
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division between BAT and BAN. Lastly, there is a dramatic difference in F2 across speaker groups in terms of the BAT, particularly when using BUT as a reference point. While there is almost no difference in F2 between BAT and BUT for Anglo females, there is an enormous difference for Anglo males.
3.2 Diphthongs
For the five diphthongs included in this study (BOAT, BOY, BAIT, BITE,
BOUT), measurements at two time points are included: at 20% and 80% of each vowel’s duration. The 20% time point will be referred to as onset and the 80% time point as offglide. As described in the Methods chapter, the Euclidean
Distance was calculated as the straight-line difference in F1 X F2 space between the onset and the offglide.
3.2.1 BOAT
Ethnicity did not have a significant effect on F1 at onset, but did affect F2 onset (p < .01). The onsets of Anglo speakers were further forward in the vowel space than those of Hispanic speakers. See Table 3.12 and Figure 3.21.
Boat f2 Estimate Std. Error df t value Pr(>|t|) (Intercept) -1.0672 0.03281 16.477 -32.529 2.22e-16 *** ethnicityHispanic -0.17147 0.04485 15.036 -3.823 0.00166 ** Table 3.12: Summary of main effects on BOAT normalized F2 onset
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Figure 3.21: F2 BOAT by Ethnicity
For the offglide, there were significant effects of both ethnicity (p<.05) and gender (p<.05) on F1. Hispanic men have a lower F1 value than the other speaker groups, as can be seen in Table 3.13 and Figure 3.22. There were no significant effects on the offglide of F2.
BOAT f1glide Estimate Std. Error df t value Pr(>|t|) (Intercept) -1.03099 0.04378 8.089 -23.55 9.68e-09 *** ethnicityHispanic 0.12288 0.04943 12.103 2.486 0.0285 * genderMale 0.14071 0.04925 11.874 2.857 0.0146 * Table 3.13: Summary of main effects on BOAT normalized F1 offglide
Figure 3.22: F1 offglide BOAT by Ethnicity and Gender
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No significant effects were found for the Euclidean Distance of the BOAT vowel.
Figure 3.23 shows highlights the difference in F2, particularly at the onset, based on ethnicity. Anglo speakers have a more fronted onset of BOAT than Hispanic speakers.
Figure 3.23: BOAT by Ethnicity and Gender
3.2.2 BOY
There is a significant effect of gender (p<.01) as well as trends for ethnicity
(p=.09914) and interaction (p=.07201) in the F1 of BOY at the onset, which is shown in Table 3.14. Figure 3.24 shows the boxplots for just gender, the only variable to reach statistical significance rather than trend. There were no significant effects in F1 at the offglide.
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BOY f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.87107 0.08193 11.101 -10.631 3.69e-07 *** ethnicityHispanic 0.19252 0.10621 10.287 1.813 0.09914 . genderMale 0.51482 0.12572 9.993 4.095 0.00217 ** ethHisp:genMale -0.31785 0.15716 9.553 -2.022 0.07201 . Table 3.14: Summary of main effects on BOY normalized F1 onset
Figure 3.24: F1 onset of BOY by Gender
For F2, there is a main effect of ethnicity (p<.05) for the onset. This is reflected in Table 3.15 and Figure 3.25. Main effects of ethnicity (p<.01), gender
(p<.01) and the interaction of these (p<.001) were all significant for the F2 offglide measurement. See Table 3.16 and Figure 3.26.
BOY f2 Estimate Std. Error df t value Pr(>|t|) (Intercept) -1.9404 0.06006 11.443 -32.31 1.33e-12 *** ethnicityHispanic 0.21044 0.0762 11.233 2.762 0.0182 * Table 3.15: Summary of main effects on BOY normalized F2 onset
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Figure 3.25: F2 onset of BOY by Ethnicity
BOY f2glide Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.4291 0.1495 11.269 -2.87 0.014908 * ethnicityHispanic 0.7116 0.1928 10.256 3.691 0.003995 ** genderMale 1.4126 0.2278 9.939 6.202 0.000104 *** ethHisp:genMale -1.3561 0.2838 9.391 -4.779 0.000891 *** Table 3.16: Summary of main effects on BOY normalized F2 offglide
Figure 3.26: F2 offglide BOY by Ethnicity and Gender
Main effects of gender (p<.01) and interaction (p<.01), as well as a trend for ethnicity (p=.08166), were found for the Euclidean Distance of the BOY vowel, as seen in Table 3.17.
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BOY ED Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.5224 0.2244 10.14 6.783 4.52e-05 *** ethnicityHispanic 0.57 0.2934 9.684 1.943 0.08166 . genderMale 1.4907 0.3486 9.483 4.277 0.00183 ** ethnicityHispanic :genderMale -1.5223 0.438 9.236 -3.476 0.00671 ** Table 3.17: Summary of main effects on BOY normalized Euclidean Distance
This leads to the ordering of the speaker groups with respect to Euclidean
Distance that can be seen in Figure 3.27.
Figure 3.27: Euclidean Distance of BOY by speaker group
Anglo women have the shortest Euclidean Distance, followed by Hispanic men,
Hispanic women, and finally Anglo men. While both genders of Hispanic participants pattern relatively similarly, Anglo men have a Euclidean Distance nearly twice that of Anglo women. Figure 3.28 shows the overall BOY vowel.
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Figure 3.28: BOY by Ethnicity and Gender
3.2.3 BAIT
There are no significant effects on the formants at 20% or 80% completion through the vowel or for Euclidean Distance. Brumbaugh and Koops (in press) reported significant effects on F1 and F2 when measured at the midpoint (50%).
The mean values of the different speaker groups are plotted in Figure 3.29.
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Figure 3.29: BAIT by Ethnicity and Gender
3.2.4 BITE
As with BAIT, no significant effects of gender or ethnicity were found for
F1, F2, or Euclidean Distance in this vowel. See Figure 3.30.
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Figure 3.30: BITE by Ethnicity and Gender 3.2.5 BOUT
The onset of F1 has main effects of ethnicity (p<.05), gender (p<.001), and their interaction (p<.05) in Table 3.18 below. There are no significant effects for the F1 offglide.
BOUT f1 Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.01593 0.08586 13.766 11.833 1.34e-08 *** ethnicityHispanic 0.27527 0.11065 12.079 2.488 0.028432 * genderMale 0.62798 0.1249 10.151 5.028 0.000493 *** ethHisp:genMale -0.47219 0.1592 10.102 -2.966 0.013991 * Table 3.18: Summary of main effects on BOUT normalized F1 onset
Figure 3.31 highlights the differences among speaker groups. Again the
Anglo females are quite distinct and produce BOUT much higher in the vowel space, and again the Anglo men and women pattern opposite from each other.
The Hispanic speakers, on the other hand, pattern similarly across the genders.
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As this analysis is based on tokens that start with a voiced consonant (as in
BOWED and BOUNCED), the raising demonstrated by the Anglo women isn’t due to Canadian-Raising or a similar pattern.
Figure 3.31: F1 BOUT by Ethnicity and Gender
There are no significant effects in the F2 dimension.
For Euclidean Distance, Table 3.19 lists the main effects of ethnicity
(p<.05), gender (p<.05) and interaction (p<.05). This leads to the following ordering of the speaker groups for Euclidean Distance, as can be seen in Figure
3.32.
BOUT ED Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.0503 0.1941 9.35 5.412 0.000374 *** ethnicityHispanic 0.6129 0.2541 8.87 2.412 0.039475 * genderMale 0.6972 0.2946 7.956 2.367 0.045656 * ethnicityHispanic :genderMale -0.9197 0.3749 8.068 -2.453 0.039501 * Table 3.19: Summary of main effects on BOUT normalized Euclidean Distance
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Figure 3.32: Mean Euclidean Distance for BOUT by speaker group
The results displayed in Figure 3.3 for the Euclidean Distance of BOUT are ordered the same as for that of BOY. Anglo females have the shortest distance, followed by Hispanic males and then Hispanic females. Anglo males have the longest Euclidean Distance. Again, the Hispanic groups patterns very similarly while there is an apparent gender split among the Anglo group. Figure 3.33 below shows the overall placement of BOUT by speaker group.
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Figure 3.33: BOUT by Ethnicity and Gender
3.2.6 Summary of Diphthongs
This section examined the values of F1 and F2 at the onset and offglide of the diphthongs BITE, BAIT, BOUT, BOAT, and BOY. In addition, the effects of gender and ethnicity were tested in the Euclidean Distance between those two time points. For BITE and BAIT, there were no significant differences across the four speaker groups for any of the measures. BOUT showed significant effects only in F1 at the onset of the diphthong and in the Euclidean Distance. BOAT and BOY showed some significant effects at both the onset and the offglide for a subset of the measures of F1, F2 and the Euclidean Distance of the diphthong.
These results are summarized in Table 3.20.
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Vowel F1 onset F1 glide F2 onset F2 glide Euclidean Distance BITE - - - - - BAIT - - - - - BOAT - ethnicity ethnicity - - gender BOUT ethnicity - - - ethnicity gender gender interaction interaction BOY gender - ethnicity ethnicity ethnicity interaction gender gender ethnicity (trend) interaction interaction Table 3.20: Summary of main effects for diphthongs
Ethnicity is a significant factor at the onset of the vowel in F1 for BOUT, and in F2 for BOAT and BOY. For the F1 at the onset of BOY, ethnicity is approaching significance and is reported as a trend. In addition, ethnicity is significant in F1 for the offglide of BOAT and in F2 for the offglide of BOY. With only two of the five vowels having Euclidean Distance as a significant factor, it is possible that either 1) the space traversed by the diphthong is not significantly different across these populations or 2) the FAVE extract algorithm, which is less accurate near the edges of vowels, did not effectively capture the differences
(see section 4.2.2 Distance of Diphthongs for further discussion).
Of the five diphthongs, three (BITE, BADE, and BOAT) had no statistically significant differences in Euclidean Distance among the speaker groups. The other two diphthongs, BOY and BOUT, showed significant main effects (and in one case, a trend) in Euclidean Distance, see Table 3.21:
Length of ED Speaker Group BOY BOUT shortest Anglo Female 1.5224 1.0503 Hispanic Male 2.0608 1.443 Hispanic Female 2.0924 1.6632 longest Anglo Male 3.0131 1.7475 Table 3.21 Euclidean Distances by group
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In both cases, Anglo females have the shortest distance between onset and offglide, followed by Hispanic males. Hispanic females are next, and Anglo males have the largest Euclidean Distance. Similar to the BAT vowel, Hispanics patterned very similarly across genders, while Anglo females and males patterned quite differently from one another. In the case of the BOY vowel, for example, Anglo males produced a Euclidean Distance nearly double that of
Anglo females.
Considering the results of the diphthong analysis from a more global perspective, the front-to-back dimension of the vowel space may play a role. The only diphthongs for which there were main effects of gender, ethnicity, or their interaction were those that contain either an onset or offglide with a high or near- high back vowel (BOAT, BOUT, and BOY). In contrast, the furthest fronted diphthongs, BITE and BAIT, showed no significant effects. A more in-depth study utilizing natural speech and a wider variety of phonetic environments may be able to make this picture clearer. The diphthongs show fewer significant differences between ethnic groups than did the monophthongs, suggesting that perhaps they play less of a role in characterizing the different speaker groups.
3.3 Conclusions
3.3.1 Research Question 1
My first research question was: How do the locations of individual vowels and their trajectories, as well as a speaker’s total vowel space, compare across the genders (male, female) and ethnicities (Anglo, Hispanic) within this study?
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3.3.2 Hypothesis 1
First, I hypothesized that Anglos and Hispanics would pattern differently with respect to a split between the vowels of BAT and BAN. Recall Figure 3.12:
Figure 3.12: BAN by Ethnicity and Gender (reprinted)
The plotted values for BAN are completely distinct for the Anglo and Hispanic groups, and ethnicity was the only main effect for both F1 (p=.000222) and F2
(p=.000145). Visually and statistically, there is a clear difference between Anglo and Hispanic participants in both formant dimensions of BAN. Though the vowels produced by the Hispanic women appear to be slightly higher in the vowel space than those of the Hispanic men, this difference was not statistically significant.
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3.3.3 Hypothesis 2
My second hypothesis was that the Hispanic females would pattern more closely to the Anglos than to Hispanic males. Characteristics of the California
Vowel Shift were expected for Anglo speakers as well as at least some participation on the part of Hispanic women. (see Research Question 2). As the
CVS is a set of linguistic changes that occur below the level of social awareness and do not carry overt prestige, women are most often the leaders of such change (Labov 1990, Labov 2001, Wolfram & Schilling-Estes 2004). In this case, that would mean that Hispanic women would begin to adopt some or all of the
CVS features before Hispanic men. In doing so, their vowels and vowel space would therefore be more similar to those of the Anglo speakers. It would also support the idea that the California Vowel Shift (further discussed in Chapter 5) is an Anglo-led change.
However, the results from this study are more complicated than predicted, as Anglo men and women are less homogenous than expected. This is due in part to the fact that in several vowels, Anglo men and women pattern very differently. For instance, the F2 means for BAT were such that Anglo men had the most fronted vowel, followed by Hispanic men, then Hispanic women, and finally Anglo women with the most retracted BAT. In this case, the Hispanic women are patterning similarly to Anglo women, but not Anglo men. In other cases, such as BOOT, Anglo men and women both show fronting, and Hispanic women appear to be following in line with that behavior. Therefore, it is more
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accurate in some cases to say that Hispanic women are patterning like Anglo women.
3.3.4 Hypothesis 3
My third hypothesis was that there would be a shorter trajectory in the diphthongs of Hispanics as compared to Anglos. As such, I predicted that there would be more monophthongization, or less distance between onset and offglide, for the short diphthongs BAIT and BOAT among the Hispanic speakers compared to the Anglo speakers. This hypothesis was not supported by the data, as there was no statistically significant difference among speaker groups for
BAIT and BOAT trajectories.
3.3.5 Hypothesis 4
Lastly, I expected that the Hispanic participants would have a larger overall vowel space. See Figure 3.34.
Figure 3.34: Vowel quadrilateral by ethnicity
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Utilizing the shape most often used to characterize the vowel space of speakers of American English, the quadrilaterals above show the mean location for BEET, BAT, BOT, and BOOT for Anglo and Hispanic groups. While the Anglo quadrilateral extends slightly further than that of the Hispanics in both the BEET and BOT corners, note the much larger area that the Hispanic quadrilateral covers in the BOOT corner. It thus appears that the hypothesis is supported, although this result is due solely to the more extreme values that the Hispanic speakers have for the BOOT vowel.
3.4 Summary
This chapter has examined the similarities and differences across four groups of New Mexicans between the ages of 18 and 28 years old: Anglo females, Anglo males, Hispanic females, and Hispanic males. The majority of the analysis focused on monophthongs, while the final portion of the chapter examined diphthongs. The results suggest that ethnicity and gender are both important social variables in New Mexico that can be indexed through vowel variation, and F1/F2 formant measures are used to index ethnicity and gender.
The next chapter (Chapter 4) will relate these participants and their vowel productions in comparison with results from similar studies across the United
States.
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Chapter 4: Discussion
4.0 Overview
This chapter addresses my second and third research questions by comparing the findings of this study with those of other research that has examined similar populations. Specifically, I consider the extent to which New
Mexico participates in sound changes characteristic of the western linguistic region of the United States as well as Chicano English speakers’ participation in local vowel variation.
4.1 Third Dialect, Western States, and California Vowel Shift
My second research question addresses the extent to which New
Mexicans’ English is characterized by the Western Vowel Space or the California
Vowel Shift. I examine in turn three broad descriptions of vowels in the West:
Third Dialect, Western States, and the California Vowel Shift.
4.1.1 Third Dialect
The Third Dialect was described by Labov (1991) as having three characteristics: BOT/BOUGHT merger, BAN-raising, and BAT-retraction. I hypothesized that BOT/BOUGHT merger would be present for all speakers regardless of social factors, BAN-raising would only occur for Anglos, and BAT- retraction would be near non-existent. The data in this study strongly supported the first two parts of my hypothesis in that no speakers show any significant differentiation between BOT and BOUGHT, and only Anglo speakers raise BAN.
As far as BAT retraction, it appears that Anglo females slightly retract this vowel,
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and Hispanic women do so a little less. Men do not show this pattern regardless of ethnicity. In fact, Anglo men show the least backed, i.e. the most fronted, mean values for BAT.
4.1.2 Western Vowel Space
In addition to the three features of the Third Dialect (BOT/BOUGHT merger, BAN-raising, BAT-retraction), the Western Vowel System (Labov, Ash, &
Boberg, 2006) also includes BOOT-fronting and slight BOAT-fronting. My hypothesis was that Anglos would show the most fronting, followed by more minimal fronting of Hispanic females, and no fronting on the part of Hispanic males in these sound changes. The data partially supported this hypothesis.
Examining these two additional properties that characterize the Western
Vowel Space, with respect to BOOT-fronting, the Anglo females produced the most fronted BOOT tokens, and Anglo males had the next most fronted. Hispanic females appear to follow behind the Anglos in this fronting, while Hispanic men continue to have a traditionally backed BOOT vowel. See Figure 4.1.
Figure 4.1 BOOT by ethnicity and gender
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With regard to BOAT-fronting, only ethnicity was statistically significant in the F2 dimension of BOAT. Anglos have only a slightly more fronted BOAT. See
Figure 4.2.
Figure 4.2 BOAT by ethnicity and gender
Therefore, it appears that Anglo speakers participate more than Hispanics in these two sound changes. In the case of BOOT-fronting, Hispanic women are advancing, but at a slower pace. For BOAT-fronting, it does not appear that
Hispanic speakers of either gender are participating in the change.
4.1.3 California Vowel Shift
The California Vowel Shift (CVS) is made up of: lowering and retraction of
BIT, BET, and BAT, raising of BAN, merging of BOT and BOUGHT, fronting of
BUT (according to some researchers (Eckert 2008) but not all (Holland &
Brandenburg in press)), and fronting of BOOK, BOOT, and BOAT (Hagiwara
1997; Fought 1999; Eckert 2008; Hall-Lew 2009; Kennedy & Grama 2012). I expected that Anglos would participate in these shifts, Hispanic females would to
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some extent as well, and Hispanic males would not, with the exception of the
BOT/BOUGHT merger which I expected all speakers to demonstrate. Further, I expected that Anglo participation would be less advanced in New Mexico than in other locales throughout the West that have been reported to participate in the
CVS. Much like the results for Western Vowel Space above (section 4.1.2), the results of my analysis were more complicated than simply Anglos patterning in one way, and Hispanics in another. Now I present a vowel-by-vowel analysis of
New Mexican participation in CVS.
• BIT: predicted to be lower and further back
No speakers in this study, regardless of gender or ethnic identity, showed
a lowering of BIT. This is not unheard of, as speakers in Oregon have been
reported to participate in CVS, but without the lowering of BIT (McLarty,
Kendall, & Farrington 2016).
• BET: predicted to be lower and further back
In the present study, the main effects of gender, ethnicity, and their
interaction were all significant in the F1 dimension such that Anglo women
showed the most lowered BET tokens, while the other three social groups
patterned together, slightly higher and more fronted in the vowel space. In
the F2 dimension, ethnicity was significant, because the Anglo speakers
had more retracted productions than the Hispanic speakers. Thus, the
CVS appears to be an accurate characterization of the Anglo women’s
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productions of BET, but less true for the Anglo men, and not at all for the
Hispanic speakers.
• BAT: predicted to be lower and further back
Main effects of gender and the interaction of gender and ethnicity, plus a
trend for ethnicity, provide evidence for a retracted BAT for Anglo females,
with Hispanic females slightly retracting BAT as well. As with BET, the
Anglo female speakers are the group who most closely mimic the patterns
of the CVS.
• BAN: predicted to be higher than BAT
Ethnicity was statistically significant as a main effect in both the F1
(p<.001) and F2 (p<.001) dimensions. Anglo speakers of both genders
raised and fronted BAN, while Hispanic speakers do not. Visually, there is
no overlap between the means of the Anglo and Hispanic speakers in
either the F1 or F2 dimensions. Raising of BAN is typical of speakers
participating in the CVS (Eckert 2008), so these findings are consistent
with Anglo but not Hispanic speakers participating in this vowel shift.
• BUT: predicted to be fronted by some researchers
Contrary to Eckert (2008), the speakers in the present study show some
evidence of BUT-retraction similar to that seen in the Colorado data of
Holland and Brandenburg (in press). To the extent that fronting of BUT is
part of the CVS, this result suggests that New Mexican speakers are not
participating in this feature CVS.
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• BOOK: predicted to be fronted
This vowel was not included in the present study.
• BOOT: predicted to be fronted
Fronting of this vowel in New Mexican speakers is minimal. Anglo females
show the most fronted position for BOOT; however, even they show only
rather limited fronting. Brumbaugh and Koops (in press) reported that New
Mexican BOOT was just above the first Atlas of North American English
benchmark for fronting (Labov, Ash, & Boberg, 2006), but only for Anglo
women. Anglo men and Hispanic women appear to be moving toward a
more fronted position, but this movement is less advanced for them than
for Anglo women, while Hispanic men maintain a more backed BOOT
vowel.
• BOAT: predicted to be fronted
The case of BOAT is similar to that of BOOT in New Mexico. Anglo
women show the most fronted BOAT vowel, but this fronting is by no
means extreme. Anglo men show advancement in BOOT-fronting as well,
but less than the Anglo women. Hispanic women show slight fronting while
Hispanic men continue to produce the retracted BOAT position.
In conclusion, while it appears that at least Anglo women in New Mexico are participating in the California Vowel Shift, its progression is less advanced than in other Western states where speakers are reported to participate in this
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shift. This leads to a new question for future research: Why is New Mexico's progression slower, or less advanced, than in other locales? It is possible that one factor is because NM is along the eastern-most border of the land that makes up the Western States dialect region. If that were the case, Colorado –
New Mexico’s neighbor to the north which also sits along the eastern border of the Western Region – should also show a limited effect of the CVS. This is not, however, the case. Rather, urban speakers and those with urban aspirations in
Colorado show very advanced stages of CVS (Holland & Brandenburg, in press).
An alternative explanation for New Mexico may involve the state’s ethnic makeup. While Colorado is predominantly Anglo, this is not the case for New
Mexico. Recall from Figure 1.1 that 38.3% of the state’s population is identifies as Anglo, meaning that 61.7% (nearly two thirds) is not Anglo. If the CVS is an
Anglo-driven shift, perhaps the fact that more than half of New Mexicans are not
Anglo leads to a slower adoption of CVS features. This is in part because maintaining local speech norms often coincides with Chicano English in this state. However, the finding that Hispanic women pattern closer to Anglo women than do Anglo men suggests that there may be an across-the-board gender effect for the CVS variables, irrespective of ethnicity. While Anglo females are the most innovative speakers in this study in terms of adoption of CVS features,
Anglo men show a much more conservative approach and sometimes a clear rejection of CVS features. For example, Anglo men front BOOT, one of the characteristics of CVS, but to a lesser degree than Anglo women. Like the
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Hispanic men, Anglo men do not, however, lower or back BET or BAT. That is not to say that Hispanic men and Anglo men are rejecting the lowering and retraction of BET and BAT for the same reasons. Hispanic women, on the other hand, do produce BAT in the direction that the CVS would suggest. It may be that Hispanic men are staying in line with Chicano English norms and Anglo men are simply linguistically conservative, meaning that they therefore reject newer linguistic forms (which in this case stem from the CVS). It may also be the case that Anglo men are assimilating to Chicano English norms. Further research is needed in order to answer the questions of what the social evaluations are for
Chicano English and the CVS in New Mexico as well as who is influencing who.
4.1.4 Summary of Third Dialect, Western States, and California Vowel Shift
This section has demonstrated the variation in the degree to which speakers in New Mexico participate in the vowel shifts that have been claimed to be present in the state. The trait that all speakers clearly share from the three descriptions above is the merging of BOT/BOUGHT. Otherwise, the ethnic and gender groups considered in this study show variable participation in the changes that characterize the Third Dialect, Western States vowel space, and the CVS.
For Third Dialect and Western States vowel space, it is the Anglo group, particularly the females, whose vowels are closest to the descriptions of these varieties. Note the near-total lack of participation amongst Hispanic men in Table
4.1:
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Partial No Vowel Description Vowel Participation Participation participation
BOT/BOUGHT 3rd dialect merger
3rd dialect BAN raising
3rd dialect BAT retraction
BOOT fronting Western Vowels Western
BOAT fronting Table 4.1: Participation in 3rd Dialect and Western States Vowel Characteristics. White shapes represent Anglo speakers, black shapes represent Hispanic speakers. Circles are females, triangles males.
As for California Vowel Shift, the pattern, which is shown in Table 4.2, is much the same as for the Third Dialect and Western States vowel spaces. Anglo women show near total participation in the shifts. Of the six shifts that the data document as taking place in New Mexico, Anglo women participate in all six.
Anglo men show near total participation in three, and partial participation in two.
Hispanic women show full participation in one, and partial participation/advancement in four others. Hispanic men participate in just one: the BOT/BOUGHT merger. See Table 4.2.
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Partial No Vowel Participation Participation Participation BIT lowering and retraction
BET lowering and retraction
BAT retraction BAN raising
BOT/BOUGHT merger BUT fronting BOOK fronting (no data) (no data)
BOAT fronting
BOOT fronting Table 4.2: Participation in California Vowel Shift Note: White shapes represent Anglo speakers, black shapes represent Hispanic speakers. Circles are females, triangles males.
4.2 Chicano English
My third research question asked how data from the Hispanic speakers in
New Mexico compare to data from Hispanic communities in other regions of the
United States. My hypothesis was that New Mexico Hispanics would not participate in a split between the vowels of BAT and BAN, and that Hispanic speakers would have shorter trajectories for the BAIT and BOAT diphthongs than
Anglos. I also expected that there would be little to no participation in the Anglo- led vowel shifts occurring throughout the West. In cases where there is Hispanic participation in these shifts, I predicted that females would demonstrate patterns tending in the direction of the Anglo speakers.
4.2.1 BAT/BAN split
Neither Hispanic New Mexican males nor females participate in the fronting and raising of the BAT vowel preceding a nasal. Figure 3.12 in Chapter 3
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shows positioning of speaker means for BAN within the entire vowel space. Both
F1 and F2 show very strong statistical significance (p<.001) with ethnicity. For the F2 dimension, in particular, there is no overlap in the boxplots of the Anglo and Hispanic groups.
While Anglo speakers all show participation in BAN-raising and fronting, this participation is not uniform in F1 or F2; as can be seen in the stark contrast between F2 values for BAT (dark grey) and BAN (light grey) in Figure 4.3.
Contrary to their Anglo counterparts, the Hispanic speakers (both male and female) show consistent grouping of speaker means for both BAT and BAN.
Though several of the other monophthongs included in this study show Hispanic females converging with Anglo vowel placements, this is not the case for
BAT/BAN. Instead, similar patterning of Hispanics of both genders for the BAN vowel suggest that the lack of BAN-fronting is an important, salient marker of ethnic identity in New Mexico.
Figure 4.3 F2 means by speaker for BAT and BAN
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Previous studies have produced similar findings in other Hispanic communities across the United States: while some communities exhibit no BAN-raising, there are others with limited or partial participation. Thomas (1993) found no evidence of BAN-raising in Chicano English speakers in Texas. Gordon (2000) similarly found very little BAN-raising in Chicano English speakers in northwest Indiana, and Frazer (1996) found that Hispanic women in nearby Sterling, Illinois exhibited slight BAN-raising (although Hispanic men did not). Eckert (2008), in her study of Hispanic teenagers in California, noted no BAN-raising; in distinct contrast to their Anglo peers. Total or near-total participation in BAN-raising has not been documented in the literature in any Chicano English communities. The most-total participation in BAN-raising was reported by Roeder (2009 & 2010) in
Michigan, who found that only young adult Hispanic females with the most advanced traits of Northern Cities Shift fully adopted BAN-raising. Importantly, their BAN-raising was complete; that is, their tokens of this vowel space mirrored those of their Anglo counterparts. Other sub-groups of Hispanic speakers
(women over the age of 25 and men of all ages) exhibited little to no BAN-raising.
Finally, it is of value to reiterate that differing levels of participation in BAN- raising underscore the fact that minority dialects are not homogenous; rather, each community participates differently compared to local Anglo norms. Section
4.2.3 will further examine this dialect variability.
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4.2.2 Distance of Diphthongs
I hypothesized that Hispanics would have diphthongs BAIT and BOAT as more monopthongal vowels than those produced by Anglo speakers. A diphthong was considered to be more monophthongal if it has a shorter distance between the F1/F2 onset and F1/F2 glide. The hypothesis for this phenomenon stems from Fought (2003), as she is the primary researcher to examine shortening of diphthongs in Hispanics. While Wolfram et al (2004) measured diphthong differences of the BITE vowel in North Carolina, which is commonly reduced among Anglo speakers, no other diphthongs were considered as part of his work. Fought (2003) noted that the Hispanic California high school students in her study exhibited a number of differences in diphthongs from their Anglo counterparts. Specifically, she noted BADE and BOAT had a variable glide; that is, some speakers produced a vowel much closer to a monophthong than a diphthong. My hypothesis that Hispanic speakers would also have shorter diphthong trajectories for BADE and BOAT was not supported by data, as no main effects reached statistical significance.
It is possible that the speakers in Fought (2003) pattern differently from the New Mexican speakers in this study. However, it is also possible that there are other factors contributing to diphthong trajectories and speaker ethnicity may not be the primary determinant. The data presented here only includes 437 tokens of diphthongs, an average of 4.46 tokens per speaker per diphthong. This may be an insufficient sample size to capture the primary determinant for
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diphthong trajectory. Additionally, Fought does not mention any specific methodology used for her analysis and it may be that her analysis was simply from her own perceptual findings, rather than derived analytically. In this case, our methodologies may be too different for comparison. Moreover, there are a number of ways to measure distance (see Konopka 2011 for an explanation of the four manners of measuring distance through VISC, or Vowel Inherent
Spectral Change). It may be that alternative methods are better suited for direct comparison of diphthong trajectories than using FAVE-extracted data. Formant tracks are generally less accurate in low intensity parts of the vowel (e.g. near the edges); the same goes for results generated by automated formant programs and applications as well. As BOAT and BAIT are short diphthongs, the glide trajectory is smaller than with other diphthongs; therefore very accurate data may be needed to identify trajectory distances. A dedicated analysis where the whole trajectory is more carefully examined might bring out a difference. Finally, as mentioned earlier, Fought (2003) is the only research that has addressed diphthongal differences across Anglos and Hispanics. This may be because other researchers have examined this phenomenon, but have not found significant differences across the speaker groups and declined to publish their negative results.
4.2.3 Participation in local non-ethnic sound changes
Aside from the BAT/BAN split and diphthongs with shorter distances between onset and glide, I hypothesized that the Hispanic speakers in this study
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would have little to no participation in local Anglo sound changes. For this study, these local sound changes included 1) Labov’s (1991) description of the Third
Dialect, 2) the ANAE description of Western States (Labov, Boburg, & Ash 2006), and 3) the California Vowel Shift (Eckert 2008). Importantly, I also hypothesized that if participation in these sound changes were found for Hispanic speakers, it would be less advanced than local Anglo participation and Hispanic women would participate more significantly than Hispanic men.
These hypotheses were confirmed. In New Mexico, it is Hispanic women who are participating to a much greater extent than Hispanic men in the three categories of sound changes studied in section 4.2. Hispanic men appear to participate exclusively in just one sound change: the merging of BOT and
BOUGHT. These findings are consistent with the majority of research on Chicano
English. Godinez and Maddieson (1983) reported male Hispanic high school students to have vowels located higher in the vowel space; more fronted BIT,
BET, BAT, and BOT, and a further backed BOOT than their Anglo counterparts.
Importantly, these features are essentially the opposite of what takes place in
California Vowel Shift, thereby reinforcing a seemingly total lack of participation on the part of male Hispanic youth. Gordon (2000) and Wolfram et al. (2004) similarly report little to no participation in local Anglo speech norms in northwest
Indiana and North Carolina, respectively.
The data in this study most closely resemble that of Roeder (2010) wherein she describes the participation in the Northern Cities Vowel Shift on the
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part of Mexican Americans in Lansing, Michigan. Although Roeder (2010) examines the NCS, while this study examines the CVS, the main theme of
Hispanics undergoing sound changes in line with Anglo sound changes remains similar. Comparable to the results in this study, Roeder (2010) reports greater participation in NCS on the part of Hispanic women than Hispanic men. While women of all ages are more advanced in this vowel shift, she finds that only women under age 25 show essentially identical participation compared to their
Anglo counterparts. This was not the case for the New Mexican data. None of the
Hispanic women in this study, regardless of age, could be described as having identical or nearly identical BAN distributions as their Anglo counterparts.
Although Hispanic females are participating in California Vowel Shift movements, they are not progressing as quickly compared to the Anglo women. Roeder also reports that Hispanic women raise BAN, while Hispanic men do not. In fact,
Hispanic women under 25 years of age show BAN-raising identical to their Anglo counterparts. In the New Mexico data, neither Hispanic men nor Hispanic women raise BAN. It would appear that the Hispanic community in Lansing is participating more fully in local sound changes than the Hispanic community in
New Mexico.
4.3 Chapter Summary
This chapter has examined how the data from New Mexican speakers compares to similar research elsewhere, addressing the second and third research questions for this work.
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The second research question examines how New Mexican English compares to the phonetic frameworks within which it has been claimed to be located and behave. The data confirm that while New Mexico is a state of the
West, it has not yet fully undergone the California Vowel Shift. Further, results support Third Dialect, Western States, and California Vowel Shift being primarily
Anglo-led. Specifically, in New Mexico, it is being led by Anglo women.
The third research question considers how Chicano English speakers pattern in comparison with other Hispanic communities in the United States.
There are both similarities and differences to previous studies on Hispanic versus
Anglo speakers. Hispanic New Mexicans show partial adoption of the Anglo-led sound changes mentioned above, and it is the women of this group showing more complete adoption, similar to results found in other Hispanic communities.
Raising of BAN is not found in the New Mexican data, similar to the majority of other communities in which Chicano English has been studied. Differences found between the Hispanics in this study and in other studies, such as advancement or degree of adoption of local Anglo sound changes, highlight the notion that
Chicano English is not one homogenous language variety, but heterogeneous and demonstrating geographic variation.
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Chapter 5: Conclusion
5.0 Overview
This final chapter comprises a summary of this dissertation, its findings, and how those findings, and therefore New Mexican speakers, compare to speakers in other communities. Next, the limitations of this study are considered and considerations for future work are discussed. I end with a brief conclusion.
5.1 Summary of study and results
Audio recordings were made of 16 university-age New Mexican speakers reading short stories and carrier phases in order to elicit specific target words.
Speaker groups were divided equally among gender and self-identified ethnicity, and all but one speaker originated from the northern half of the state. F1 and F2 measurements were extracted at the 50% point for nine monophthongs: BEET,
BIT, BET, BAT, BAN, BOT, BOUGHT, BUT, BURT, and BOOT. F1 and F2 measurements were extracted at the 20% and 80% points, and Euclidean distances were calculated, for five diphthongs: BITE, BAIT, BOUT, BOAT, and
BOY. Mixed effects statistical models were run in order to assess the statistical significance of ethnicity, gender, and their interaction. Models were run individually for each vowel’s F1 and F2 measurements, as well as for Euclidean
Distance traversed in formant space in the case of diphthongs.
Comparison across the four speaker groups (Anglo men, Anglo women,
Hispanic men, and Hispanic women) resulted in a number of interesting observations. All speakers showed a near-complete overlap of BOT and
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BOUGHT tokens, as expected given the well-documented merger of these vowels, particularly in the Western United States (Labov 1991; Labov, Ash, &
Boberg, 2006; Eckert 2008). The lack of a BOT/BOUGHT distinction in New
Mexico is reported in Brumbaugh & Koops (in press). In general, the Hispanic men and women patterned similarly. At the same time, Hispanic women always patterned more similarly to the Anglo women than the Hispanic men did. Anglo men and women did not present such a homogenous group as did the Hispanic men and women. While the Anglo groups shared some commonalities, namely the fronting and raising of BAN and the fronting of BOOT and BOAT, there were several cases in which Anglo men patterned in the opposite direction from Anglo women. Such was the case for BAT (which the women backed) and BUT (which the men backed).
These findings were then compared to regionally-based linguistic descriptions that have included New Mexico, despite those descriptions having an extremely limited number of New Mexican speakers in their data collection.
New Mexico is described as a Western State in the Atlas of North American
English (Labov, Ash, & Boberg, 2006), and thus New Mexican speakers would be expected to show characteristics of the Western States Vowel Space as described by Labov, Ash, and Boberg (2006). The data analyzed here suggest that this is at least partially true for both Anglo men and women for four of the five vowels described for this “vowel space”: BOT/BOUGHT merger, BAN-raising,
BOOT-fronting, and slight BOAT-fronting. The fifth vowel shift, BAT-retraction,
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only occurs among Anglo women. Hispanic women participate in the
BOT/BOUGHT merger and appear to be following in the direction of the Anglo women in all cases except BAN-raising. Hispanic men only show evidence of merging BOT/BOUGHT and no other changes. The four groups pattern in much the same ways with respect to the California Vowel Shift (CVS), which is to be expected since the vowel shifts typical of the Western States Vowel Space described above make up a large portion of the CVS characteristics. Namely,
Anglo women lead the way with advancement of the CVS, Anglo men and
Hispanic women follow (though to different degrees), and Hispanic men do not show any evidence of this shift.
Finally, the data from the Hispanic participants was considered alongside other research on Chicano English throughout the United States. The findings on diphthong trajectories in this study did not align with the limited previous research available (Fought 2003). This topic remains in need of further examination. The lack of a BAT-BAN split is a commonly documented characteristic in the Chicano
English literature, and the data in this study supported this as well. Finally, only
Hispanic women appear to participate in the local Anglo-led sound changes, albeit to a less advanced degree than Anglos. This finding is also a common theme throughout the literature on Chicano English.
5.2 Limitations
This dissertation has provided a number of observations about the vowels in New Mexican English. Nonetheless, it represents one of the very first phonetic
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examinations into variation in the English spoken in New Mexico. As such, a number of limitations should be considered and accounted for in future work.
First, a subsequent study should have a larger and more diverse set of speakers. The need for a larger speaker set needs no explanation; more speakers is always advantageous. Diversity, in terms of a study on Anglo and
Chicano English, includes a number of considerations. For the present study, all speakers were between 18 and 32 years old, lived in Albuquerque and attended or had attended the University of New Mexico, and were from the northern half of the state (with one exception). A future study would ideally include participants with a broader age range, different levels of educational background, and from different parts of the state. As mentioned in Chapter 1, the state of New Mexico is enormous in size. Such spatially-distant regions might lead to differing linguistic patterns and norms, particularly given the varying geography that historically isolated some regions, many of which are still quite rural today. This urban/rural axis may be key in understanding the adoption (or lack) of the California Vowel
Shift, as was the case for Colorado (Holland & Brandenburg, in press).
Furthermore, while northern and southern New Mexico both have long traditions of use of the Spanish language, the actual Spanish varieties are often said to be very different between these two populations. It is well within reason to hypothesize that the differences in Spanish may also correlate with differences in
English across these communities. As for including speakers with more diverse educational, regional, and socioeconomic backgrounds, it has been well
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documented that those who are minorities in some way but have extensive and continued participation in the majority world will exhibit linguistic features similar to the minority language variety (Fought 2003).
Next, there are a number of ways in which the recording procedures could be improved upon to elicit more natural data. All recordings were completed in a sound-treated booth in a university setting with participants wearing a head- mounted microphone. Each of these factors, from the university setting to the sound-treated room to the microphone that must be affixed to one’s head, can add to a participant’s anxiety. The clinical university setting may also lead to an unconscious choice to use a more standard language variety. In this study, I was the only researcher interacting with participants; it is possible that my speech could influence someone to make certain linguistic accommodations. The fact that such gender and ethnicity differences were still found in a university laboratory setting with reading activities underscores that these differences are very real and pervasive. Nonetheless, it would be wise to have facilitators from the community interact with participants who share more background, ethnicity, and therefore most likely more linguistic similarities (Hay, Drager, & Warren
2009; Fought 2013).
In regards to the experiment design, all recordings were made from participants reading either short stories or carrier phrases that included carefully- selected lexical items from a word list. This word list was made up of words that fit into one of three phonetic environments – bVt, bVd, bVn. These very limited
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phonetic environments control for vowel formants being more affected by their surrounding sounds, thereby making analysis easier for the researcher.
Unfortunately, this means that only part of the overall picture of vowel patterning is apparent. Roeder (2009) provides a list of phonetic environments ranked in terms of how much disruption each environment causes the BAT vowel. While some phonetic environments make analysis much more difficult, it is still of value and necessary to establish the overall distribution of a particular vowel or vowel system. For example, some of the words included in the short stories, but not used for actual data collection, elicited very innovative vowel productions. More research into post-lateral /ae/ (as in black) and other pre-nasal /ae/ environments
(as in family, gamble) could shine light on other unique qualities of Chicano
English in Albuquerque. Anecdotally, it seems that vowels preceding an /l/ are more greatly affected for Hispanic speakers than Anglos, such that the word
FELL is produced with a vowel more similar to BAT than BET, a feature identified by as characteristic of Chicano English (Penfield & Ornstein-Galicia 1985;
Hernandez 1993; Williams 2010). In addition, many participants in both the Anglo and Hispanic groups produced the consonant cluster /nj/ in the word new. This is an interesting topic that also deserves more consideration. Lastly, the BAG class of vowels is raised by some speakers in New Mexico. A better understanding of local productions of this class of vowels, and pre-velar vowels in general, could be compared with findings from other states in the West where such raising has also been reported (Holland & Brandenburg, in press; Wassink 2016).
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The controlled experience for the reading activities is advantageous in ensuring a high-quality, clean recording, and in controlling for a number of potentially confounding variables while simultaneously creating a set of recordings that is consistent across speakers. However, it is also known that this methodology can cause a person to inadvertently use a more standard language variety. Further, a speaker’s reading level and comfort with reading aloud may influence their performance. In future work, more naturalistic data would be recommended. A sociolinguistic interview, for example, would produce not only more naturally-produced data but would deliver a larger set of phonetic environments surrounding the vowels in question. I expect that more naturally acquired data would highlight the differences between Chicano English and
Anglo English in Albuquerque. Such data could also be used for a wider variety of sociophonetic investigations.
This experiment looked at just some of the facets of vowels; namely, F1,
F2 and for diphthongs, Euclidean Distance as well. There are a number of other measures that could be investigated for vowels, among which duration would be wise to study. Konopka (2011) offers a variety of ways in which to study vowel differences related to duration and distance.
Finally, more and more sociophonetic studies include a perceptual component in addition to studying production. It would be very interesting to learn what dimensions are used to assess an individual as sounding New Mexican,
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Hispanic, etc. Some work is currently underway that explores New Mexicans’ perceptions of local speech (Koops and Wilson 2016).
5.3 Future Work
Future work on English in New Mexico should learn from and build upon the limitations considered above. Most importantly, this would include a larger set of participants with more diverse educational and socioeconomic backgrounds from across the state participating in studies from which natural data would be observed and a greater breadth of phonetic environments would be evaluated.
While this dissertation has considered the English in New Mexico as produced by Anglo and Hispanic inhabitants, there is a realm of possibilities for phonetic and phonological analyses of English in New Mexico. I see four broad questions that stand out clearly as important.
First, as has been mentioned throughout this work, there is the question of viewing New Mexico as a monolithic whole versus separating it into regions with distinct patterns of variation. There exist a number of key differences between the north and south in New Mexico, including but not limited to the very different varieties of Spanish and different histories of contact between Spanish and
English. If the Spanish dialects of these two areas are so markedly different from one another in all linguistic domains, from phonetically to lexically to syntactically, as described in Bills & Vigil (2008), it would make sense that the English varieties that live alongside Spanish in these communities would also be markedly different in all linguistic aspects. At the same time, Bills and Vigil (2008) note the
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rapidly changing landscape for Spanish across the state, such that Mexican
Spanish may be overtaking Traditional New Mexican Spanish. Recent census data speak to this changing landscape: of the nearly 158,000 foreign-born Latin-
Americans residing within the state in 2010, 45% live in the southern half of the state, and 55% live in the northern half of the state (US Census 2010). While obviously not all Latin Americans living in New Mexico are from Mexico, the majority undoubtedly are, primarily from the northern Mexican state of
Chihuahua. A better understanding of immigration and language patterns throughout the New Mexico, as opposed to an overgeneralized (and perhaps incorrect) belief that the Spanish variety of the north and that of the south are so distinct from one another, is crucial for future linguistic works. Similarly, the theme of urban versus rural spaces was crucial to the history of English in New
Mexico and the shift in the state from Spanish to English. This is still an important factor today and must be accounted for when researching current linguistic variation in New Mexico.
The second large question relates to the inclusion and position of New
Mexico in larger regionally-based descriptions of the United States. As discussed earlier, there is a portion of southeastern New Mexico not within the bounds of
The West as defined by the Atlas of North American English (ANAE) (Labov,
Ash, & Boberg, 2006). In the ANAE, the borderline for the West appears to cut directly through Las Cruces, the second largest city in New Mexico. This begs the question of whether or not speakers in Las Cruces pattern more like the West
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or Texas. This question, as with the first, could be best answered by including a variety of speakers from across the state.
Third, it is also still unclear the influence of Spanish on the English of New
Mexico. This study only considered how the local varieties of English interact with each other. In chapter 4, I addressed the possibility that Chicano English may be reinforcing the conservative, non-CVS vowels of Anglo men because the characteristics of Chicano English produce much the same results as maintaining local speech norms here. Even that is only a working theory at best; as this study did not look at Spanish, I am hesitant to make any assumptions on the influence of Spanish on English in New Mexico. I am more confident in proposing that
Chicano English has a stronger influence on Anglo English in New Mexico than elsewhere in the US. Hispanics in New Mexico are not a minority group in the same way as in other parts of the country, and the lack of CVS features found in
Anglo vowels here may be influenced by Chicano English. In any case, more work is needed to better understand the influences that Spanish, Chicano
English, and Anglo English have on one another.
Finally, while this study has investigated English in the two largest ethnic populations in the state, Hispanics and Anglos, these are not the only ethnicities in New Mexico. The third largest population is that of Native Americans, who make up 8.5% of the state’s population (American Fact Finder 1-Year Estimates), in contrast to the US overall, where they make up just 0.8% of the total population. Leap (1993) offers an introduction to Native American English across
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North America, yet there has not been a comprehensive study of the characteristics of this language variety in New Mexico. While this dissertation, in particular Chapter 1, highlighted the unique historical and linguistic characteristics of New Mexico, it was framed exclusively in terms of Anglos and
Hispanics. The historical and linguistic record of Native Americans in this state is much longer that of either of these groups, and even less work on American
Indian English in New Mexico has been done than on other forms of English in this state.
5.4 Closing Comments
This final chapter has offered a summary of my findings situated within
New Mexico as well as in comparison with other bodies of research across the country. Limitations were discussed and recommendations of possible solutions were offered when possible. These suggestions are given in hopes that the work on the Englishes of New Mexico has only just begun.
In conclusion, this study has identified and highlighted some of the vocalic differences between English speakers in New Mexico that self-identify as Anglo versus those that self-identify as Hispanic. Both the Anglo and Hispanic data were evaluated in terms of participation (or lack thereof) in the California Vowel
Shift and as a Labovian Western State. The findings from the Hispanic group were additionally compared with other studies on Chicano English from across the United States. In terms of commonality, the one feature that all participants in this study share is a merged BOT/BOUGHT space, as would be expected for a
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Western state (Labov 2001; Labov, Ash, & Boberg 2006). The overall findings additionally support that Anglo women in New Mexico are participating in the majority of the shifts involved in the California Vowel Shift, and Hispanic women are also producing vowels which show advancement of this shift. Anglo men show variable participation in the shifts of the CVS. The fact that Hispanic women
(and not Hispanic men) are patterning in the same direction as the Anglos, particularly Anglo women, supports that the CVS is Anglo-driven. On the other hand, the fact that Anglo and Hispanic women pattern so similarly in terms of
CVS advancement suggests the possibility of an overall gender effect for the
CVS in New Mexico. At the same time, Hispanic men and women alike also demonstrate some of the most common traits of Chicano English, such as lack of
BAN-raising. It will be interesting to see the advancement of CVS in New Mexico in terms of how far speakers progress in the shifts and which speakers (men, women, Hispanic, Anglo) do so. At present, it is not surprising that New Mexico shows less advancement in CVS than do some of our neighbors, such as
Colorado (Holland & Brandenburg, in press). In the land of the mañana attitude, its inhabitants indeed take that approach with their language shifts as well: they are participating, but in no real hurry.
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Appendices
Appendix A: Questionnaire ...... Error! Bookmark not defined.
Appendix B: Reading passages ...... Error! Bookmark not defined.
Appendix C: Carrier phrases ...... Error! Bookmark not defined.
Appendix D: Picture description task...... Error! Bookmark not defined.
Appendix E: Raw and normalized formant values Error! Bookmark not defined.
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Appendix A: Questionnaire
Questionnaire Participant code:______
Gender: Male Female
Are you from New Mexico? YES NO
If yes, which part? ______
If you are from Albuquerque, which high school did you go to? ______
Have you lived anywhere outside of New Mexico? If so, please list where and for how long.
What do you identify as ethnically? Circle all that apply
White/Anglo Black Native American Asian Hispanic- Anglo
Hispanic Chicano/a Hispano/a Latino/a Mexicano/a
Mexican-American Spanish- American Afro-Latino
Coyotito Other: ______
Where are your parents from?
Mother- Father-
What kind of work do they do? Mother- Father-
Rate the languages that your parents speak- circle your answers: Mother: English only English and some Spanish English and Spanish equally Spanish and some English Spanish only
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Father: English only English and some Spanish English and Spanish equally Spanish and some English Spanish only
Do your parents use any other languages? If yes, please list here: Mother-
Father-
Where are your grandparents from? Mother's side: your grandmother- your grandfather-
Father's side: your grandmother- your grandfather-
Rate the languages that your grandparents speak- circle your answer: English only English and some Spanish English and Spanish equally Spanish and some English Spanish only
What was your first language? English Spanish Both
How would you rate your Spanish? Circle one answer in each row.
Listening: Excellent Very good Good Fair Poor Speaking: Excellent Very good Good Fair Poor Reading: Excellent Very good Good Fair Poor Writing: Excellent Very good Good Fair Poor
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When do you speak in Spanish? Check one box in each row. Always Often Sometimes Seldom Never N/A With mother With father With grandparents With other relatives With >1 friend At work At church At school Other: (please specify)
Who addresses you in Spanish? Check one box in each row. Always Often Sometimes Seldom Never N/A Mother Father Grandparents Other relatives Friends At work At church At school Other: (please specify)
Do you listen to conversations between the following people in Spanish? Check one box in each row. Always Often Sometimes Seldom Never N/A Parents Grandparents Other relatives Friends At work At church At school Other: (please specify)
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As a child, who did you speak Spanish with? Check one box in each row. Always Often Sometimes Seldom Never N/A Mother Father Grandparents Other relatives Friends At church At school Other: (please specify)
Do you attend functions where the main language is Spanish?
N/A Always Often Sometimes Seldom Never
Do you watch TV in Spanish?
N/A Always Often Sometimes Seldom Never
Do you listen to Spanish radio?
N/A Always Often Sometimes Seldom Never
Do your parents encourage you to speak Spanish?
N/A Always Often Sometimes Seldom Never
I can make small-talk in Spanish:
N/A Always Often Sometimes Seldom Never
What Spanish classes have you taken at UNM? Please list the class numbers.
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Appendix B: Reading passages
1. A long, long time ago, there was a small girl named Wendy. She was only interested in drinking coffee! Most girls play with dolls, and others played kickball, but Wendy refused. Sometimes her mom or dad would get upset that she had drunk all the coffee in the house, and left none for them. But when Wendy grew up, she became a famous millionaire- she had her own coffee company and every cup of coffee had her face on it. After that, her mom and dad didn’t care if there wasn’t any coffee in the house.
2. Once upon a time there was a boy named Burt and he loved to play outside. His parents didn’t play sports, but they always bought him new baseball equipment for Christmas including a ball, a bat, and a glove. Sometimes Burt had good baseball dreams, dreaming about when his little league team beat the Chicago Cubs. Other times, he would have scary nightmares about running towards a base, and falling on his butt in front of everyone! Then he would dream that the crowd boo’ed him. His biggest fear, though, was about breaking a bone and not being able to play baseball anymore! If that happened, his mom would probably make him stay in bed all day long.
3. Burt had a brother named Ben and they couldn’t have been more opposite! Ben liked to spend his time in the garden and kitchen. He liked to take care of plants, such as carrots, beans, and tomatoes. He enjoyed seeing the new plants and buds come up. He liked to bake too- everything from cakes to buns to cookies. One time he wasn’t paying attention, and he burnt an entire batch of cookies! He had been distracted by a beautiful bird sitting on the window ledge. The cookies were black, but Burt decided to try them anyways. When he bit into the cookie, he knew that they were totally bad right away. He quickly washed it down with an entire bottle of water and promised to be more careful next time!
4. The brother that most people forget about was named Boyde. He loved school and studied really hard. His school stuff was always organized in folders and big, big,
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binders. He knew many things that his brothers didn't. For instance, the past tense of bid was bade. He knew lots about non-school stuff too- like the fact that hotdogs are a good bait for fish. One time, in fact, a shark fell for the hotdog trick, but instead of just getting the hotdog, he got the fishing rod in his bite, too! Even though Boyde knew lots of neat things, his brothers always picked on him- they were the bane of his existance. He tried to get along with them, and talk to them, but he never knew what to talk about. He wasn't good at boytalk. Sometimes he said things incorrectly too- one time he meant to say point but accidentally said boint instead. His brothers laughed- they just didn't respect him. So, he decided to bide his time- he knew that one day things would change. Finally, that day came when he and his brothers met the emperor of Japan. His brothers bounced while Boyde bowed properly to the emperor. Since that day, his brothers have been much nicer to him.
5. The final brother was named Boone and he sure was a trouble maker. He liked to gamble and stay out too late. One time he made a big bet and lost, and he had to give up the family dog! Another time, he placed too many bids at an auction, and he didn’t have enough money! To escape trouble that time, he ran away and hid in a garbage bin behind his parents’ house. He was afraid that he would be found by following his shoeprints, so he took off his boots ,threw them in a bonfire, and ran to hide in just his socks! Sometimes, though, Boone had good luck. One time, he won a beautiful new boat and another time, he won a bag of rubies, beads, and gold. But his parents didn’t care about the boat or the jewels. These bad behaviors did not bode well for Boone. Once his parents found out about all of this, Boone was banned from leaving the house!
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Appendix C: Carrier phrases
Read the following sentences out-loud. Please pause between lines.
1) Bead. I am saying “bead” again.
2) Bid. I am saying “bid” again.
3) Bed. I am saying “bed” again.
4) Bad. I am saying “bad” again.
5) Bottle. I am saying “bottle” again.
6) Bode. I am saying “bode” again.
7) Boo'ed. I am saying “boo'ed” again.
8) Bud. I am saying “bud” again.
9) Bade. I am saying “bade” again.
10) Bide. I am saying “bide” again.
11) Boyde. I am saying “Boyde” again.
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Appendix D: Picture description task
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Appendix E: Raw and normalized formant values
Raw formant values Normalized formant values (z-scores) F1 onset F2 onset F1 F2 F1 onset F2 onset F1 F2 Speaker Vowel Context or nucleus or nucleus glide glide or nucleus or nucleus glide glide HispMale1 BURT BURT 512.8 1220.9 -0.107 -0.591 HispMale1 BOT BOUGHT 671.7 1035.7 1.214 -1.011 HispMale1 BAT BAT 704.3 1528.3 1.486 0.107 HispMale1 BEAT BEAT 320.3 2125.9 -1.707 1.464 HispMale1 BUTT BUTT 582.2 1157.5 0.47 -0.735 HispMale1 BET BED 516.7 1695.9 -0.074 0.488 HispMale1 BET BEN 635 1647.6 0.909 0.378 HispMale1 BEAT BEANS 371.4 2204.5 -1.282 1.642 HispMale1 BUTT BUDS 567.7 1208.5 0.35 -0.619 HispMale1 BUTT BUNS 608.8 1113.8 0.691 -0.834 HispMale1 BURT BURNT 508 1260.9 -0.147 -0.5 HispMale1 BURT BIRD 535.6 1108.3 0.083 -0.846 HispMale1 BIT BIT 490.2 1887.1 -0.295 0.922 HispMale1 BAT BAD 673.1 1530.4 1.226 0.112 HispMale1 BOT BOTTLE 636.6 988.2 0.923 -1.119 HispMale1 BIT BID 470.2 1840.8 -0.461 0.817 HispMale1 BOOT BOONE 343 772.8 -1.519 -1.608 HispMale1 BIT BIDS 477.9 1810.9 -0.397 0.749 HispMale1 BIT BIN 503.4 1620 -0.185 0.315 HispMale1 BOOT BOOTS 334 935 -1.593 -1.24 HispMale1 BOT BONFIRE 693.7 1010.7 1.397 -1.068 HispMale1 BEAT BEADS 289.9 2266.7 -1.96 1.783 HispMale1 BAT BAD 648 1501.3 1.017 0.046 HispMale1 BAN BANNED 705.4 1676.4 1.495 0.443 HispMale1 BEAT BEAD 313.3 2287.2 -1.765 1.83 HispMale1 BEAT BEAD 279.9 2274.8 -2.043 1.802 HispMale1 BIT BID 508 1890.7 -0.147 0.93 HispMale1 BIT BID 482.3 1739.2 -0.36 0.586 HispMale1 BET BED 530 1732.4 0.036 0.57 HispMale1 BET BED 525 1739.5 -0.005 0.587 HispMale1 BAT BAD 716.2 1569.2 1.584 0.2 HispMale1 BAT BAD 664.9 1564.5 1.158 0.189 HispMale1 BOT BOTTLE 661.1 1002.8 1.126 -1.086 HispMale1 BOT BOTTLE 638.5 1039.6 0.938 -1.002 HispMale1 BUTT BUD 563.5 1222.4 0.315 -0.587 HispMale1 BUTT BUD 544.5 1276.3 0.157 -0.465 HispMale1 BURT BURT 506.4 1196.7 -0.16 -0.646 HispMale1 BOT BOUGHT 695.9 1040.4 1.416 -1 HispMale1 BAT BAT 690.9 1507 1.374 0.059 HispMale1 BEAT BEAT 293.6 2240.7 -1.929 1.724 HispMale1 BUTT BUTT 636.9 1190.7 0.925 -0.659 HispMale1 BET BED 539.1 1758.3 0.112 0.629 HispMale1 BET BEN 667.3 1752.3 1.178 0.616 HispMale1 BEAT BEANS 424 2238.1 -0.845 1.718 HispMale1 BUTT BUDS 521.6 1176.2 -0.034 -0.692 HispMale1 BUTT BUNS 579.2 1089.3 0.445 -0.889 HispMale1 BURT BURNT 524.3 1205.4 -0.011 -0.626 HispMale1 BURT BIRD 470.1 1164.8 -0.462 -0.718 HispMale1 BIT BIT 446 1802.3 -0.662 0.729 HispMale1 BAT BAD 657.2 1489 1.094 0.018 HispMale1 BOT BOTTLE 641.2 1049.7 0.961 -0.979 HispMale1 BIT BID 494.4 1878.3 -0.26 0.902 HispMale1 BOOT BOONE 370.9 707.4 -1.287 -1.756 HispMale1 BET BET 568.3 1704 0.355 0.506 HispMale1 BIT BIDS 475.1 1943.4 -0.42 1.049 HispMale1 BIT BIN 485.9 1653 -0.33 0.39 HispMale1 BOOT BOOTS 351.2 903.3 -1.45 -1.312 HispMale1 BOT BONFIRE 679.5 1001.9 1.279 -1.088 HispMale1 BEAT BEADS 300.6 2245.8 -1.871 1.736
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HispMale1 BAT BAD 704.1 1696.1 1.484 0.488 HispMale1 BOOT BOONE 378.2 728.8 -1.226 -1.708 HispMale1 BAN BANNED 678.3 1673.8 1.269 0.437 HispMale1 BEAT BEAD 388.9 2231.9 -1.137 1.704 HispMale1 BEAT BEAD 312.8 2268.6 -1.77 1.788 HispMale1 BIT BID 487.3 1839.6 -0.319 0.814 HispMale1 BIT BID 462.9 1758 -0.522 0.629 HispMale1 BET BED 531.6 1783.6 0.05 0.687 HispMale1 BET BED 571.7 1708.2 0.383 0.516 HispMale1 BAT BAD 720.6 1714.5 1.621 0.53 HispMale1 BAT BAD 683.6 1570.4 1.313 0.203 HispMale1 BOT BOTTLE 666.6 1061.1 1.172 -0.953 HispMale1 BOT BOTTLE 681.4 1073.4 1.295 -0.926 HispMale1 BUTT BUD 590.2 1267.3 0.537 -0.485 HispMale1 BUTT BUD 564.5 1228.9 0.323 -0.573 HispMale1 BOY BOYDE 440.1 747.8 414.9 1601.2 -0.711 -1.665 -0.921 0.273 HispMale1 BAIT BADE 452.9 1829 375.6 2090 -0.605 0.79 -1.247 1.382 HispMale1 BAIT BAIT 460.1 1780.1 373.2 2062.1 -0.545 0.679 -1.267 1.319 HispMale1 BITE BITE 648 1234.9 401.6 1947.2 1.017 -0.559 -1.031 1.058 HispMale1 BITE BIDE 668 1181.6 528.4 1712 1.184 -0.68 0.023 0.524 HispMale1 BOUT BOWED 730.1 1192.9 491.7 921.9 1.7 -0.654 -0.282 -1.269 HispMale1 BOAT BOAT 465.5 870.3 393.6 850 -0.5 -1.387 -1.098 -1.433 HispMale1 BOAT BODE 508.5 963.4 433.6 897.9 -0.142 -1.175 -0.765 -1.324 HispMale1 BOAT BODE 504.1 959.6 429.8 934.9 -0.179 -1.184 -0.797 -1.24 HispMale1 BOAT BODE 500.6 976.1 461.3 1036 -0.208 -1.146 -0.535 -1.01 HispMale1 BAIT BADE 479.2 1929.9 349.2 2184.7 -0.386 1.019 -1.467 1.597 HispMale1 BAIT BADE 448.8 1891.3 387.6 2091.7 -0.639 0.931 -1.148 1.386 HispMale1 BITE BIDE 702.5 1312.1 455 1892.6 1.471 -0.384 -0.587 0.934 HispMale1 BITE BIDE 635.6 1348.4 572.9 1712.5 0.914 -0.301 0.393 0.525 HispMale1 BOY BOYDE 472.8 806.6 435.6 1596.2 -0.439 -1.531 -0.749 0.261 HispMale1 BOY BOYDE 463.1 755 459.6 1475.7 -0.52 -1.648 -0.549 -0.012 HispMale1 BOUT BOWED 705.3 1246.2 494.4 926.4 1.494 -0.533 -0.26 -1.259 HispMale1 BOUT BOWED 650.4 1242.2 563.3 1129.8 1.037 -0.542 0.313 -0.797 HispMale1 BOY BOYDE 464.2 692.4 429.2 1623.3 -0.511 -1.79 -0.802 0.323 HispMale1 BAIT BADE 474.4 1877 360.3 2087.4 -0.426 0.899 -1.375 1.376 HispMale1 BAIT BAIT 489.1 1855.8 341.2 2180.5 -0.304 0.851 -1.533 1.588 HispMale1 BITE BITE 618.7 1236.1 452.9 1751.6 0.774 -0.556 -0.605 0.614 HispMale1 BITE BIDE 687.9 1221.8 487.8 1777.2 1.349 -0.589 -0.315 0.672 HispMale1 BOAT BOAT 508 1009.2 388.1 896.1 -0.147 -1.071 -1.144 -1.328 HispMale1 BOAT BODE 470.3 837.6 445.6 952.1 -0.46 -1.461 -0.665 -1.201 HispMale1 BAIT BADE 517.8 1858.8 383.6 2158 -0.065 0.857 -1.181 1.537 HispMale1 BAIT BADE 483.2 1909.1 404.9 2167.5 -0.353 0.972 -1.004 1.558 HispMale1 BITE BIDE 723.4 1266.9 464 1902.4 1.644 -0.486 -0.512 0.956 HispMale1 BITE BIDE 692.2 1281.5 543.6 1766.2 1.385 -0.453 0.149 0.647 HispMale1 BOY BOYDE 495.9 739.9 461.8 1522.8 -0.247 -1.683 -0.531 0.095 HispMale1 BOY BOYDE 498 862 443.5 1535 -0.23 -1.405 -0.683 0.122 HispMale1 BOUT BOWED 730.9 1269.3 480.3 916.3 1.707 -0.481 -0.377 -1.282 HispMale1 BOUT BOWED 680.4 1333.4 568.8 1079.9 1.287 -0.335 0.359 -0.911 HispMale2 BUTT BUTT 621.7 1302.7 0.594 -0.639 HispMale2 BET BEN 525.8 1767.6 -0.049 0.428 HispMale2 BIT BIN 605.4 1902.7 0.485 0.738 HispMale2 BET BEN 600.2 1804 0.45 0.511 HispMale2 BEAT BEAD 260.3 2365.4 -1.827 1.8 HispMale2 BIT BID 450.6 1902.6 -0.552 0.738 HispMale2 BAT BAD 745.6 1738.8 1.423 0.362 HispMale2 BUTT BUD 569.7 1240.5 0.245 -0.782 HispMale2 BURT BURT 470.7 1364.2 -0.418 -0.498 HispMale2 BOT BOUGHT 703.5 1146.7 1.142 -0.997 HispMale2 BAT BAT 796.8 1616.9 1.766 0.082 HispMale2 BEAT BEAT 269.2 2323.5 -1.767 1.704 HispMale2 BET BED 568.8 1796.2 0.239 0.494 HispMale2 BEAT BEANS 311 2607.4 -1.487 2.355 HispMale2 BUTT BUDS 519 1214.4 -0.094 -0.842 HispMale2 BUTT BUNS 594.7 1244.6 0.413 -0.772 HispMale2 BURT BURNT 478.1 1387.2 -0.368 -0.445 HispMale2 BURT BIRD 436.2 1463.4 -0.649 -0.27 HispMale2 BIT BIT 460.8 2009.7 -0.484 0.984
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HispMale2 BAT BAD 746.9 1667.9 1.432 0.199 HispMale2 BOT BOTTLE 654 946.3 0.81 -1.457 HispMale2 BIT BID 452.6 1975.8 -0.539 0.906 HispMale2 BOOT BOONE 327.3 1122.3 -1.378 -1.053 HispMale2 BET BET 605 1862.1 0.482 0.645 HispMale2 BIT BIDS 447.3 1969.7 -0.574 0.892 HispMale2 BOOT BOOTS 354.7 1294.2 -1.194 -0.658 HispMale2 BOT BONFIRE 771.5 1073.3 1.597 -1.165 HispMale2 BEAT BEADS 271.8 2321.5 -1.75 1.699 HispMale2 BAT BAD 717.9 1620.9 1.238 0.091 HispMale2 BAN BANNED 817.3 1619.1 1.904 0.087 HispMale2 BEAT BEAD 261.4 2322.2 -1.819 1.701 HispMale2 BEAT BEAD 257.5 2318.8 -1.845 1.693 HispMale2 BIT BID 475.1 2009.4 -0.388 0.983 HispMale2 BIT BID 449 1925.8 -0.563 0.791 HispMale2 BET BED 609.6 1806.7 0.513 0.518 HispMale2 BET BED 582.5 1911.5 0.331 0.758 HispMale2 BAT BAD 751.8 1601.4 1.465 0.047 HispMale2 BAT BAD 810.7 1785.5 1.859 0.469 HispMale2 BOT BOTTLE 721.5 1059.6 1.262 -1.197 HispMale2 BOT BOTTLE 705.5 1031.2 1.155 -1.262 HispMale2 BUTT BUD 614.2 1345.3 0.543 -0.541 HispMale2 BUTT BUD 607 1285.1 0.495 -0.679 HispMale2 BURT BURT 441.6 1359.4 -0.612 -0.509 HispMale2 BOT BOUGHT 650.7 1084.7 0.788 -1.139 HispMale2 BAT BAT 712.5 1628.7 1.202 0.109 HispMale2 BEAT BEAT 273.4 2273.2 -1.739 1.588 HispMale2 BUTT BUTT 572.1 1230.4 0.262 -0.805 HispMale2 BET BED 621.3 1809.1 0.591 0.523 HispMale2 BEAT BEANS 291.9 2188.5 -1.615 1.394 HispMale2 BUTT BUDS 575.2 1287.8 0.282 -0.673 HispMale2 BUTT BUNS 569.6 1205.9 0.245 -0.861 HispMale2 BURT BURNT 527.6 1406.5 -0.036 -0.401 HispMale2 BURT BIRD 481.5 1545.2 -0.345 -0.082 HispMale2 BIT BIT 487.5 1965.2 -0.305 0.881 HispMale2 BAT BAD 729.3 1497.9 1.314 -0.191 HispMale2 BOT BOTTLE 675.2 999.4 0.952 -1.335 HispMale2 BIT BID 457.9 1841.8 -0.503 0.598 HispMale2 BOOT BOONE 348.5 1098.3 -1.236 -1.108 HispMale2 BET BET 594.3 1846.7 0.41 0.609 HispMale2 BIT BIDS 454.2 1944.1 -0.528 0.833 HispMale2 BIT BIN 421.4 1884.8 -0.748 0.697 HispMale2 BOOT BOOTS 348.6 1320.5 -1.235 -0.598 HispMale2 BOT BONFIRE 709.5 1064.5 1.182 -1.186 HispMale2 BEAT BEADS 283.2 2306.1 -1.673 1.664 HispMale2 BAT BAD 644.4 1587 0.746 0.013 HispMale2 BAN BANNED 821.8 1611.9 1.934 0.071 HispMale2 BEAT BEAD 250.6 2349.3 -1.892 1.763 HispMale2 BIT BID 469.3 1963.1 -0.427 0.877 HispMale2 BET BED 626.7 1779.9 0.627 0.456 HispMale2 BET BED 584.7 1711.5 0.346 0.299 HispMale2 BAT BAD 731.8 1657.7 1.331 0.176 HispMale2 BOT BOTTLE 636.9 1041.1 0.695 -1.239 HispMale2 BOT BOTTLE 593.1 917.9 0.402 -1.522 HispMale2 BUTT BUD 574.1 1255.1 0.275 -0.748 HispMale2 BITE BIDE 708.7 1184.5 485.4 1846.7 1.176 -0.91 -0.319 0.609 HispMale2 BAIT BADE 478.7 1900 344.4 2343.8 -0.364 0.732 -1.263 1.75 HispMale2 BOY BOYDE 484.8 809.7 392.7 1903.7 -0.323 -1.77 -0.94 0.74 HispMale2 BITE BIDE 742.2 1275.6 423.7 1814.7 1.401 -0.701 -0.732 0.536 HispMale2 BOY BOYDE 472.2 992.3 355.3 2023.5 -0.407 -1.351 -1.19 1.015 HispMale2 BOY BOYDE 476.7 784.7 460.4 1661.2 -0.377 -1.828 -0.487 0.184 HispMale2 BAIT BADE 466.4 1994 297.2 2309.1 -0.446 0.948 -1.579 1.671 HispMale2 BAIT BAIT 439.7 2071.3 320.1 2089.5 -0.625 1.125 -1.426 1.167 HispMale2 BITE BITE 678.1 1171.8 425.6 1957.6 0.971 -0.939 -0.72 0.864 HispMale2 BOUT BOWED 680.4 1545.9 597.2 1108.9 0.987 -0.081 0.43 -1.084 HispMale2 BOAT BOAT 548.7 1110.5 488.7 985.8 0.105 -1.08 -0.297 -1.366 HispMale2 BOAT BODE 466.5 1012.9 378 990.7 -0.446 -1.304 -1.038 -1.355
140
HispMale2 BOAT BODE 526.8 1088.8 447.2 1068.7 -0.042 -1.13 -0.575 -1.176 HispMale2 BOAT BODE 502.4 1083.2 424.1 1073.3 -0.205 -1.143 -0.73 -1.165 HispMale2 BAIT BADE 438.8 2129.7 323.5 2189.2 -0.631 1.259 -1.403 1.395 HispMale2 BITE BIDE 724.8 1191.2 533.2 1758.9 1.284 -0.895 0.001 0.408 HispMale2 BITE BIDE 725.4 1313.8 570.3 1689 1.288 -0.613 0.249 0.248 HispMale2 BOY BOYDE 473.2 826.1 476.4 1770.6 -0.401 -1.733 -0.379 0.435 HispMale2 BOY BOYDE 523.9 872.3 464.1 1631.5 -0.061 -1.627 -0.462 0.116 HispMale2 BOUT BOWED 807.2 1615.8 503.1 1025.6 1.836 0.08 -0.201 -1.275 HispMale2 BOUT BOWED 748.6 1641.4 617 1220.8 1.444 0.138 0.562 -0.827 HispMale2 BAIT BADE 500.1 1963.3 356.4 2122.1 -0.221 0.877 -1.183 1.241 HispMale2 BAIT BAIT 406.9 1991.5 324.3 2306.4 -0.845 0.942 -1.398 1.664 HispMale2 BITE BITE 670.6 1124.7 561.8 1684 0.921 -1.047 0.193 0.236 HispMale2 BOUT BOWED 756.3 1546.1 558.8 1080.1 1.495 -0.08 0.172 -1.15 HispMale2 BOAT BOAT 537.6 1010.8 478.2 923.8 0.03 -1.309 -0.367 -1.508 HispMale2 BOAT BODE 463.9 906.7 424.6 1000.8 -0.463 -1.548 -0.726 -1.332 HispMale2 BOAT BODE 563.4 1149.6 438 1049.3 0.203 -0.99 -0.637 -1.22 HispMale2 BOAT BODE 421.8 1034.4 378.1 1052.8 -0.745 -1.255 -1.038 -1.212 HispMale2 BAIT BADE 486.6 1929.1 306.3 2161 -0.311 0.799 -1.518 1.331 HispMale2 BAIT BADE 453.8 2018.4 350.9 2192.6 -0.531 1.003 -1.22 1.403 HispMale2 BITE BIDE 740.7 1196.1 523.3 1782 1.391 -0.884 -0.065 0.461 HispMale2 BITE BIDE 675.4 1278.3 542.3 1762 0.953 -0.695 0.062 0.415 HispMale2 BOY BOYDE 441.3 790 427.5 1638 -0.614 -1.816 -0.707 0.131 HispMale2 BOUT BOWED 769.2 1614.7 666.7 1244.6 1.581 0.077 0.895 -0.772 HispMale2 BOUT BOWED 685 1518.3 597.5 1222.4 1.018 -0.144 0.432 -0.823 HispMale3 BOT BOTTLE 687.8 1057.5 0.875 -1.279 HispMale3 BIT BIN 495.1 2239.9 -0.408 0.951 HispMale3 BIT BID 447.9 2198.4 -0.723 0.873 HispMale3 BAT BAD 827.4 1788.5 1.805 0.1 HispMale3 BOT BOTTLE 672.1 1034.5 0.77 -1.322 HispMale3 BET BET 579.1 2050.4 0.151 0.594 HispMale3 BAT BAD 723.5 1756.6 1.113 0.04 HispMale3 BIT BID 457.4 2082.8 -0.659 0.655 HispMale3 BIT BID 438.6 2167.1 -0.784 0.814 HispMale3 BURT BURT 517.5 1675.2 -0.259 -0.114 HispMale3 BOT BOUGHT 644.7 1233.1 0.588 -0.947 HispMale3 BAT BAT 797.3 1666.5 1.604 -0.13 HispMale3 BEAT BEAT 291.2 2763.2 -1.766 1.938 HispMale3 BUTT BUTT 599.5 1239.8 0.287 -0.935 HispMale3 BET BED 597.9 1939.2 0.276 0.384 HispMale3 BET BEN 652.7 1999.4 0.641 0.498 HispMale3 BEAT BEANS 395.4 2707.8 -1.072 1.834 HispMale3 BUTT BUDS 592.8 1466.2 0.242 -0.508 HispMale3 BUTT BUNS 626.5 1409.9 0.467 -0.614 HispMale3 BURT BURNT 554.4 1614.5 -0.013 -0.228 HispMale3 BIT BIT 482.6 2135.1 -0.491 0.754 HispMale3 BAT BAD 787.2 1662.5 1.537 -0.138 HispMale3 BIT BID 471 2167.2 -0.569 0.814 HispMale3 BOOT BOONE 382.9 951.6 -1.155 -1.478 HispMale3 BET BET 637 2000.7 0.537 0.5 HispMale3 BIT BIDS 458.3 2147.4 -0.653 0.777 HispMale3 BOOT BOOTS 353.3 1301.5 -1.353 -0.818 HispMale3 BOT BONFIRE 726.5 1069.7 1.133 -1.256 HispMale3 BEAT BEADS 307.1 2665 -1.66 1.753 HispMale3 BAT BAD 771.7 1571 1.434 -0.31 HispMale3 BAN BANNED 833.9 1686.6 1.848 -0.092 HispMale3 BEAT BEAD 311.1 2644.6 -1.634 1.715 HispMale3 BEAT BEAD 290.3 2711.5 -1.772 1.841 HispMale3 BET BED 630.8 1985.5 0.495 0.472 HispMale3 BET BED 621.3 1988.5 0.432 0.477 HispMale3 BAT BAD 884.5 1724.1 2.185 -0.021 HispMale3 BOT BOTTLE 749 1107.8 1.283 -1.184 HispMale3 BUTT BUD 605.2 1445.1 0.325 -0.548 HispMale3 BUTT BUD 658.1 1582.5 0.677 -0.288 HispMale3 BURT BURT 464 1685.3 -0.615 -0.095 HispMale3 BOT BOUGHT 694.8 1187.8 0.922 -1.033 HispMale3 BAT BAT 790.3 1723.8 1.558 -0.022 HispMale3 BEAT BEAT 302.1 2719.1 -1.693 1.855
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HispMale3 BUTT BUTT 594.4 1195 0.253 -1.019 HispMale3 BET BED 602.7 1958.9 0.308 0.421 HispMale3 BET BEN 652.9 2000.2 0.643 0.499 HispMale3 BEAT BEANS 405.1 2594.1 -1.008 1.619 HispMale3 BUTT BUDS 586 1319.2 0.197 -0.785 HispMale3 BUTT BUNS 643.3 1386.1 0.579 -0.659 HispMale3 BURT BURNT 529 1715.3 -0.182 -0.038 HispMale3 BURT BIRD 471.4 1754.8 -0.566 0.037 HispMale3 BIT BIT 466.7 2278 -0.597 1.023 HispMale3 BAT BAD 731.3 1627.9 1.165 -0.203 HispMale3 BOT BOTTLE 625.7 1037.7 0.461 -1.316 HispMale3 BIT BID 453 2101.4 -0.689 0.69 HispMale3 BOOT BOONE 411 1230.8 -0.968 -0.952 HispMale3 BIT BIDS 460.7 2120.4 -0.637 0.726 HispMale3 BIT BIN 482.4 2009.4 -0.493 0.517 HispMale3 BOOT BOOTS 372.9 1416.7 -1.222 -0.601 HispMale3 BOT BONFIRE 698.6 1169.5 0.947 -1.067 HispMale3 BEAT BEADS 263.9 2853.2 -1.948 2.108 HispMale3 BAN BANNED 746.3 1687.7 1.265 -0.09 HispMale3 BEAT BEAD 294 2723.6 -1.747 1.864 HispMale3 BEAT BEAD 319.5 2421.7 -1.578 1.294 HispMale3 BET BED 623.8 1968.7 0.449 0.44 HispMale3 BET BED 627.8 1938 0.475 0.382 HispMale3 BAT BAD 805.5 1745.1 1.659 0.018 HispMale3 BAT BAD 826.1 1837.6 1.796 0.193 HispMale3 BOT BOTTLE 754.1 1130.9 1.317 -1.14 HispMale3 BOT BOTTLE 728.1 1178.1 1.143 -1.051 HispMale3 BUTT BUD 592.4 1354.2 0.24 -0.719 HispMale3 BUTT BUD 609.8 1481.7 0.356 -0.479 HispMale3 BITE BITE 660.5 1088.5 409.3 2271.3 0.693 -1.22 -0.98 1.011 HispMale3 BITE BIDE 770.5 1480.4 523.4 2063 1.426 -0.481 -0.22 0.618 HispMale3 BOY BOYDE 446.5 800.6 430.6 2002.8 -0.732 -1.763 -0.838 0.504 HispMale3 BAIT BADE 451.7 2149.4 404.8 2321.3 -0.697 0.781 -1.01 1.105 HispMale3 BAIT BAIT 422.1 2252.6 359.5 2511.1 -0.894 0.975 -1.311 1.463 HispMale3 BITE BIDE 734.5 1080.3 623.9 2100 1.186 -1.236 0.449 0.688 HispMale3 BOUT BOWED 769.4 1384.7 538 1031.9 1.418 -0.661 -0.123 -1.327 HispMale3 BOAT BOAT 561.8 1062.7 428.5 817.4 0.036 -1.269 -0.852 -1.731 HispMale3 BOAT BODE 524.1 1037 463.2 1091.1 -0.215 -1.317 -0.621 -1.215 HispMale3 BOAT BODE 572.7 1170.9 430.7 1103.6 0.109 -1.065 -0.837 -1.192 HispMale3 BOAT BODE 529.4 1050.8 531.9 1240 -0.18 -1.291 -0.163 -0.934 HispMale3 BAIT BADE 457.2 2388.5 399.1 2403.5 -0.661 1.232 -1.048 1.26 HispMale3 BAIT BADE 452.8 2436.2 430 2389.1 -0.69 1.322 -0.842 1.233 HispMale3 BITE BIDE 773.3 1623.9 569.1 2129.1 1.444 -0.21 0.085 0.742 HispMale3 BOY BOYDE 475.5 845.9 418 2136.7 -0.539 -1.678 -0.922 0.757 HispMale3 BOY BOYDE 467.8 926 448.2 1687.5 -0.59 -1.527 -0.721 -0.09 HispMale3 BOUT BOWED 786.3 1512.7 559.1 1159.1 1.531 -0.42 0.018 -1.087 HispMale3 BOUT BOWED 781.3 1546.1 640.1 1366.1 1.498 -0.357 0.557 -0.697 HispMale3 BOY BOYDE 422.5 781.4 426 1985.8 -0.892 -1.799 -0.868 0.472 HispMale3 BAIT BADE 429 2174.7 367.7 2448.6 -0.848 0.828 -1.257 1.345 HispMale3 BAIT BAIT 413.5 2373.6 366.1 2548 -0.952 1.204 -1.267 1.532 HispMale3 BITE BITE 652.1 1478.3 488.4 2007.8 0.637 -0.485 -0.453 0.514 HispMale3 BOUT BOWED 803.7 1549 539.3 1109.6 1.647 -0.352 -0.114 -1.18 HispMale3 BOAT BOAT 486.2 930.3 411.4 812.2 -0.467 -1.518 -0.966 -1.741 HispMale3 BOAT BODE 506.2 1049.2 446.8 1157 -0.334 -1.294 -0.73 -1.091 HispMale3 BOAT BODE 557.1 1170.1 458.2 1239.7 0.005 -1.066 -0.654 -0.935 HispMale3 BOAT BODE 525.5 1124.2 499 1273.6 -0.206 -1.153 -0.382 -0.871 HispMale3 BAIT BADE 436.7 2332.3 393.5 2455.7 -0.797 1.126 -1.085 1.358 HispMale3 BAIT BADE 438.3 2488.6 394.1 2598.1 -0.786 1.42 -1.081 1.627 HispMale3 BITE BIDE 725.6 1484.1 587.9 2075.2 1.127 -0.474 0.21 0.641 HispMale3 BOY BOYDE 505.3 957.2 437.3 2054.4 -0.34 -1.468 -0.793 0.602 HispMale3 BOY BOYDE 475.1 874.3 463.2 1687.8 -0.541 -1.624 -0.621 -0.09 HispMale3 BOUT BOWED 780.8 1567.6 527.9 1140.2 1.494 -0.317 -0.19 -1.123 HispMale3 BOUT BOWED 773 1636.1 594.5 1307.1 1.442 -0.187 0.254 -0.808 Hispmale4 BEAT BEATS 301 2125.5 -1.557 1.346 Hispmale4 BUTT BUTT 590.6 1342.3 0.269 -0.613 Hispmale4 BET BED 581.6 1671.6 0.212 0.211 Hispmale4 BURT BURT 473.3 1520.8 -0.471 -0.167
142
Hispmale4 BET BEN 618.7 1771.9 0.446 0.461 Hispmale4 BEAT BEANS 362.8 2093.8 -1.167 1.267 Hispmale4 BUTT BUDS 581.7 1453.4 0.213 -0.335 Hispmale4 BUTT BUNS 633.9 1340.6 0.542 -0.617 Hispmale4 BURT BURNT 600.3 1713.4 0.33 0.315 Hispmale4 BURT BIRD 519.1 1554 -0.182 -0.084 Hispmale4 BIT BIT 453.8 1925.3 -0.594 0.845 Hispmale4 BAT BAD 738.7 1542.6 1.202 -0.112 Hispmale4 BOT BOTTLE 707.8 1127.6 1.007 -1.15 Hispmale4 BOOT BOONE 397 1016.3 -0.952 -1.428 Hispmale4 BET BET 602.1 1755.1 0.341 0.419 Hispmale4 BIT BIDS 419.2 1835.6 -0.812 0.621 Hispmale4 BIT BIN 483.6 1916.6 -0.406 0.823 Hispmale4 BOOT BOOTS 324.7 1214.5 -1.408 -0.933 Hispmale4 BOT BONFIRE 757 1111.3 1.318 -1.191 Hispmale4 BEAT BEADS 263.3 2121.1 -1.795 1.335 Hispmale4 BAT BAD 710.3 1534.4 1.023 -0.133 Hispmale4 BAN BANNED 821 1606.7 1.721 0.048 Hispmale4 BEAT BEAD 281.6 2188.1 -1.679 1.502 Hispmale4 BEAT BEAD 283.4 2123.2 -1.668 1.34 Hispmale4 BIT BID 441.8 1974.3 -0.669 0.968 Hispmale4 BIT BID 447.4 1871.8 -0.634 0.711 Hispmale4 BET BED 612.1 1799.6 0.404 0.531 Hispmale4 BET BED 631.4 1732.8 0.526 0.364 Hispmale4 BAT BAD 822.2 1614.2 1.729 0.067 Hispmale4 BAT BAD 793.9 1516 1.55 -0.179 Hispmale4 BOT BOTTLE 703.6 1077.4 0.981 -1.276 Hispmale4 BOT BOTTLE 722.1 1099.8 1.098 -1.22 Hispmale4 BUTT BUD 634.1 1354 0.543 -0.584 Hispmale4 BUTT BUD 612.8 1405.5 0.409 -0.455 Hispmale4 BURT BURT 468.4 1381.7 -0.502 -0.515 Hispmale4 BOT BOUGHT 726 1132.6 1.122 -1.138 Hispmale4 BAT BAT 809.3 1599.2 1.647 0.029 Hispmale4 BEAT BEAT 307.6 2118.6 -1.515 1.329 Hispmale4 BUTT BUTT 619 1430.6 0.448 -0.392 Hispmale4 BET BED 637.9 1881.8 0.567 0.736 Hispmale4 BET BEN 672.3 1823.6 0.784 0.591 Hispmale4 BEAT BEANS 391 2252.6 -0.99 1.664 Hispmale4 BUTT BUD 627.6 1422.6 0.502 -0.412 Hispmale4 BUTT BUNS 644 1334.5 0.605 -0.633 Hispmale4 BURT BURNT 568.1 1539 0.127 -0.121 Hispmale4 BURT BIRD 474.7 1579.8 -0.462 -0.019 Hispmale4 BIT BIT 474.4 1968.7 -0.464 0.954 Hispmale4 BAT BAD 728.9 1672.5 1.14 0.213 Hispmale4 BOT BOTTLE 720.7 1131.9 1.089 -1.139 Hispmale4 BOOT BOONE 374.5 1045.8 -1.094 -1.355 Hispmale4 BET BET 584.8 1810 0.232 0.557 Hispmale4 BIT BIDS 429.2 1865.5 -0.749 0.696 Hispmale4 BIT BIN 486.5 1851.6 -0.388 0.661 Hispmale4 BOOT BOOTS 333.9 1098.9 -1.35 -1.222 Hispmale4 BOT BONFIRE 741.3 1150.2 1.219 -1.094 Hispmale4 BEAT BEADS 289.7 2137.9 -1.628 1.377 Hispmale4 BAT BAD 781.4 1570.6 1.471 -0.042 Hispmale4 BAN BANNED 876.2 1625.2 2.069 0.095 Hispmale4 BEAT BEAD 303.4 2228.7 -1.542 1.604 Hispmale4 BEAT BEAD 296.1 2144.1 -1.588 1.392 Hispmale4 BIT BID 450.4 1961 -0.615 0.934 Hispmale4 BIT BID 463.5 1899.9 -0.533 0.782 Hispmale4 BET BED 589.9 1797.4 0.264 0.525 Hispmale4 BET BED 615.8 1697.6 0.428 0.276 Hispmale4 BAT BAD 837.5 1592.9 1.825 0.014 Hispmale4 BAT BAD 777.6 1536 1.447 -0.129 Hispmale4 BOT BOTTLE 725.2 1103.2 1.117 -1.211 Hispmale4 BOT BOTTLE 729.3 1089.8 1.143 -1.245 Hispmale4 BUTT BUD 621.3 1412.1 0.462 -0.438 Hispmale4 BUTT BUD 601.2 1418 0.335 -0.424 Hispmale4 BOY BOYDE 463.2 829.6 371.7 2082.9 -0.534 -1.895 -1.111 1.239
143
Hispmale4 BAIT BADE 444.8 2035.7 359.7 2114 -0.65 1.121 -1.187 1.317 Hispmale4 BAIT BAIT 443.2 2069 345.3 2298.9 -0.661 1.205 -1.278 1.78 Hispmale4 BITE BITE 732.9 1291.5 503.7 1993.5 1.166 -0.74 -0.279 1.016 Hispmale4 BITE BIDE 721.3 1373.7 458.2 1990.7 1.093 -0.535 -0.566 1.009 Hispmale4 BOAT BOAT 533.2 1025.7 426.3 815.2 -0.093 -1.405 -0.767 -1.931 Hispmale4 BOAT BODE 520 993.1 397.7 1045.4 -0.176 -1.487 -0.947 -1.356 Hispmale4 BOAT BODE 564.3 1124.6 436 1023.5 0.103 -1.158 -0.706 -1.41 Hispmale4 BOAT BODE 520.6 992.8 420.6 1043.7 -0.173 -1.487 -0.803 -1.36 Hispmale4 BAIT BADE 465.1 1971.3 355.1 2186.9 -0.523 0.96 -1.216 1.499 Hispmale4 BAIT BADE 455.3 2012.1 357.3 2104.4 -0.584 1.062 -1.202 1.293 Hispmale4 BOY BOYDE 439.6 770.4 425.5 1522.9 -0.683 -2.044 -0.772 -0.161 Hispmale4 BOY BOYDE 475.5 910.5 424.5 1555.1 -0.457 -1.693 -0.778 -0.081 Hispmale4 BITE BIDE 882.8 1391 392.4 2140.8 2.111 -0.491 -0.981 1.384 Hispmale4 BITE BIDE 769.3 1332.1 490.1 1948.6 1.395 -0.639 -0.365 0.903 Hispmale4 BOY BOYDE 472.2 806.8 419.4 1881.6 -0.478 -1.952 -0.811 0.736 Hispmale4 BAIT BADE 464.8 1995 350 2177.2 -0.524 1.019 -1.248 1.475 Hispmale4 BAIT BAIT 417.1 2093.7 324.8 2267.8 -0.825 1.266 -1.407 1.702 Hispmale4 BITE BITE 710.7 1340.5 449.1 2142.4 1.026 -0.618 -0.623 1.388 Hispmale4 BITE BIDE 820.5 1330.2 407.1 2173.1 1.718 -0.643 -0.888 1.465 Hispmale4 BOUT BOWED 725.9 1226.4 665.3 1098.7 1.122 -0.903 0.74 -1.222 Hispmale4 BOAT BOAT 538.6 1046.4 411.9 822.1 -0.059 -1.353 -0.858 -1.914 Hispmale4 BOAT BODE 583.1 1193.8 450.5 1066.4 0.221 -0.985 -0.615 -1.303 Hispmale4 BOAT BOAT 553.4 1073.3 392.2 859.6 0.034 -1.286 -0.982 -1.82 Hispmale4 BOAT BODE 541.5 1189.7 474.4 957.9 -0.041 -0.995 -0.464 -1.575 Hispmale4 BAIT BADE 445.9 1998.5 365.3 2232.7 -0.644 1.028 -1.152 1.614 Hispmale4 BAIT BADE 460.1 1952.7 382.5 2025.6 -0.554 0.914 -1.043 1.096 Hispmale4 BITE BIDE 742 1313.5 437.7 2046.1 1.223 -0.685 -0.695 1.147 Hispmale4 BITE BIDE 758.4 1352.6 501.5 2087 1.326 -0.587 -0.293 1.25 Hispmale4 BOY BOYDE 496.9 889 406.5 1922.4 -0.322 -1.747 -0.892 0.838 Hispmale4 BOY BOYDE 451.4 939.4 428.6 1478.2 -0.609 -1.621 -0.753 -0.273 Hispmale4 BOUT BOWED 828 1433.7 619.2 1196 1.765 -0.384 0.449 -0.979 Hispmale4 BOUT BOWED 776.1 1434.8 604.1 1258.3 1.438 -0.382 0.354 -0.823 HispFemale1 BURT BURT 602.8 1546.4 -0.309 -0.622 HispFemale1 BOT BOUGHT 912.2 1273.2 1.275 -1.093 HispFemale1 BAT BAT 1003.8 1760.3 1.744 -0.253 HispFemale1 BEAT BEAT 357.3 3051.7 -1.565 1.975 HispFemale1 BUTT BUTT 839.7 1804.3 0.904 -0.177 HispFemale1 BET BED 692.4 2167.8 0.15 0.45 HispFemale1 BET BEN 848.8 2063.4 0.951 0.27 HispFemale1 BEAT BEANS 429.3 2962.4 -1.197 1.821 HispFemale1 BUTT BUDS 753.3 1722 0.462 -0.319 HispFemale1 BUTT BUNS 790.4 1570.1 0.652 -0.581 HispFemale1 BURT BURNT 554.3 1599.8 -0.557 -0.53 HispFemale1 BIT BIT 665 2300.8 0.01 0.68 HispFemale1 BAT BAD 1016.8 1793.5 1.811 -0.195 HispFemale1 BOT BOTTLE 837.5 1258.5 0.893 -1.118 HispFemale1 BIT BID 586.7 2397.6 -0.391 0.847 HispFemale1 BOOT BOONE 409.2 1077.1 -1.3 -1.431 HispFemale1 BET BET 710.3 2177.5 0.242 0.467 HispFemale1 BIT BIDS 545.2 2260.8 -0.603 0.611 HispFemale1 BIT BIN 525.5 2205.6 -0.704 0.516 HispFemale1 BOOT BOOTS 381.6 1343.6 -1.441 -0.972 HispFemale1 BOT BONFIRE 854.2 1218.2 0.978 -1.188 HispFemale1 BEAT BEADS 381.4 2881.7 -1.442 1.682 HispFemale1 BAT BAD 862 1966.3 1.018 0.103 HispFemale1 BAN BANNED 1002.6 1902.6 1.738 -0.007 HispFemale1 BEAT BEAD 437.2 2730.9 -1.156 1.422 HispFemale1 BEAT BEAD 378 2919 -1.459 1.746 HispFemale1 BIT BID 632.2 2446.3 -0.158 0.931 HispFemale1 BIT BID 538.7 2285.8 -0.637 0.654 HispFemale1 BET BED 719.8 2240 0.29 0.575 HispFemale1 BET BED 739.5 2062 0.391 0.268 HispFemale1 BAT BAD 1002.3 1925.4 1.737 0.032 HispFemale1 BAT BAD 949.5 1821.8 1.466 -0.147 HispFemale1 BOT BOTTLE 839.9 1276.6 0.905 -1.087 HispFemale1 BOT BOTTLE 909.1 1266.9 1.259 -1.104 HispFemale1 BUTT BUD 807.3 1874.1 0.738 -0.056
144
HispFemale1 BUTT BUD 750.8 1820.9 0.449 -0.148 HispFemale1 BURT BURT 622.8 1598 -0.206 -0.533 HispFemale1 BOT BOUGHT 1005.1 1389.1 1.751 -0.893 HispFemale1 BAT BAT 1045.5 1881.8 1.958 -0.043 HispFemale1 BEAT BEAT 365.4 2942.6 -1.524 1.787 HispFemale1 BUTT BUTT 870.2 1792.1 1.06 -0.198 HispFemale1 BET BED 730.1 2059.8 0.343 0.264 HispFemale1 BET BEN 792.9 2017.8 0.665 0.192 HispFemale1 BEAT BEANS 488.2 3026.4 -0.895 1.932 HispFemale1 BUTT BUDS 732.6 1723.6 0.356 -0.316 HispFemale1 BUTT BUNS 822.1 1597.2 0.814 -0.534 HispFemale1 BURT BURNT 638.3 1515.7 -0.127 -0.675 HispFemale1 BURT BIRD 602 1464.2 -0.313 -0.764 HispFemale1 BIT BIT 563.1 2316.3 -0.512 0.707 HispFemale1 BAT BAD 912.1 1842.3 1.275 -0.111 HispFemale1 BOT BOTTLE 787.1 1244.6 0.635 -1.142 HispFemale1 BIT BID 592.4 2314.2 -0.362 0.703 HispFemale1 BOOT BOONE 424.1 1085.5 -1.223 -1.417 HispFemale1 BET BET 715.9 2128.7 0.27 0.383 HispFemale1 BIT BIDS 552.4 2255.1 -0.567 0.601 HispFemale1 BIT BIN 581.9 2167.8 -0.416 0.45 HispFemale1 BOOT BOOTS 374.8 1184.7 -1.476 -1.246 HispFemale1 BOT BONFIRE 847.1 1128.1 0.942 -1.343 HispFemale1 BEAT BEADS 351.3 2963.9 -1.596 1.824 HispFemale1 BAT BAD 812.7 2042 0.766 0.233 HispFemale1 BAN BANNED 941.7 1945.6 1.426 0.067 HispFemale1 BEAT BEAD 347.9 2962.2 -1.613 1.821 HispFemale1 BEAT BEAD 330.8 2917 -1.701 1.743 HispFemale1 BIT BID 627 2392.1 -0.185 0.837 HispFemale1 BIT BID 628.4 2217 -0.178 0.535 HispFemale1 BET BED 771.4 2186 0.555 0.482 HispFemale1 BET BED 723.2 2091.5 0.308 0.319 HispFemale1 BAT BAD 920.8 1910.4 1.319 0.006 HispFemale1 BAT BAD 904.4 1941.9 1.235 0.061 HispFemale1 BOT BOTTLE 870 1375.8 1.059 -0.916 HispFemale1 BOT BOTTLE 870.4 1313.9 1.061 -1.023 HispFemale1 BUTT BUD 835.6 1724.8 0.883 -0.314 HispFemale1 BUTT BUD 762 1781.9 0.506 -0.215 HispFemale1 BOY BOYDE 520.4 859.9 413.8 2159.3 -0.73 -1.806 -1.276 0.436 HispFemale1 BAIT BADE 520.1 2533.5 395.6 2866.5 -0.732 1.081 -1.369 1.656 HispFemale1 BAIT BAIT 507.4 2574.8 360.3 2949.5 -0.797 1.153 -1.55 1.799 HispFemale1 BITE BITE 837.5 1443.6 533.3 2417 0.893 -0.799 -0.664 0.88 HispFemale1 BITE BIDE 927 1441.9 473 2604.4 1.351 -0.802 -0.973 1.204 HispFemale1 BOUT BOWED 952.2 1757.3 521.4 1027.4 1.48 -0.258 -0.725 -1.517 HispFemale1 BOAT BOAT 588.6 1165.5 459.9 852.5 -0.381 -1.279 -1.04 -1.819 HispFemale1 BOAT BODE 616 1322.8 464.6 1224.2 -0.241 -1.007 -1.016 -1.178 HispFemale1 BAIT BADE 549.5 2357.8 472.9 2729.4 -0.581 0.778 -0.974 1.419 HispFemale1 BAIT BADE 548.9 2386.9 451.6 2689.5 -0.584 0.828 -1.083 1.35 HispFemale1 BITE BIDE 932.5 1540.7 573.5 2445.6 1.379 -0.632 -0.459 0.93 HispFemale1 BITE BIDE 893.8 1561.6 587.5 1950.9 1.181 -0.595 -0.387 0.076 HispFemale1 BOY BOYDE 560.2 880.6 449.9 1814 -0.527 -1.77 -1.091 -0.16 HispFemale1 BOY BOYDE 616.8 989.3 491.2 2083.2 -0.237 -1.583 -0.88 0.304 HispFemale1 BOUT BOWED 964.8 1881.2 594.4 1123.5 1.545 -0.044 -0.352 -1.351 HispFemale1 BOUT BOWED 899.3 1792 669 1291.1 1.209 -0.198 0.03 -1.062 HispFemale1 BOAT BODE 636.2 1177.2 496.6 1147.6 -0.138 -1.259 -0.852 -1.31 HispFemale1 BOAT BODE 622.8 1177.7 523.1 1274.9 -0.206 -1.258 -0.717 -1.09 HispFemale1 BAIT BADE 582.2 2319.6 449.4 2732.4 -0.414 0.712 -1.094 1.424 HispFemale1 BAIT BADE 557.6 2335.3 414.4 2705.5 -0.54 0.739 -1.273 1.378 HispFemale1 BOY BOYDE 588.2 909.9 447.9 2295.6 -0.383 -1.72 -1.102 0.671 HispFemale1 BAIT BADE 531.3 2401.6 388.3 2848.4 -0.675 0.854 -1.407 1.625 HispFemale1 BAIT BAIT 507 2430 383.7 2825.3 -0.799 0.903 -1.43 1.585 HispFemale1 BITE BITE 849.5 1371.7 472 2601.7 0.954 -0.923 -0.978 1.199 HispFemale1 BITE BIDE 909.1 1426.9 493.4 2527.9 1.259 -0.828 -0.869 1.072 HispFemale1 BOUT BOWED 980.7 1761.1 543.2 952.5 1.626 -0.251 -0.614 -1.646 HispFemale1 BOAT BOAT 568 1009.6 497.7 909 -0.487 -1.548 -0.847 -1.721 HispFemale1 BOAT BODE 631.6 1131.3 446 1090.1 -0.161 -1.338 -1.111 -1.409 HispFemale1 BOAT BODE 648.4 1196.9 507.3 1148.5 -0.075 -1.225 -0.797 -1.308
145
HispFemale1 BOAT BODE 619.3 1137.6 470.3 1171.7 -0.224 -1.327 -0.987 -1.268 HispFemale1 BAIT BADE 593.6 2445.1 445.3 2754.2 -0.356 0.929 -1.115 1.462 HispFemale1 BAIT BADE 522.4 2348.2 443 2670.7 -0.72 0.762 -1.127 1.318 HispFemale1 BITE BIDE 958.3 1578.4 495.9 2181.7 1.511 -0.566 -0.856 0.474 HispFemale1 BITE BIDE 879.7 1560.4 602.4 2373.4 1.109 -0.598 -0.311 0.805 HispFemale1 BOY BOYDE 538.2 968.5 415.9 1687.7 -0.639 -1.619 -1.265 -0.378 HispFemale1 BOY BOYDE 588.6 984.4 470.2 2070.9 -0.381 -1.591 -0.987 0.283 HispFemale1 BOUT BOWED 979.9 1799.3 581.8 1085.9 1.622 -0.185 -0.416 -1.416 HispFemale1 BOUT BOWED 815.3 1841.2 699.6 1381.8 0.779 -0.113 0.187 -0.906 HispFemale2 BURT BURT 568.2 1692.5 -0.332 -0.405 HispFemale2 BOT BOUGHT 867.3 1368 1.44 -0.929 HispFemale2 BAT BAT 1010.5 1761.1 2.289 -0.295 HispFemale2 BEAT BEAT 332 2912.9 -1.731 1.564 HispFemale2 BUTT BUTT 711.1 1472.9 0.515 -0.76 HispFemale2 BET BED 648.6 2104.1 0.145 0.259 HispFemale2 BET BEN 698.5 2170.7 0.44 0.366 HispFemale2 BEAT BEANS 449.6 3151.2 -1.034 1.949 HispFemale2 BUTT BUDS 666.8 1685.2 0.253 -0.417 HispFemale2 BUTT BUNS 671.4 1660.6 0.28 -0.457 HispFemale2 BURT BURNT 699.5 1753.7 0.446 -0.307 HispFemale2 BURT BIRD 494.5 1702 -0.768 -0.39 HispFemale2 BIT BIT 540.7 2514.2 -0.495 0.921 HispFemale2 BAT BAD 903.4 1822.6 1.654 -0.196 HispFemale2 BOT BOTTLE 765.3 1293.6 0.836 -1.049 HispFemale2 BIT BID 460.1 2629.7 -0.972 1.107 HispFemale2 BET BET 661.6 2339.4 0.222 0.639 HispFemale2 BIT BIDS 493.6 2477.7 -0.774 0.862 HispFemale2 BIT BIN 559.4 2416.5 -0.384 0.763 HispFemale2 BOT BONFIRE 880.4 1330.4 1.518 -0.99 HispFemale2 BEAT BEADS 408.5 3094.6 -1.278 1.858 HispFemale2 BAT BAD 864.8 1582.6 1.426 -0.583 HispFemale2 BAN BANNED 739.5 1781.2 0.683 -0.262 HispFemale2 BEAT BEAD 477.4 2882.9 -0.87 1.516 HispFemale2 BEAT BEAD 426.3 3035.5 -1.172 1.762 HispFemale2 BIT BID 554.9 2513.6 -0.41 0.92 HispFemale2 BIT BID 476.8 2487.1 -0.873 0.877 HispFemale2 BET BED 757.6 2277.5 0.79 0.539 HispFemale2 BET BED 713.3 2270.6 0.528 0.528 HispFemale2 BOT BOTTLE 852.9 1131.6 1.355 -1.311 HispFemale2 BOT BOTTLE 857 1104.5 1.379 -1.355 HispFemale2 BURT BURT 567.6 1808.6 -0.335 -0.218 HispFemale2 BOT BOUGHT 845.1 1459.6 1.309 -0.781 HispFemale2 BAT BAT 916.8 1730.7 1.734 -0.344 HispFemale2 BEAT BEAT 414.1 2837.3 -1.245 1.442 HispFemale2 BUTT BUTT 676.2 1693.1 0.308 -0.405 HispFemale2 BET BED 699.8 2212.9 0.448 0.434 HispFemale2 BET BEN 662.5 2286.9 0.227 0.554 HispFemale2 BEAT BEANS 450.5 3118.2 -1.029 1.896 HispFemale2 BUTT BUDS 664 1631.1 0.236 -0.505 HispFemale2 BUTT BUNS 717.6 1612 0.553 -0.535 HispFemale2 BURT BURNT 667.8 1730 0.258 -0.345 HispFemale2 BURT BIRD 533.2 1985.2 -0.539 0.067 HispFemale2 BIT BIT 547.8 2536.4 -0.452 0.957 HispFemale2 BAT BAD 930.7 1863.1 1.816 -0.13 HispFemale2 BOT BOTTLE 745.1 1312.7 0.716 -1.019 HispFemale2 BIT BID 540.4 2386.2 -0.496 0.714 HispFemale2 BEAT BEAD 401.2 2977.3 -1.321 1.668 HispFemale2 BEAT BEAD 364.9 3080.9 -1.536 1.835 HispFemale2 BIT BID 531.8 2438.3 -0.547 0.798 HispFemale2 BIT BID 509.4 2388.2 -0.68 0.717 HispFemale2 BET BED 716.5 2234.9 0.547 0.47 HispFemale2 BET BED 709.8 2222.7 0.507 0.45 HispFemale2 BAT BAD 909.4 1887.2 1.69 -0.091 HispFemale2 BAT BAD 925.1 1806.8 1.783 -0.221 HispFemale2 BOT BOTTLE 759.5 1253.1 0.802 -1.115 HispFemale2 BOT BOTTLE 788 1295.4 0.971 -1.046 HispFemale2 BUTT BUD 728.1 1749.4 0.616 -0.314
146
HispFemale2 BUTT BUD 715.7 1652.1 0.542 -0.471 HispFemale2 BAN BANNED 857.3 1735.2 1.381 -0.337 HispFemale2 BOOT BOONE 505.2 1133.3 -0.705 -1.308 HispFemale2 BOOT BOOTS 378.4 1355 -1.456 -0.95 HispFemale2 BOY BOYDE 527.4 891.2 535 2053.5 -0.573 -1.699 -0.528 0.177 HispFemale2 BAIT BADE 531.5 2682.1 379.1 2945.6 -0.549 1.192 -1.452 1.617 HispFemale2 BAIT BAIT 528 2763.4 411.3 2961.9 -0.57 1.323 -1.261 1.643 HispFemale2 BITE BITE 896.8 1591.1 489.9 2668.8 1.615 -0.569 -0.795 1.17 HispFemale2 BITE BIDE 861.6 1555.6 635 2417.7 1.407 -0.626 0.064 0.765 HispFemale2 BOUT BOWED 929.6 1713.6 726.1 1225.6 1.809 -0.371 0.604 -1.159 HispFemale2 BOAT BOAT 567.2 1132.7 452.3 937.6 -0.338 -1.309 -1.018 -1.624 HispFemale2 BOAT BODE 553.9 1058.7 439.8 982.9 -0.416 -1.428 -1.092 -1.551 HispFemale2 BOAT BODE 608 1215.2 488.8 1066.5 -0.096 -1.176 -0.802 -1.416 HispFemale2 BOAT BODE 612 1213.1 518.1 1022.2 -0.072 -1.179 -0.628 -1.487 HispFemale2 BAIT BADE 546.1 2593.3 410.4 2724.4 -0.463 1.048 -1.266 1.26 HispFemale2 BITE BIDE 897.2 1342.1 628.9 2405 1.617 -0.971 0.028 0.745 HispFemale2 BITE BIDE 794.5 1709.4 733.1 2356.6 1.009 -0.378 0.645 0.666 HispFemale2 BOY BOYDE 490.9 821.8 550.9 1343.7 -0.79 -1.811 -0.434 -0.968 HispFemale2 BOY BOYDE 429.2 798.9 547.4 1757.2 -1.155 -1.848 -0.455 -0.301 HispFemale2 BOY BOYDE 503.7 861.2 524.1 1880.7 -0.714 -1.747 -0.593 -0.102 HispFemale2 BAIT BADE 488.1 2651.5 372.3 2889.5 -0.806 1.142 -1.492 1.527 HispFemale2 BAIT BAIT 491.4 2731.9 398.2 2952.1 -0.787 1.272 -1.339 1.628 HispFemale2 BITE BITE 891.4 1560.6 437.3 2705.9 1.583 -0.618 -1.107 1.23 HispFemale2 BITE BIDE 813.9 1465.1 658.1 2433.8 1.124 -0.773 0.201 0.791 HispFemale2 BOAT BODE 601.4 1254.3 484.2 1054.6 -0.135 -1.113 -0.829 -1.435 HispFemale2 BOAT BODE 553.8 1233.1 471.3 1174.3 -0.417 -1.147 -0.906 -1.242 HispFemale2 BAIT BADE 533.3 2551.4 424.6 2701.2 -0.538 0.981 -1.182 1.223 HispFemale2 BAIT BADE 485.8 2688.3 411.4 2732.3 -0.82 1.202 -1.261 1.273 HispFemale2 BITE BIDE 846.7 1480.9 616 2499.5 1.318 -0.747 -0.048 0.897 HispFemale2 BITE BIDE 792.7 1580.9 700.4 2249.9 0.998 -0.586 0.452 0.494 HispFemale2 BOY BOYDE 537.3 952.5 507.7 2475.6 -0.515 -1.6 -0.69 0.858 HispFemale2 BOY BOYDE 575.9 1000.3 534.2 2401 -0.286 -1.523 -0.533 0.738 HispFemale2 BOUT BOWED 804.6 1782.2 634.4 1351.6 1.069 -0.261 0.061 -0.956 HispFemale2 BOUT BOWED 776.5 2003.4 714.7 1589.9 0.902 0.096 0.536 -0.571 HispFemale2 BAN BANNED 760.5 1944.4 0.808 0.001 HispFemale3 BOT BOTTLE 720.5 1089 0.537 -1.32 HispFemale3 BOT BONFIRE 857.7 1198.3 1.27 -1.151 HispFemale3 BOT BOTTLE 750.9 1147 0.699 -1.231 HispFemale3 BOT BOTTLE 853.7 1184.9 1.248 -1.172 HispFemale3 BOT BOTTLE 782 1201.2 0.865 -1.147 HispFemale3 BOT BONFIRE 844.9 1226.7 1.201 -1.107 HispFemale3 BOT BOTTLE 806.7 1191.1 0.997 -1.162 HispFemale3 BAT BAT 961.2 1947.1 1.823 0.006 HispFemale3 BAT BAD 853.5 2335.5 1.247 0.607 HispFemale3 BAT BAD 838.5 1972.6 1.167 0.046 HispFemale3 BAT BAD 887.1 2228.6 1.427 0.442 HispFemale3 BAT BAD 884 2492.3 1.41 0.849 HispFemale3 BAT BAT 908.5 2526.5 1.541 0.902 HispFemale3 BAT BAD 880.9 2167.6 1.394 0.347 HispFemale3 BAT BAD 896.3 2221.8 1.476 0.431 HispFemale3 BAT BAD 865.7 2076.2 1.313 0.206 HispFemale3 BAT BAD 837.1 2087.8 1.16 0.224 HispFemale3 BAN BANNED 829.3 1966.3 1.118 0.036 HispFemale3 BAN BANNED 834.2 1976.5 1.144 0.052 HispFemale3 BUTT BUTT 816 1632.9 1.047 -0.479 HispFemale3 BUTT BUDS 765.3 1540 0.776 -0.623 HispFemale3 BUTT BUNS 765.2 1523.1 0.776 -0.649 HispFemale3 BUTT BUD 762.4 1569.5 0.761 -0.577 HispFemale3 BUTT BUD 730.9 1510.3 0.592 -0.669 HispFemale3 BUTT BUTT 820.4 1560.6 1.071 -0.591 HispFemale3 BUTT BUDS 710.3 1513.3 0.482 -0.664 HispFemale3 BUTT BUNS 789.6 1506.8 0.906 -0.674 HispFemale3 BUTT BUD 723.7 1492.8 0.554 -0.696 HispFemale3 BUTT BUD 786.1 1539.3 0.887 -0.624 HispFemale3 BOT BOUGHT 879.1 1289.6 1.384 -1.01 HispFemale3 BOT BOUGHT 839.4 1286 1.172 -1.016 HispFemale3 BET BEN 766.3 2367.5 0.781 0.656
147
HispFemale3 BET BET 692.2 2146.4 0.385 0.315 HispFemale3 BET BED 690.3 2619.7 0.375 1.046 HispFemale3 BET BED 634.7 2598.3 0.078 1.013 HispFemale3 BET BED 645.4 2290.2 0.135 0.537 HispFemale3 BET BEN 764 2422.1 0.769 0.741 HispFemale3 BET BET 709.2 2251.2 0.476 0.477 HispFemale3 BET BED 719.9 2604.5 0.533 1.023 HispFemale3 BET BED 657.8 2364.9 0.202 0.652 HispFemale3 BURT BURT 594.1 1628.4 -0.139 -0.486 HispFemale3 BURT BURNT 695 1621 0.4 -0.498 HispFemale3 BURT BIRD 498.8 1696.1 -0.648 -0.382 HispFemale3 BURT BURT 558.7 1665.5 -0.328 -0.429 HispFemale3 BURT BURNT 575.4 1662.1 -0.239 -0.434 HispFemale3 BURT BIRD 537.4 1697.3 -0.442 -0.38 HispFemale3 BIT BIT 562.3 2460.5 -0.309 0.8 HispFemale3 BIT BID 528.6 2447.4 -0.489 0.78 HispFemale3 BIT BIDS 555 2474.2 -0.348 0.821 HispFemale3 BIT BIN 657.1 2299.5 0.198 0.551 HispFemale3 BIT BID 501.3 2417.9 -0.635 0.734 HispFemale3 BIT BID 446.2 2450.8 -0.929 0.785 HispFemale3 BIT BIT 536 2407.5 -0.449 0.718 HispFemale3 BIT BID 483.4 2424.7 -0.73 0.745 HispFemale3 BIT BIDS 498.7 2498.4 -0.649 0.859 HispFemale3 BIT BIN 650.1 2333.2 0.16 0.603 HispFemale3 BIT BID 477.4 2557.5 -0.762 0.95 HispFemale3 BIT BID 443 2580.8 -0.946 0.986 HispFemale3 BEAT BEAT 315 2891.6 -1.63 1.467 HispFemale3 BEAT BEANS 352.7 2914.6 -1.429 1.502 HispFemale3 BEAT BEADS 354.2 2758.5 -1.421 1.261 HispFemale3 BEAT BEAD 334.1 2899 -1.528 1.478 HispFemale3 BEAT BEAD 304.3 2834.9 -1.688 1.379 HispFemale3 BEAT BEAT 350 2863.9 -1.443 1.424 HispFemale3 BEAT BEANS 387.8 2898.7 -1.241 1.478 HispFemale3 BEAT BEADS 345.2 2850 -1.469 1.402 HispFemale3 BEAT BEAD 325.3 2959.2 -1.575 1.571 HispFemale3 BEAT BEAD 302.6 2938.6 -1.697 1.539 HispFemale3 BOOT BOONE 357.8 1090.9 -1.402 -1.317 HispFemale3 BOOT BOONE 359.6 1088.4 -1.392 -1.321 HispFemale3 BOOT BOOTS 396.4 1217.8 -1.195 -1.121 HispFemale3 BOOT BOONE 353.9 1023.4 -1.422 -1.422 HispFemale3 BOOT BOOTS 357.5 993.2 -1.403 -1.468 HispFemale3 BOUT BOWED 874.4 1967.6 776.4 1359.3 1.359 0.038 0.835 -0.902 HispFemale3 BOUT BOWED 852.3 1891.2 611 1166 1.241 -0.08 -0.049 -1.201 HispFemale3 BOUT BOWED 903.6 1865.6 541.1 1082.3 1.515 -0.12 -0.422 -1.331 HispFemale3 BOUT BOWED 895.3 1950.8 462.1 1073.6 1.471 0.012 -0.844 -1.344 HispFemale3 BOUT BOWED 838.4 1914.5 510.1 1106.9 1.167 -0.044 -0.588 -1.293 HispFemale3 BITE BITE 868.8 1453.4 494.3 2453.9 1.329 -0.757 -0.672 0.79 HispFemale3 BITE BIDE 853 1286.3 564.2 1733.8 1.245 -1.015 -0.299 -0.323 HispFemale3 BITE BIDE 906 1440.2 585.8 2542 1.528 -0.777 -0.183 0.926 HispFemale3 BITE BIDE 797.3 1310 574.5 2513.2 0.947 -0.979 -0.244 0.882 HispFemale3 BITE BITE 908.1 1400.1 564.2 2705.8 1.539 -0.839 -0.299 1.179 HispFemale3 BITE BIDE 860.9 1365.7 600.3 1908.9 1.287 -0.893 -0.106 -0.053 HispFemale3 BITE BIDE 643.2 957.9 560.8 2118.5 0.124 -1.523 -0.317 0.271 HispFemale3 BITE BIDE 778.1 1260.4 594.7 2526.5 0.844 -1.055 -0.136 0.902 HispFemale3 BAIT BADE 505.3 2590.5 369.9 2878 -0.613 1.001 -1.337 1.446 HispFemale3 BAIT BAIT 542.6 2648.9 359.7 2822.5 -0.414 1.091 -1.391 1.36 HispFemale3 BAIT BADE 548.4 2512.1 401.9 2918.1 -0.383 0.88 -1.166 1.508 HispFemale3 BAIT BADE 521.7 2493.5 425.1 2798.4 -0.526 0.851 -1.042 1.323 HispFemale3 BAIT BADE 544.2 2621.1 389.2 2878.8 -0.405 1.048 -1.234 1.447 HispFemale3 BAIT BAIT 518.3 2778.5 312.3 2914.5 -0.544 1.292 -1.645 1.502 HispFemale3 BAIT BADE 540.6 2470.8 401.8 2904.8 -0.425 0.816 -1.166 1.487 HispFemale3 BAIT BADE 555.3 2573.5 405.9 2840.7 -0.346 0.975 -1.145 1.388 HispFemale3 BOAT BOAT 610.9 1144.5 462.9 880.4 -0.049 -1.235 -0.84 -1.643 HispFemale3 BOAT BODE 569.5 1147.3 474.5 932.7 -0.27 -1.23 -0.778 -1.562 HispFemale3 BOAT BODE 675.7 1197.6 427.3 1058.4 0.297 -1.152 -1.03 -1.368 HispFemale3 BOAT BODE 605.1 1121.9 362.9 882.2 -0.08 -1.269 -1.374 -1.64 HispFemale3 BOAT BOAT 684.1 1256 425.2 917 0.342 -1.062 -1.041 -1.586
148
HispFemale3 BOAT BODE 528.2 1172.5 489 937.5 -0.491 -1.191 -0.7 -1.555 HispFemale3 BOAT BODE 677.3 1350.6 418.1 1092.6 0.306 -0.916 -1.079 -1.315 HispFemale3 BOAT BODE 638.1 1264.2 403.7 1087.1 0.096 -1.049 -1.156 -1.323 HispFemale3 BOY BOYDE 460.5 780.1 411.9 1928.7 -0.853 -1.798 -1.112 -0.022 HispFemale3 BOY BOYDE 512.3 804.3 446.6 1722.5 -0.576 -1.761 -0.927 -0.341 HispFemale3 BOY BOYDE 471 804.5 448.2 2308.2 -0.797 -1.76 -0.919 0.565 HispFemale3 BOY BOYDE 514.3 844.4 466.2 2453.6 -0.565 -1.699 -0.822 0.789 Hispfemale4 BURT BURT 617.3 2024.9 -0.188 -0.012 Hispfemale4 BOT BOUGHT 877.6 1477.5 1.175 -0.894 Hispfemale4 BAT BAT 1008.5 1653.3 1.861 -0.611 Hispfemale4 BEAT BEAT 451.9 3121.3 -1.055 1.754 Hispfemale4 BUTT BUTT 732.5 1772.5 0.415 -0.419 Hispfemale4 BET BED 734.3 2182.8 0.424 0.242 Hispfemale4 BET BEN 765.8 2203 0.589 0.275 Hispfemale4 BEAT BEANS 426.3 3193.5 -1.189 1.87 Hispfemale4 BUTT BUDS 665.7 1794.2 0.065 -0.384 Hispfemale4 BUTT BUNS 682 1778.8 0.15 -0.408 Hispfemale4 BURT BURNT 559.2 1911.6 -0.493 -0.195 Hispfemale4 BURT BIRD 589.3 1666.3 -0.335 -0.59 Hispfemale4 BIT BIT 670.4 2474.3 0.09 0.712 Hispfemale4 BAT BAD 968.2 1775.3 1.65 -0.414 Hispfemale4 BOT BOTTLE 872.8 1360.4 1.15 -1.082 Hispfemale4 BIT BID 574.9 2263.3 -0.411 0.372 Hispfemale4 BOOT BOONE 418.6 1825.9 -1.229 -0.333 Hispfemale4 BET BET 780.6 2214.3 0.667 0.293 Hispfemale4 BIT BIDS 594.4 2326.3 -0.308 0.473 Hispfemale4 BIT BIN 559.9 2146.6 -0.489 0.184 Hispfemale4 BOOT BOOTS 456.8 1620.1 -1.029 -0.664 Hispfemale4 BOT BONFIRE 893.7 1318.7 1.259 -1.149 Hispfemale4 BEAT BEADS 400.5 3064.1 -1.324 1.661 Hispfemale4 BAN BANNED 928.3 1934.9 1.441 -0.157 Hispfemale4 BEAT BEAD 357.7 3138.3 -1.548 1.781 Hispfemale4 BEAT BEAD 377.9 3155 -1.443 1.808 Hispfemale4 BIT BID 557 2425.8 -0.504 0.634 Hispfemale4 BIT BID 536.9 2360.7 -0.61 0.529 Hispfemale4 BET BED 686.2 2307.6 0.172 0.443 Hispfemale4 BET BED 723.2 2186.9 0.366 0.249 Hispfemale4 BAT BAD 1017.8 1800.7 1.91 -0.373 Hispfemale4 BAT BAD 965.7 1825.5 1.637 -0.333 Hispfemale4 BOT BOTTLE 931.4 1254.5 1.457 -1.253 Hispfemale4 BOT BOTTLE 821.2 1293.1 0.88 -1.191 Hispfemale4 BUTT BUD 719.4 1832.8 0.346 -0.322 Hispfemale4 BUTT BUD 619.6 1726.3 -0.176 -0.493 Hispfemale4 BURT BURT 573 1911.9 -0.421 -0.194 Hispfemale4 BOT BOUGHT 913.5 1439.9 1.363 -0.954 Hispfemale4 BAT BAT 1013.2 1764.1 1.885 -0.432 Hispfemale4 BEAT BEAT 411.2 3182.7 -1.268 1.852 Hispfemale4 BUTT BUTT 763.8 1625.6 0.579 -0.655 Hispfemale4 BET BED 677.7 2119.7 0.128 0.141 Hispfemale4 BET BEN 694 2232.2 0.213 0.322 Hispfemale4 BEAT BEANS 465.2 3253.6 -0.985 1.967 Hispfemale4 BUTT BUDS 706.7 1758.6 0.28 -0.441 Hispfemale4 BUTT BUNS 725.1 1796.5 0.376 -0.38 Hispfemale4 BURT BURNT 623.9 1927.9 -0.154 -0.168 Hispfemale4 BURT BIRD 607.9 1782.6 -0.238 -0.402 Hispfemale4 BIT BIT 589 2514.3 -0.337 0.776 Hispfemale4 BAT BAD 948.2 1699.6 1.545 -0.536 Hispfemale4 BOT BOTTLE 815.5 1227.3 0.85 -1.297 Hispfemale4 BIT BID 479.3 2328.2 -0.911 0.476 Hispfemale4 BOOT BOONE 472.4 1333.8 -0.948 -1.125 Hispfemale4 BET BET 833.1 2152.4 0.942 0.193 Hispfemale4 BIT BIDS 544.6 2330.4 -0.569 0.48 Hispfemale4 BIT BIN 583.8 2148.3 -0.364 0.187 Hispfemale4 BOOT BOOTS 449 1626.3 -1.07 -0.654 Hispfemale4 BOT BONFIRE 887.3 1337.7 1.226 -1.119 Hispfemale4 BEAT BEADS 421 3064.3 -1.217 1.662 Hispfemale4 BAT BAD 965.8 1822.4 1.637 -0.338
149
Hispfemale4 BAN BANNED 892.8 1847.7 1.255 -0.298 Hispfemale4 BEAT BEAD 438.1 3195.2 -1.127 1.873 Hispfemale4 BEAT BEAD 373 3146.1 -1.468 1.794 Hispfemale4 BIT BID 528.6 2404.2 -0.653 0.599 Hispfemale4 BIT BID 503.6 2310.2 -0.784 0.447 Hispfemale4 BET BED 690.4 2275.3 0.194 0.391 Hispfemale4 BET BED 696 2263.1 0.224 0.371 Hispfemale4 BAT BAD 945.9 1943.9 1.533 -0.143 Hispfemale4 BAT BAD 867.1 1898.5 1.12 -0.216 Hispfemale4 BOT BOTTLE 921.6 1302.9 1.406 -1.175 Hispfemale4 BOT BOTTLE 846.8 1310.9 1.014 -1.162 Hispfemale4 BUTT BUD 697.4 1904.2 0.231 -0.207 Hispfemale4 BUTT BUD 698.4 1952.4 0.236 -0.129 Hispfemale4 BEAT BEAD 375.6 3125.9 -1.455 1.761 Hispfemale4 BEAT BEAD 406.3 3040.4 -1.294 1.623 Hispfemale4 BOY BOYDE 421 844.9 495.3 2098.5 -1.217 -1.912 -0.828 0.106 Hispfemale4 BAIT BADE 488.9 2715.8 371.7 2764.6 -0.861 1.101 -1.475 1.179 Hispfemale4 BAIT BAIT 415.6 2931.6 360.3 3098.7 -1.245 1.448 -1.535 1.717 Hispfemale4 BITE BITE 946.6 1740.2 417.9 2833.1 1.537 -0.471 -1.233 1.289 Hispfemale4 BITE BIDE 961.2 1517.6 606 2499.1 1.613 -0.829 -0.248 0.752 Hispfemale4 BOUT BOWED 924.1 1866.2 740.5 1475.3 1.419 -0.268 0.457 -0.897 Hispfemale4 BOAT BOAT 642.3 1292.5 501 934.7 -0.058 -1.192 -0.798 -1.768 Hispfemale4 BOAT BODE 601.1 1232.9 464.4 1156.9 -0.273 -1.288 -0.989 -1.41 Hispfemale4 BOAT BODE 592.2 1278.6 455.8 1092.7 -0.32 -1.214 -1.034 -1.513 Hispfemale4 BOAT BODE 516.1 1188.8 441.9 1151.2 -0.719 -1.359 -1.107 -1.419 Hispfemale4 BAIT BADE 437 2893.7 430.3 2872.1 -1.133 1.387 -1.168 1.352 Hispfemale4 BAIT BADE 416 2877 445 2810 -1.243 1.36 -1.091 1.252 Hispfemale4 BITE BIDE 982.7 1547.2 624 2459 1.726 -0.781 -0.153 0.687 Hispfemale4 BITE BIDE 944.4 1608.2 652.2 2467 1.525 -0.683 -0.006 0.7 Hispfemale4 BOY BOYDE 611.5 758.7 544 2484.6 -0.219 -2.051 -0.572 0.728 Hispfemale4 BOY BOYDE 510 871 516.6 2288 -0.751 -1.87 -0.716 0.412 Hispfemale4 BOUT BOWED 872.9 2048.7 655 1336.7 1.15 0.026 0.009 -1.12 Hispfemale4 BOUT BOWED 897.7 1993.5 704.5 1540.1 1.28 -0.063 0.268 -0.793 Hispfemale4 BOY BOYDE 453.5 789.2 475 2540.2 -1.047 -2.002 -0.934 0.818 Hispfemale4 BAIT BADE 387.9 2990.2 378.6 3173.3 -1.39 1.542 -1.439 1.837 Hispfemale4 BAIT BAIT 435.9 2798.1 376.3 2986.7 -1.139 1.233 -1.451 1.537 Hispfemale4 BITE BITE 868.8 1854.7 503.7 2665.4 1.129 -0.286 -0.784 1.019 Hispfemale4 BITE BIDE 936.6 1547.5 635.9 2389.7 1.484 -0.781 -0.091 0.575 Hispfemale4 BOUT BOWED 895.5 1835.7 649.2 1275.7 1.269 -0.317 -0.021 -1.219 Hispfemale4 BOAT BOAT 614.3 1101.2 493.5 902 -0.204 -1.5 -0.837 -1.821 Hispfemale4 BOAT BOWED 558.1 1265.9 438.5 1056.7 -0.499 -1.234 -1.125 -1.571 Hispfemale4 BITE BIDE 919.6 1674.6 609.4 2494 1.395 -0.576 -0.23 0.743 Hispfemale4 BITE BIDE 817.9 1736.2 693.8 2374.2 0.862 -0.477 0.212 0.55 Hispfemale4 BOY BOYDE 435.6 800.8 462 2615.9 -1.14 -1.984 -1.002 0.94 Hispfemale4 BOY BOYDE 496.9 960 495.2 2452.7 -0.819 -1.727 -0.828 0.677 Hispfemale4 BOUT BOWED 806.6 1912.8 577.7 1186.2 0.803 -0.193 -0.396 -1.363 Hispfemale4 BOUT BOWED 865 1951.7 734.3 1615.5 1.109 -0.13 0.424 -0.671 Anglomale1 BURT BURT 475.5 1304.7 -0.675 -0.674 Anglomale1 BAT BAT 734.9 1513.5 1.085 -0.168 Anglomale1 BEAT BEAT 276.1 2199.5 -2.028 1.492 Anglomale1 BUTT BUTT 684.1 1317 0.74 -0.644 Anglomale1 BET BED 660.5 1663.6 0.58 0.195 Anglomale1 BET BEN 631.9 1766.9 0.386 0.445 Anglomale1 BEAT BEANS 300.4 2435.7 -1.863 2.064 Anglomale1 BUTT BUDS 657.9 1356.3 0.562 -0.549 Anglomale1 BUTT BUNS 681.3 1250.2 0.721 -0.806 Anglomale1 BURT BURNT 523.6 1184.2 -0.349 -0.965 Anglomale1 BURT BIRD 513.2 1428.7 -0.419 -0.374 Anglomale1 BIT BIT 552.6 1901.2 -0.152 0.77 Anglomale1 BAT BAD 739.9 1626.9 1.119 0.106 Anglomale1 BOT BOTTLE 695.1 1062.4 0.815 -1.26 Anglomale1 BOOT BOONE 457.4 1166 -0.798 -1.01 Anglomale1 BET BET 662.2 1511.1 0.592 -0.174 Anglomale1 BIT BIDS 485.7 1916.8 -0.606 0.808 Anglomale1 BIT BIN 618.7 1738.2 0.296 0.376 Anglomale1 BOOT BOOTS 394.3 1349.7 -1.226 -0.565 Anglomale1 BOT BONFIRE 721.8 1069.3 0.996 -1.244
150
Anglomale1 BEAT BEADS 300.6 2265.4 -1.861 1.652 Anglomale1 BAT BAD 681.6 1723.4 0.723 0.34 Anglomale1 BAN BANNED 499.1 2377 -0.515 1.922 Anglomale1 BURT BURT 464.3 1262.5 -0.751 -0.776 Anglomale1 BOT BOUGHT 745.2 1097.4 1.155 -1.176 Anglomale1 BAT BAT 772.9 1620.9 1.343 0.092 Anglomale1 BEAT BEAT 280 2316.7 -2.001 1.776 Anglomale1 BUTT BUTT 736.9 1324.8 1.098 -0.625 Anglomale1 BET BED 645.2 1597.8 0.476 0.036 Anglomale1 BET BEN 694.1 1680 0.808 0.235 Anglomale1 BEAT BEANS 331.9 2454.8 -1.649 2.11 Anglomale1 BUTT BUDS 662.8 1309.3 0.596 -0.663 Anglomale1 BUTT BUNS 742.3 1388.7 1.135 -0.47 Anglomale1 BURT BURNT 504.9 1231.6 -0.476 -0.851 Anglomale1 BURT BIRD 484.5 1415.1 -0.614 -0.406 Anglomale1 BIT BIT 548.5 1870.4 -0.18 0.696 Anglomale1 BAT BAD 775.1 1714.9 1.357 0.319 Anglomale1 BOT BOTTLE 735.4 1017.2 1.088 -1.37 Anglomale1 BAN BANNED 517.3 2180 -0.391 1.445 Anglomale1 BOAT BOAT 551.2 1204.3 411.1 1081.9 -0.161 -0.917 -1.112 -1.213 Anglomale1 BOAT BODE 563.4 1200.4 444.5 1100.9 -0.079 -0.926 -0.885 -1.167 AngloMale2 BURT BURT 524.3 1311.9 -0.483 -0.715 AngloMale2 BOT BOUGHT 815.3 1252.6 1.257 -0.863 AngloMale2 BAT BAT 924.7 1685 1.911 0.219 AngloMale2 BEAT BEAT 302.9 2210.2 -1.807 1.534 AngloMale2 BUTT BUTT 693.2 1414.3 0.527 -0.459 AngloMale2 BET BED 637.3 1765.3 0.192 0.42 AngloMale2 BET BEN 760.4 1865.6 0.928 0.672 AngloMale2 BEAT BEANS 412.9 2376.9 -1.149 1.952 AngloMale2 BUTT BUDS 660.8 1350.9 0.333 -0.617 AngloMale2 BUTT BUNS 716.2 1285.5 0.664 -0.781 AngloMale2 BURT BURNT 667 1377.9 0.37 -0.55 AngloMale2 BURT BIRD 494 1394.8 -0.664 -0.507 AngloMale2 BIT BIT 563.2 1892.5 -0.251 0.739 AngloMale2 BAT BAD 794.4 1623.9 1.132 0.066 AngloMale2 BOT BOTTLE 808.6 1167.3 1.217 -1.077 AngloMale2 BIT BID 487.7 1855.2 -0.702 0.646 AngloMale2 BOOT BOONE 482 1002.2 -0.736 -1.49 AngloMale2 BET BET 653.4 1764.1 0.289 0.417 AngloMale2 BIT BIDS 506.6 1851.7 -0.589 0.637 AngloMale2 BIT BIN 520.1 1829.7 -0.508 0.582 AngloMale2 BOOT BOOTS 398.6 1129 -1.235 -1.173 AngloMale2 BOT BONFIRE 782.6 1153.4 1.061 -1.112 AngloMale2 BEAT BEADS 310.9 2157.2 -1.759 1.402 AngloMale2 BAT BAD 801.6 1676 1.175 0.197 AngloMale2 BAN BANNED 685 1918 0.478 0.803 AngloMale2 BEAT BEAD 301.1 2284.3 -1.818 1.72 AngloMale2 BEAT BEAD 299.7 2239.5 -1.826 1.608 AngloMale2 BIT BID 517.7 1851.7 -0.523 0.637 AngloMale2 BIT BID 486.1 1826.7 -0.712 0.574 AngloMale2 BET BED 635.6 1776.1 0.182 0.447 AngloMale2 BET BED 673.8 1748.6 0.411 0.379 AngloMale2 BAT BAD 823.1 1650.1 1.303 0.132 AngloMale2 BAT BAD 854.3 1712 1.49 0.287 AngloMale2 BOT BOTTLE 788.6 1154.6 1.097 -1.109 AngloMale2 BOT BOTTLE 760.6 1189.2 0.93 -1.022 AngloMale2 BUTT BUD 763 1379.6 0.944 -0.545 AngloMale2 BUTT BUD 695.1 1360.9 0.538 -0.592 AngloMale2 BURT BURT 493.5 1348.1 -0.667 -0.624 AngloMale2 BOT BOUGHT 842.3 1284.4 1.418 -0.784 AngloMale2 BAT BAT 898.9 1676.1 1.756 0.197 AngloMale2 BEAT BEAT 302.4 2143.7 -1.81 1.368 AngloMale2 BUTT BUTT 703.6 1453.4 0.589 -0.361 AngloMale2 BET BED 628.9 1771.2 0.142 0.435 AngloMale2 BET BEN 725.3 1741.5 0.719 0.361 AngloMale2 BEAT BEANS 471.9 2216.8 -0.796 1.551 AngloMale2 BUTT BUDS 676.1 1288.1 0.424 -0.775
151
AngloMale2 BUTT BUNS 696.4 1296.5 0.546 -0.754 AngloMale2 BURT BURNT 687.1 1323 0.49 -0.687 AngloMale2 BURT BIRD 521.9 1355.2 -0.497 -0.607 AngloMale2 BIT BIT 565.8 1917.9 -0.235 0.803 AngloMale2 BAT BAD 896.2 1969.4 1.74 0.931 AngloMale2 BOT BOTTLE 809.6 1192.3 1.223 -1.014 AngloMale2 BIT BID 496.9 1819.2 -0.647 0.555 AngloMale2 BOOT BOONE 549.3 1097.4 -0.334 -1.252 AngloMale2 BET BET 664.9 1772.3 0.357 0.438 AngloMale2 BIT BIDS 507.4 1868.2 -0.584 0.678 AngloMale2 BIT BIN 573.7 1781.2 -0.188 0.46 AngloMale2 BOOT BOOTS 408.7 1268.3 -1.174 -0.824 AngloMale2 BOT BONFIRE 758.2 1276.6 0.915 -0.803 AngloMale2 BEAT BEADS 318.5 2296.6 -1.714 1.751 AngloMale2 BAT BAD 834.6 1678.2 1.372 0.202 AngloMale2 BAN BANNED 655.5 1881.2 0.301 0.711 AngloMale2 BEAT BEAD 312.6 2259.1 -1.749 1.657 AngloMale2 BEAT BEAD 304.8 2244.1 -1.795 1.619 AngloMale2 BIT BID 491.6 1849.6 -0.679 0.631 AngloMale2 BIT BID 482.6 1820.4 -0.732 0.558 AngloMale2 BET BED 670.4 1794.3 0.39 0.493 AngloMale2 BET BED 646.1 1753.2 0.245 0.39 AngloMale2 BAT BAD 858.8 1671.7 1.517 0.186 AngloMale2 BAT BAD 853.2 1602.5 1.483 0.013 AngloMale2 BOT BOTTLE 805.6 1178.3 1.199 -1.05 AngloMale2 BOT BOTTLE 762.9 1206.6 0.943 -0.979 AngloMale2 BUTT BUD 675 1323.4 0.418 -0.686 AngloMale2 BUTT BUD 695.3 1331.5 0.539 -0.666 AngloMale2 BOY BOYDE 551 779.6 402.7 2074.6 -0.324 -2.048 -1.21 1.195 AngloMale2 BAIT BADE 564 1870.5 390.3 2102.5 -0.246 0.684 -1.284 1.265 AngloMale2 BAIT BAIT 520.7 1889.9 334.7 2072.4 -0.505 0.732 -1.617 1.189 AngloMale2 BITE BITE 769.8 1321.7 418.5 2019 0.985 -0.69 -1.116 1.056 AngloMale2 BITE BIDE 796.9 1254.9 614.9 1849.8 1.147 -0.858 0.059 0.632 AngloMale2 BOUT BOWED 852.8 1566.2 616 1093.1 1.481 -0.078 0.065 -1.263 AngloMale2 BOAT BOAT 570.4 1092.8 437.1 1042.3 -0.208 -1.264 -1.004 -1.39 AngloMale2 BOAT BODE 605.5 1081.9 463.6 1005.2 0.002 -1.291 -0.846 -1.483 AngloMale2 BOAT BODE 561.9 1107.7 469.3 1048.6 -0.258 -1.226 -0.812 -1.374 AngloMale2 BOAT BODE 572.4 1052.2 475.9 1078.8 -0.196 -1.365 -0.772 -1.299 AngloMale2 BAIT BADE 554.7 1893 382.7 2170.7 -0.301 0.74 -1.33 1.436 AngloMale2 BAIT BADE 519.6 1900.8 401 2166.2 -0.511 0.76 -1.22 1.424 AngloMale2 BITE BIDE 814.5 1316.6 478.6 2053.1 1.252 -0.703 -0.756 1.141 AngloMale2 BITE BIDE 792.4 1298.8 487.2 1977.1 1.12 -0.748 -0.705 0.951 AngloMale2 BOY BOYDE 509 764 391.4 2157.5 -0.575 -2.087 -1.278 1.403 AngloMale2 BOY BOYDE 580.2 643.1 346.1 2186.9 -0.149 -2.39 -1.549 1.476 AngloMale2 BOUT BOWED 878.2 1671.7 672.3 1134.5 1.633 0.186 0.402 -1.159 AngloMale2 BOUT BOWED 865.1 1612.8 770.2 1115 1.554 0.039 0.987 -1.208 AngloMale2 BOY BOYDE 567.9 751.5 382.8 2081 -0.222 -2.118 -1.329 1.211 AngloMale2 BAIT BADE 539.4 1832.8 374.5 2017.5 -0.393 0.589 -1.379 1.052 AngloMale2 BAIT BAIT 515 1901.9 363.1 2141.8 -0.539 0.762 -1.447 1.363 AngloMale2 BITE BITE 738.7 1373.2 378.9 2015.8 0.799 -0.561 -1.352 1.048 AngloMale2 BITE BIDE 775.6 1273.4 578 1827.1 1.019 -0.811 -0.162 0.575 AngloMale2 BOUT BOWED 802.7 1552.6 729 1160.8 1.181 -0.112 0.741 -1.093 AngloMale2 BOAT BOAT 607.4 1099.2 479.7 955.8 0.014 -1.248 -0.75 -1.607 AngloMale2 BOAT BODE 562.8 1084.1 457.8 1044.8 -0.253 -1.285 -0.881 -1.384 AngloMale2 BOAT BODE 577.9 1119.4 445.9 1052.8 -0.163 -1.197 -0.952 -1.364 AngloMale2 BOAT BODE 576.3 1082.2 466.3 1091.9 -0.172 -1.29 -0.83 -1.266 AngloMale2 BAIT BADE 532.9 1896.5 377.9 2213.6 -0.432 0.749 -1.358 1.543 AngloMale2 BAIT BADE 519.9 1874.2 378.1 2149.1 -0.509 0.693 -1.357 1.381 AngloMale2 BITE BIDE 784 1227 466.2 2032.9 1.07 -0.928 -0.83 1.09 AngloMale2 BITE BIDE 822.9 1312 478.5 1990.9 1.302 -0.715 -0.757 0.985 AngloMale2 BOY BOYDE 550.5 761.9 416.8 2039.8 -0.326 -2.092 -1.126 1.108 AngloMale2 BOY BOYDE 535.7 756.9 416.2 2114.3 -0.415 -2.105 -1.129 1.294 AngloMale2 BOUT BOWED 836.6 1614.3 700.6 1340.4 1.384 0.042 0.571 -0.644 AngloMale2 BOUT BOWED 846.9 1594.3 611.5 1116.9 1.446 -0.008 0.038 -1.203 AngloMale3 BOT BOTTLE 766.6 1108.4 1.698 -0.999 AngloMale3 BOT BONFIRE 592 1078.1 0.458 -1.06 AngloMale3 BOT BOTTLE 715.6 1072.2 1.336 -1.071
152
AngloMale3 BOT BOTTLE 743.9 1093 1.537 -1.03 AngloMale3 BOT BOTTLE 705.5 1074.5 1.265 -1.067 AngloMale3 BOT BONFIRE 586.5 1039.7 0.419 -1.137 AngloMale3 BOT BOTTLE 728 1077.1 1.424 -1.062 AngloMale3 BOT BOTTLE 714.3 1062.6 1.327 -1.091 AngloMale3 BAT BAT 749.8 1705.1 1.579 0.195 AngloMale3 BAT BAD 691.5 1815.6 1.165 0.417 AngloMale3 BAT BAD 700 1936.2 1.225 0.658 AngloMale3 BAT BAD 703.8 1814.8 1.252 0.415 AngloMale3 BAT BAD 662.2 1724.1 0.957 0.233 AngloMale3 BAT BAT 718.5 1716.9 1.357 0.219 AngloMale3 BAT BAD 644.6 1741.4 0.832 0.268 AngloMale3 BAT BAD 681.9 1933.5 1.097 0.652 AngloMale3 BAT BAD 703 1847.1 1.247 0.48 AngloMale3 BAT BAD 657.5 1757.5 0.924 0.3 AngloMale3 BAN BANNED 509.3 2095.9 -0.129 0.978 AngloMale3 BAN BANNED 496 2024.9 -0.223 0.835 AngloMale3 BUTT BUTT 688.1 1170.6 1.141 -0.875 AngloMale3 BUTT BUDS 636.6 1206.1 0.775 -0.803 AngloMale3 BUTT BUNS 575.5 1109.8 0.341 -0.996 AngloMale3 BUTT BUD 591.4 1207.5 0.454 -0.801 AngloMale3 BUTT BUD 615.2 1267 0.623 -0.682 AngloMale3 BUTT BUTT 671.7 1198.1 1.025 -0.819 AngloMale3 BUTT BUDS 618.6 1184.8 0.647 -0.846 AngloMale3 BUTT BUNS 575.4 1176.8 0.341 -0.862 AngloMale3 BUTT BUD 611.7 1192.5 0.598 -0.831 AngloMale3 BUTT BUD 610.5 1265.8 0.59 -0.684 AngloMale3 BOT BOUGHT 677.5 1008.8 1.066 -1.198 AngloMale3 BOT BOUGHT 676.8 953.9 1.061 -1.308 AngloMale3 BET BED 571.2 1832.1 0.311 0.45 AngloMale3 BET BEN 538.1 1891.5 0.076 0.568 AngloMale3 BET BED 614.8 1921.5 0.62 0.628 AngloMale3 BET BED 570.7 1812.3 0.307 0.41 AngloMale3 BET BED 567.7 1829.9 0.286 0.445 AngloMale3 BET BEN 521.5 1910.8 -0.042 0.607 AngloMale3 BET BED 583 1781.7 0.395 0.349 AngloMale3 BET BED 568.1 1762.1 0.289 0.309 AngloMale3 BET BET 650.5 1787.2 0.874 0.36 AngloMale3 BET BET 673.8 1772.9 1.039 0.331 AngloMale3 BURT BURT 446.2 1227.5 -0.577 -0.761 AngloMale3 BURT BURNT 478 1271.3 -0.351 -0.673 AngloMale3 BURT BIRD 471.9 1314.2 -0.394 -0.587 AngloMale3 BURT BURT 438.9 1265.2 -0.629 -0.685 AngloMale3 BURT BURNT 472.5 1230.4 -0.39 -0.755 AngloMale3 BURT BIRD 438.6 1263.9 -0.631 -0.688 AngloMale3 BIT BIT 467.9 1930.1 -0.423 0.646 AngloMale3 BIT BID 421.1 2119.3 -0.755 1.024 AngloMale3 BIT BIDS 462 1977 -0.465 0.74 AngloMale3 BIT BIN 485.6 1939.4 -0.297 0.664 AngloMale3 BIT BID 440.8 2020.1 -0.615 0.826 AngloMale3 BIT BID 436.7 1931.5 -0.644 0.648 AngloMale3 BIT BIT 442.7 1790.4 -0.602 0.366 AngloMale3 BIT BIDS 442.5 2010.3 -0.603 0.806 AngloMale3 BIT BIN 479.3 1906.3 -0.342 0.598 AngloMale3 BIT BID 439 1997 -0.628 0.78 AngloMale3 BIT BID 431 1952.7 -0.685 0.691 AngloMale3 BIT BID 428.1 2059.3 -0.705 0.904 AngloMale3 BEAT BEAT 298.8 2398.2 -1.624 1.583 AngloMale3 BEAT BEADS 311.8 2485 -1.531 1.756 AngloMale3 BEAT BEAD 260.1 2405.8 -1.899 1.598 AngloMale3 BEAT BEAD 322.5 2371.2 -1.455 1.529 AngloMale3 BEAT BEAT 288.2 2423.9 -1.699 1.634 AngloMale3 BEAT BEADS 262.2 2363.8 -1.884 1.514 AngloMale3 BEAT BEAD 254.9 2348.4 -1.935 1.483 AngloMale3 BEAT BEAD 279 2395.2 -1.764 1.577 AngloMale3 BEAT BEANS 398.3 2545 -0.917 1.876 AngloMale3 BEAT BEANS 416.1 2625 -0.791 2.037
153
AngloMale3 BOOT BOONE 328.9 1079.7 -1.41 -1.056 AngloMale3 BOOT BOONE 363.2 1111.7 -1.166 -0.992 AngloMale3 BOOT BOOTS 398.7 1074.4 -0.914 -1.067 AngloMale3 BOOT BOOTS 413.8 1142.1 -0.807 -0.932 AngloMale3 BOUT BOWED 864.4 1469.3 566.2 928.2 2.393 -0.277 0.275 -1.36 AngloMale3 BOUT BOWED 786.5 1502.5 497.2 898.1 1.84 -0.21 -0.215 -1.42 AngloMale3 BOUT BOWED 724.1 1379 531.9 985.5 1.397 -0.457 0.032 -1.245 AngloMale3 BOUT BOWED 819 1454.1 527.2 911.1 2.071 -0.307 -0.002 -1.394 AngloMale3 BOUT BOWED 681.6 1378.2 520.6 1080.5 1.095 -0.459 -0.049 -1.055 AngloMale3 BOUT BOWED 844.6 1534.4 634.1 890.8 2.252 -0.146 0.757 -1.435 AngloMale3 BITE BITE 688.2 1138 342.4 2259.3 1.142 -0.94 -1.314 1.305 AngloMale3 BITE BIDE 751.7 1167 565.2 1755.6 1.593 -0.882 0.268 0.296 AngloMale3 BITE BIDE 756.6 1217.8 527 1962.6 1.627 -0.78 -0.003 0.711 AngloMale3 BITE BIDE 710.6 1260.5 505 1828.4 1.301 -0.695 -0.159 0.442 AngloMale3 BITE BITE 659.4 1171.4 344.4 2217.6 0.937 -0.873 -1.3 1.221 AngloMale3 BITE BIDE 780.9 1172.5 491.4 1965.6 1.8 -0.871 -0.256 0.717 AngloMale3 BITE BIDE 794.9 1277.8 540 1931.6 1.899 -0.66 0.089 0.649 AngloMale3 BITE BIDE 674.6 1200 519 1860.9 1.045 -0.816 -0.06 0.507 AngloMale3 BAIT BADE 500.5 2068.9 342 2334 -0.191 0.924 -1.317 1.454 AngloMale3 BAIT BAIT 393.2 2158.5 326.3 2303.2 -0.953 1.103 -1.428 1.392 AngloMale3 BAIT BADE 499.6 2002.6 375.8 2301.9 -0.198 0.791 -1.077 1.39 AngloMale3 BAIT BADE 451.2 2036.1 359.3 2241.5 -0.541 0.858 -1.194 1.269 AngloMale3 BAIT BADE 486.3 2052.1 364.8 2277.3 -0.292 0.89 -1.155 1.341 AngloMale3 BAIT BAIT 451.4 1960.4 313.2 2419.5 -0.54 0.706 -1.521 1.625 AngloMale3 BAIT BADE 474.3 2072.5 356 2304.9 -0.377 0.931 -1.218 1.396 AngloMale3 BAIT BADE 490.1 2146.1 321.7 2382.6 -0.265 1.078 -1.461 1.551 AngloMale3 BOAT BODE 494 1075.1 377.5 877.1 -0.237 -1.066 -1.065 -1.462 AngloMale3 BOAT BODE 522.1 1143.7 389.8 978.6 -0.038 -0.928 -0.977 -1.259 AngloMale3 BOAT BODE 510.7 1223.4 412.7 1158.6 -0.119 -0.769 -0.815 -0.899 AngloMale3 BOAT BOAT 539.3 1016.2 373.9 893.1 0.084 -1.184 -1.09 -1.43 AngloMale3 BOAT BODE 474.1 1091.5 380.4 928.6 -0.379 -1.033 -1.044 -1.359 AngloMale3 BOAT BODE 548.1 1126.8 441.6 998.5 0.147 -0.962 -0.61 -1.219 AngloMale3 BOAT BODE 542.1 1108.4 387.8 1001.2 0.104 -0.999 -0.992 -1.214 AngloMale3 BOAT BOAT 515 1026.1 365.9 683.3 -0.088 -1.164 -1.147 -1.85 AngloMale3 BOY BOYDE 414.3 674.5 388.3 1880.8 -0.803 -1.867 -0.988 0.547 AngloMale3 BOY BOYDE 489 764.4 399.9 2062.2 -0.273 -1.688 -0.906 0.91 AngloMale3 BOY BOYDE 472.6 740.4 405.4 1879.4 -0.389 -1.736 -0.867 0.544 AngloMale3 BOY BOYDE 510.1 743.5 390.8 1818 -0.123 -1.729 -0.97 0.421 AngloMale3 BOY BOYDE 483.8 803 401.6 2005.8 -0.31 -1.61 -0.894 0.797 Anglomale4 BURT BURT 539 1374.8 -0.499 -0.619 Anglomale4 BAT BAT 813.5 1570.7 1.167 -0.129 Anglomale4 BEAT BEAT 306.5 2332.3 -1.91 1.776 Anglomale4 BUTT BUTT 701 1287.1 0.484 -0.838 Anglomale4 BET BED 660.1 1814.9 0.236 0.482 Anglomale4 BET BEN 757.6 1709.6 0.827 0.219 Anglomale4 BEAT BEANS 432.7 2385.8 -1.144 1.909 Anglomale4 BUTT BUDS 669.5 1331.6 0.293 -0.727 Anglomale4 BUTT BUNS 681 1296.9 0.362 -0.813 Anglomale4 BURT BURNT 650.1 1387.4 0.175 -0.587 Anglomale4 BURT BIRD 529.1 1506.1 -0.559 -0.29 Anglomale4 BIT BIT 498.1 1944.4 -0.748 0.806 Anglomale4 BAT BAD 804.2 1777.5 1.11 0.388 Anglomale4 BOT BOTTLE 785 1136.6 0.994 -1.214 Anglomale4 BOOT BOONE 465.3 1256.7 -0.947 -0.914 Anglomale4 BET BET 699 1769.7 0.472 0.369 Anglomale4 BIT BIDS 512.1 1998 -0.663 0.94 Anglomale4 BIT BIN 588.8 1891.3 -0.197 0.673 Anglomale4 BOOT BOOTS 386.6 1209.1 -1.424 -1.033 Anglomale4 BOT BONFIRE 746.9 1120.1 0.762 -1.256 Anglomale4 BEAT BEADS 338.3 2284.9 -1.717 1.657 Anglomale4 BAT BAD 910.3 1807 1.754 0.462 Anglomale4 BAN BANNED 815.3 1785.7 1.178 0.409 Anglomale4 BURT BURT 525.7 1536.2 -0.58 -0.215 Anglomale4 BOT BOUGHT 778.9 1110.1 0.957 -1.281 Anglomale4 BAT BAT 825.3 1696.6 1.238 0.186 Anglomale4 BEAT BEAT 338.1 2322.2 -1.719 1.75 Anglomale4 BUTT BUTT 748.2 1267 0.77 -0.888
154
Anglomale4 BET BED 682.8 1778.6 0.373 0.391 Anglomale4 BET BEN 819 1744.6 1.2 0.306 Anglomale4 BEAT BEANS 404.8 2512.4 -1.314 2.226 Anglomale4 BUTT BUDS 681.6 1302.3 0.366 -0.8 Anglomale4 BUTT BUNS 774.7 1282.9 0.931 -0.848 Anglomale4 BURT BURNT 649.6 1474.7 0.172 -0.369 Anglomale4 BURT BIRD 565.1 1589.2 -0.341 -0.083 Anglomale4 BIT BIT 537.1 2069.6 -0.511 1.119 Anglomale4 BAT BAD 892.4 1775.4 1.645 0.383 Anglomale4 BOOT BOONE 465.4 1215.9 -0.946 -1.016 Anglomale4 BET BET 731.9 1817.6 0.671 0.489 Anglomale4 BIT BIDS 490.9 2005.3 -0.791 0.958 Anglomale4 BIT BIN 572.1 1873.9 -0.298 0.629 Anglomale4 BOOT BOOTS 372.9 1354.6 -1.507 -0.669 Anglomale4 BOT BONFIRE 780.2 1073.2 0.965 -1.373 Anglomale4 BEAT BEADS 341.7 2344.1 -1.697 1.805 Anglomale4 BAT BAD 848.1 1717.3 1.377 0.238 Anglomale4 BAN BANNED 793 1875.9 1.042 0.634 Anglomale4 BOAT BOAT 620.2 1184 478.2 1084 -0.006 -1.096 -0.868 -1.346 Anglomale4 BOAT BODE 569.4 1111 429.5 995.9 -0.315 -1.278 -1.164 -1.566 Anglomale4 BOAT BOAT 680.9 1229.4 498.9 1020.1 0.362 -0.982 -0.743 -1.506 Anglomale4 BOAT BODE 600.6 1153.3 430.4 1006.5 -0.125 -1.173 -1.158 -1.54 Anglofemale1 BURT BURT 705.4 1586.4 0.061 -0.641 Anglofemale1 BAT BAT 1122.4 1926.2 1.941 -0.103 Anglofemale1 BEAT BEAT 314.1 2975.8 -1.703 1.558 Anglofemale1 BUTT BUTT 884 1662 0.866 -0.521 Anglofemale1 BET BED 853.8 2122.9 0.73 0.208 Anglofemale1 BET BEN 979.2 2133 1.295 0.224 Anglofemale1 BEAT BEANS 485.7 3008.6 -0.93 1.61 Anglofemale1 BUTT BUDS 784.2 1745.3 0.416 -0.39 Anglofemale1 BUTT BUNS 961.6 1528 1.216 -0.734 Anglofemale1 BURT BURNT 707.7 1449.6 0.071 -0.858 Anglofemale1 BURT BIRD 614.3 1504.9 -0.35 -0.77 Anglofemale1 BIT BIT 705.1 2514.1 0.059 0.828 Anglofemale1 BAT BAD 1080.7 1703.6 1.753 -0.456 Anglofemale1 BOT BOTTLE 953.5 1211.8 1.179 -1.234 Anglofemale1 BIT BID 577.9 2411.7 -0.514 0.665 Anglofemale1 BOOT BOONE 538.4 1699.9 -0.692 -0.461 Anglofemale1 BET BET 977.4 2028.3 1.287 0.058 Anglofemale1 BIT BIDS 596.8 2427.4 -0.429 0.69 Anglofemale1 BIT BIN 685.3 2353.9 -0.03 0.574 Anglofemale1 BOOT BOOTS 382.8 1717.1 -1.394 -0.434 Anglofemale1 BOT BONFIRE 741.4 1097.5 0.223 -1.415 Anglofemale1 BEAT BEADS 373.8 2984.7 -1.434 1.573 Anglofemale1 BAT BAD 1066.4 1716.6 1.688 -0.435 Anglofemale1 BAN BANNED 613.1 2842.4 -0.355 1.347 Anglofemale1 BEAT BEAD 422.3 3174 -1.215 1.872 Anglofemale1 BEAT BEAD 390.3 3005.5 -1.36 1.606 Anglofemale1 BIT BID 656.2 2454.8 -0.161 0.734 Anglofemale1 BIT BID 551.5 2392.9 -0.633 0.636 Anglofemale1 BET BED 866.9 2204.3 0.789 0.337 Anglofemale1 BET BED 849.7 2060.5 0.711 0.109 Anglofemale1 BAT BAD 1037.5 1947.6 1.558 -0.069 Anglofemale1 BAT BAD 1134.4 1747.4 1.995 -0.386 Anglofemale1 BOT BOTTLE 908.5 1292.1 0.976 -1.107 Anglofemale1 BOT BOTTLE 939.4 1190 1.116 -1.269 Anglofemale1 BUTT BUD 854.2 1657.8 0.732 -0.528 Anglofemale1 BUTT BUD 823.1 1713.2 0.591 -0.44 Anglofemale1 BURT BURT 687.8 1480.1 -0.019 -0.809 Anglofemale1 BOT BOUGHT 879.2 1280.6 0.844 -1.125 Anglofemale1 BAT BAT 1157.9 1751.5 2.101 -0.38 Anglofemale1 BEAT BEAT 383.4 3091.2 -1.391 1.741 Anglofemale1 BIT BID 629.8 2381.1 -0.28 0.617 Anglofemale1 BOOT BOONE 548.7 1576.4 -0.646 -0.657 Anglofemale1 BET BET 954.8 2141.6 1.185 0.238 Anglofemale1 BIT BIDS 633.1 2519.8 -0.265 0.837 Anglofemale1 BIT BIN 688 2406.9 -0.018 0.658
155
Anglofemale1 BOOT BOOTS 389.1 1804.9 -1.365 -0.295 Anglofemale1 BOT BONFIRE 842.1 1165.9 0.677 -1.307 Anglofemale1 BOOT BOONE 494.8 1508.7 -0.889 -0.764 Anglofemale1 BEAT BEADS 373.8 2953.4 -1.434 1.523 Anglofemale1 BAT BAD 1127.8 1846.5 1.965 -0.229 Anglofemale1 BAN BANNED 602.5 2679.4 -0.403 1.089 Anglofemale1 BEAT BEAD 391 3156.3 -1.357 1.844 Anglofemale1 BEAT BEAD 352.5 2991.4 -1.53 1.583 Anglofemale1 BIT BID 655.2 2459.1 -0.165 0.74 Anglofemale1 BIT BID 613.9 2375.4 -0.352 0.608 Anglofemale1 BET BED 829.3 2225.9 0.619 0.371 Anglofemale1 BET BED 815.2 2140.5 0.556 0.236 Anglofemale1 BOY BOYDE 426.1 779.3 472.2 1484.8 -1.198 -1.919 -0.991 -0.802 Anglofemale1 BAIT BADE 664.8 2550.9 400.3 3040.8 -0.122 0.886 -1.315 1.661 Anglofemale1 BAIT BAIT 507.9 2557.2 373.7 2611.3 -0.83 0.896 -1.435 0.981 Anglofemale1 BITE BITE 865.1 1537.9 402.8 2756.1 0.781 -0.718 -1.303 1.211 Anglofemale1 BITE BIDE 916.4 1277.9 746 2018.8 1.012 -1.13 0.244 0.043 Anglofemale1 BOUT BOWED 867.1 1768.9 876.2 1355.7 0.79 -0.352 0.831 -1.006 Anglofemale1 BOAT BOAT 665.6 1334 499.3 1043.5 -0.119 -1.041 -0.868 -1.501 Anglofemale1 BOAT BODE 663.7 1181.2 550 1097.4 -0.127 -1.283 -0.64 -1.415 Anglofemale1 BOAT BOWED 657.9 1336.8 473.4 987.1 -0.153 -1.036 -0.985 -1.59 Anglofemale1 BOAT BOWED 608.1 1331.4 479 1140.2 -0.378 -1.045 -0.96 -1.348 Anglofemale1 BAIT BADE 594.5 2518.1 420.6 3071.6 -0.439 0.834 -1.223 1.71 Anglofemale1 BAIT BADE 550.2 2505.4 404.8 2899.4 -0.639 0.814 -1.294 1.438 Anglofemale1 BITE BIDE 903.7 1445.6 603.9 2608.8 0.955 -0.864 -0.397 0.977 Anglofemale1 BITE BIDE 887.2 1305.7 716.2 2133.4 0.88 -1.086 0.11 0.225 Anglofemale1 BOY BOYDE 466 895.3 461.5 1314.3 -1.018 -1.735 -1.039 -1.072 Anglofemale1 BOY BOYDE 541.7 902 514 2298.8 -0.677 -1.725 -0.802 0.487 Anglofemale1 BOUT BOWED 882.2 1866.7 772.3 1346.4 0.858 -0.197 0.362 -1.021 Anglofemale1 BOUT BOWED 837.8 1855.9 823.4 1514.4 0.658 -0.214 0.593 -0.755 Anglofemale1 BAIT BADE 660.3 2189.1 416.7 2873.3 -0.142 0.313 -1.241 1.396 Anglofemale1 BAIT BAIT 545.6 2405.5 372.5 3094.6 -0.66 0.656 -1.44 1.747 Anglofemale1 BITE BITE 906 1544.5 437.5 2782.1 0.965 -0.707 -1.147 1.252 Anglofemale1 BOY BOYDE 532 809.8 468.3 1689.7 -0.721 -1.871 -1.008 -0.478 Anglofemale1 BITE BIDE 918.4 1429.9 719.5 2183 1.021 -0.889 0.124 0.303 Anglofemale1 BOUT BOWED 957.4 1787 704.6 1276.2 1.197 -0.324 0.057 -1.132 Anglofemale1 BOAT BOAT 646.5 1374.1 470 991.5 -0.205 -0.977 -1 -1.583 Anglofemale1 BOAT BODE 650.6 1185.6 577.1 1021.3 -0.186 -1.276 -0.518 -1.536 Anglofemale2 BURT BURT 557.2 1663.8 -0.525 -0.297 Anglofemale2 BOT BOUGHT 794.3 1366.6 0.901 -1.047 Anglofemale2 BAT BAT 932.5 1608.2 1.732 -0.438 Anglofemale2 BEAT BEAT 423.6 2504 -1.328 1.823 Anglofemale2 BUTT BUTT 817.3 1668.5 1.039 -0.285 Anglofemale2 BET BED 795.9 1696.4 0.911 -0.215 Anglofemale2 BET BEN 838.4 1858.7 1.166 0.194 Anglofemale2 BEAT BEANS 440.3 2611.6 -1.228 2.094 Anglofemale2 BUTT BUDS 668.4 1543.1 0.144 -0.602 Anglofemale2 BUTT BUNS 822.5 1459.2 1.071 -0.814 Anglofemale2 BURT BURNT 524.2 1614.5 -0.723 -0.422 Anglofemale2 BURT BIRD 517.8 1734.6 -0.762 -0.119 Anglofemale2 BIT BIT 524.9 2144.4 -0.719 0.915 Anglofemale2 BAT BAD 799.7 1712.7 0.934 -0.174 Anglofemale2 BIT BID 510.6 1946.4 -0.805 0.416 Anglofemale2 BOOT BOONE 558.1 1502.3 -0.519 -0.705 Anglofemale2 BET BET 698.4 1858.9 0.324 0.195 Anglofemale2 BIT BIDS 582.7 1991.6 -0.371 0.53 Anglofemale2 BIT BIN 593.4 1965.4 -0.307 0.464 Anglofemale2 BOOT BOOTS 405.5 1759.7 -1.437 -0.055 Anglofemale2 BOT BONFIRE 855.7 1205.6 1.27 -1.454 Anglofemale2 BEAT BEADS 398.8 2408.9 -1.477 1.583 Anglofemale2 BAT BAD 921.2 1699.2 1.664 -0.208 Anglofemale2 BAN BANNED 820.2 1931.6 1.057 0.378 Anglofemale2 BEAT BEAD 408.7 2587.5 -1.418 2.033 Anglofemale2 BEAT BEAD 434.5 2511.8 -1.263 1.842 Anglofemale2 BIT BID 587 1989.2 -0.345 0.524 Anglofemale2 BIT BID 525.3 1965.5 -0.716 0.464 Anglofemale2 BET BED 808.5 1932.7 0.986 0.381
156
Anglofemale2 BET BED 775.5 1920.7 0.788 0.351 Anglofemale2 BAT BAD 991.4 1686.6 2.086 -0.24 Anglofemale2 BAT BAD 921.7 1707 1.667 -0.188 Anglofemale2 BOT BOTTLE 842.8 1365.9 1.193 -1.049 Anglofemale2 BOT BOTTLE 811 1231.5 1.002 -1.388 Anglofemale2 BUTT BUD 740.4 1628.7 0.577 -0.386 Anglofemale2 BUTT BUD 704.8 1587.9 0.363 -0.489 Anglofemale2 BURT BURT 515 1692.6 -0.778 -0.225 Anglofemale2 BOT BOUGHT 845.9 1302.1 1.211 -1.21 Anglofemale2 BAT BAT 967.1 1630.8 1.94 -0.381 Anglofemale2 BEAT BEAT 420.5 2610.9 -1.347 2.093 Anglofemale2 BUTT BUTT 701.6 1668.6 0.344 -0.285 Anglofemale2 BET BED 743.2 1801 0.594 0.049 Anglofemale2 BET BEN 823.5 1859.1 1.077 0.195 Anglofemale2 BEAT BEANS 457.5 2591.2 -1.124 2.043 Anglofemale2 BUTT BUDS 667.3 1589.7 0.137 -0.484 Anglofemale2 BUTT BUNS 808.8 1491.7 0.988 -0.732 Anglofemale2 BURT BURNT 544.6 1701.8 -0.6 -0.201 Anglofemale2 BURT BIRD 501.5 1675 -0.86 -0.269 Anglofemale2 BIT BIT 582.5 2101.4 -0.373 0.807 Anglofemale2 BAT BAD 818.2 1604.9 1.045 -0.446 Anglofemale2 BOT BOTTLE 849.7 1201.8 1.234 -1.463 Anglofemale2 BIT BID 508.5 2002.6 -0.818 0.558 Anglofemale2 BOOT BOONE 541.9 1530.4 -0.617 -0.634 Anglofemale2 BET BET 671.6 1809.2 0.163 0.07 Anglofemale2 BIT BIDS 584.5 1722 -0.36 -0.15 Anglofemale2 BIT BIN 534.1 1871.7 -0.664 0.227 Anglofemale2 BOOT BOOTS 427 1786.8 -1.308 0.013 Anglofemale2 BOT BONFIRE 827.9 1338.2 1.103 -1.119 Anglofemale2 BEAT BEADS 383.3 2451 -1.57 1.689 Anglofemale2 BAT BAD 880.9 1598 1.422 -0.463 Anglofemale2 BAN BANNED 791.4 1916.7 0.884 0.341 Anglofemale2 BEAT BEAD 399.5 2588.5 -1.473 2.036 Anglofemale2 BEAT BEAD 373.6 2520 -1.629 1.863 Anglofemale2 BIT BID 579.3 2034.1 -0.392 0.637 Anglofemale2 BIT BID 503.3 2038.7 -0.849 0.649 Anglofemale2 BET BED 774.7 1928.2 0.783 0.37 Anglofemale2 BET BED 771.8 1843 0.766 0.155 Anglofemale2 BAT BAD 931 1604.1 1.723 -0.448 Anglofemale2 BAT BAD 875 1701 1.386 -0.203 Anglofemale2 BOT BOTTLE 843.6 1318.4 1.198 -1.169 Anglofemale2 BOT BOTTLE 781.9 1233.7 0.827 -1.383 Anglofemale2 BUTT BUD 749.3 1646.2 0.631 -0.342 Anglofemale2 BUTT BUD 639.3 1689.5 -0.031 -0.232 Anglofemale2 BOY BOYDE 533.3 925.2 504.3 1345 -0.668 -2.161 -0.843 -1.102 Anglofemale2 BAIT BADE 505 2279.6 436.5 2383 -0.839 1.257 -1.25 1.517 Anglofemale2 BAIT BAIT 409.1 2423.5 375.7 2493.8 -1.415 1.62 -1.616 1.797 Anglofemale2 BITE BITE 766.2 1661 501 2213.6 0.732 -0.304 -0.863 1.09 Anglofemale2 BITE BIDE 831.6 1447.4 645.8 2010.2 1.125 -0.843 0.008 0.577 Anglofemale2 BOUT BOWED 838.9 1598.8 659.6 1355.7 1.169 -0.461 0.091 -1.075 Anglofemale2 BOAT BOAT 608.7 1337.9 449.8 1266.4 -0.215 -1.12 -1.171 -1.3 Anglofemale2 BOAT BODE 584.7 1336.2 491.4 1268.5 -0.359 -1.124 -0.92 -1.295 Anglofemale2 BOAT BODE 738.8 1451.3 526.4 1312.7 0.567 -0.834 -0.71 -1.183 Anglofemale2 BOAT BODE 590.3 1458.3 466.2 1492.7 -0.326 -0.816 -1.072 -0.729 Anglofemale2 BAIT BADE 555.7 2247.6 496.8 2277.8 -0.534 1.176 -0.888 1.252 Anglofemale2 BAIT BADE 473.6 2129.5 475.3 2251 -1.027 0.878 -1.017 1.184 Anglofemale2 BITE BIDE 883.6 1521.6 661.1 1756.4 1.438 -0.656 0.1 -0.064 Anglofemale2 BITE BIDE 735.5 1655.1 661.9 1919 0.548 -0.319 0.105 0.347 Anglofemale2 BOY BOYDE 541.4 939.7 530.7 1961.9 -0.62 -2.124 -0.684 0.455 Anglofemale2 BOY BOYDE 437.8 988.1 540.2 1548.9 -1.243 -2.002 -0.627 -0.587 Anglofemale2 BOUT BOWED 824.1 1635.1 677 1486.8 1.08 -0.37 0.196 -0.744 Anglofemale2 BOY BOYDE 587 919.8 579.4 1862 -0.345 -2.175 -0.391 0.203 Anglofemale2 BAIT BADE 510.3 2327.3 439.5 2407 -0.807 1.377 -1.232 1.578 Anglofemale2 BAIT BAIT 408.7 2366.3 372.2 2467 -1.418 1.475 -1.637 1.729 Anglofemale2 BITE BITE 830.1 1753.4 485.2 2374.1 1.116 -0.071 -0.958 1.495 Anglofemale2 BITE BIDE 801.1 1526.2 640.4 1957.2 0.942 -0.645 -0.024 0.443 Anglofemale2 BOUT BOWED 853.5 1538.8 684.8 1401.4 1.257 -0.613 0.243 -0.959
157
Anglofemale2 BOAT BOAT 616.3 1413.7 470.8 1182 -0.169 -0.928 -1.044 -1.513 Anglofemale2 BOAT BODE 533.8 1359.4 486.5 1333.2 -0.665 -1.065 -0.95 -1.132 Anglofemale2 BOAT BODE 594.3 1490.8 505.3 1337.7 -0.302 -0.734 -0.837 -1.12 Anglofemale2 BOAT BODE 549.6 1466 496.3 1504 -0.57 -0.796 -0.891 -0.701 Anglofemale2 BAIT BADE 522 2444.7 456.2 2461 -0.736 1.673 -1.132 1.714 Anglofemale2 BAIT BADE 487.5 2426.8 417.1 2539.5 -0.944 1.628 -1.367 1.912 Anglofemale2 BITE BIDE 836.8 1588.1 615.9 2075.5 1.157 -0.488 -0.172 0.742 Anglofemale2 BITE BIDE 767.9 1591.9 645.7 1898.4 0.742 -0.479 0.008 0.295 Anglofemale2 BOY BOYDE 590.5 944 526.2 1711.3 -0.324 -2.114 -0.711 -0.177 Anglofemale2 BOY BOYDE 460.9 1029.3 504.6 1753.1 -1.104 -1.898 -0.841 -0.072 Anglofemale2 BOUT BOWED 859 1764.2 753.9 1468.1 1.29 -0.044 0.658 -0.791 Anglofemale2 BOUT BOWED 735.4 1679.5 671.4 1559 0.547 -0.258 0.162 -0.562 Anglofemale3 BURT BURT 557 1717.8 -0.713 -0.284 Anglofemale3 BOT BOUGHT 968.2 1346.8 1.098 -0.986 Anglofemale3 BAT BAT 1029.2 1712.7 1.367 -0.294 Anglofemale3 BEAT BEAT 309.1 2898.7 -1.805 1.949 Anglofemale3 BUTT BUTT 828.8 1649.9 0.484 -0.413 Anglofemale3 BET BED 835.6 1982.5 0.514 0.216 Anglofemale3 BET BEN 911.1 2110.1 0.846 0.458 Anglofemale3 BEAT BEANS 502.1 3043.4 -0.955 2.223 Anglofemale3 BUTT BUDS 855.5 1709.8 0.601 -0.299 Anglofemale3 BUTT BUNS 987.5 1626.2 1.183 -0.457 Anglofemale3 BURT BURNT 718.9 1557.7 0 -0.587 Anglofemale3 BURT BIRD 548 1872.5 -0.753 0.008 Anglofemale3 BIT BIT 543.9 2460 -0.771 1.12 Anglofemale3 BAT BAD 971 1647.5 1.11 -0.417 Anglofemale3 BOT BOTTLE 846.1 1027.6 0.56 -1.59 Anglofemale3 BOOT BOONE 363.3 1455.3 -1.566 -0.781 Anglofemale3 BET BET 930.4 1946.6 0.931 0.149 Anglofemale3 BIT BIDS 515 2352.1 -0.898 0.915 Anglofemale3 BIT BIN 720 2271.2 0.005 0.762 Anglofemale3 BOOT BOOTS 403.7 1792.9 -1.389 -0.142 Anglofemale3 BOT BONFIRE 916.4 1245.9 0.87 -1.177 Anglofemale3 BEAT BEADS 341.2 2936.3 -1.664 2.02 Anglofemale3 BAT BAD 1029.8 1677 1.369 -0.361 Anglofemale3 BAN BANNED 729.9 2531.4 0.048 1.255 Anglofemale3 BURT BURT 578.1 1774.3 -0.62 -0.177 Anglofemale3 BOT BOUGHT 941.9 1393.8 0.982 -0.897 Anglofemale3 BAT BAT 1027.2 1660.4 1.358 -0.393 Anglofemale3 BEAT BEAT 307.3 2770.7 -1.813 1.707 Anglofemale3 BUTT BUTT 886.7 1674.1 0.739 -0.367 Anglofemale3 BET BED 828.2 1936 0.481 0.128 Anglofemale3 BET BEN 847.8 2017.6 0.568 0.283 Anglofemale3 BEAT BEANS 485.2 2993.6 -1.03 2.129 Anglofemale3 BUTT BUDS 881.1 1569 0.714 -0.566 Anglofemale3 BUTT BUNS 954 1607.6 1.035 -0.493 Anglofemale3 BURT BURNT 764.6 1601.8 0.201 -0.504 Anglofemale3 BURT BIRD 562.7 1838.5 -0.688 -0.056 Anglofemale3 BIT BIT 569.5 2425.8 -0.658 1.055 Anglofemale3 BAT BAD 1023.9 1588 1.343 -0.53 Anglofemale3 BOT BOTTLE 838.5 1129.6 0.527 -1.397 Anglofemale3 BOOT BOONE 521.9 1451.4 -0.868 -0.788 Anglofemale3 BET BET 926.1 1853.3 0.912 -0.028 Anglofemale3 BIT BIDS 562.8 2261.2 -0.688 0.744 Anglofemale3 BIT BIN 605.8 2290.3 -0.498 0.799 Anglofemale3 BOOT BOOTS 418.7 1907.8 -1.322 0.075 Anglofemale3 BOT BONFIRE 970.3 1305.4 1.107 -1.064 Anglofemale3 BEAT BEADS 387.2 2912.6 -1.461 1.976 Anglofemale3 BAT BAD 1046.5 1694.6 1.443 -0.328 Anglofemale3 BAN BANNED 901.7 2199.9 0.805 0.628 Anglofemale3 BOAT BOAT 703.5 1396.6 477.7 1130.9 -0.068 -0.892 -1.063 -1.394 Anglofemale3 BOAT BODE 564 1305.4 407.4 1072.1 -0.682 -1.064 -1.372 -1.505 Anglofemale3 BOAT BOAT 718.7 1351.1 486.9 1131.8 -0.001 -0.978 -1.022 -1.393 Anglofemale3 BOAT BODE 568.2 1145.8 445.4 888.6 -0.664 -1.366 -1.205 -1.853 Anglofemale4 BURT BURT 664.4 1864.2 -0.292 -0.262 Anglofemale4 BOT BOUGHT 927.6 1331.1 0.997 -1.236 Anglofemale4 BAT BAT 1073.8 1843.4 1.713 -0.3
158
Anglofemale4 BEAT BEAT 415.3 3021.6 -1.512 1.852 Anglofemale4 BUTT BUTT 915.8 1799.9 0.939 -0.38 Anglofemale4 BET BED 865.3 2081.1 0.692 0.134 Anglofemale4 BET BEN 1089.5 2012.3 1.79 0.008 Anglofemale4 BEAT BEANS 453.4 3123.4 -1.326 2.038 Anglofemale4 BUTT BUDS 812.3 1816 0.432 -0.35 Anglofemale4 BUTT BUNS 961.5 1730.1 1.163 -0.507 Anglofemale4 BURT BURNT 714 1766.3 -0.049 -0.441 Anglofemale4 BURT BIRD 675.3 1819.5 -0.239 -0.344 Anglofemale4 BIT BIT 590.9 2336 -0.652 0.599 Anglofemale4 BAT BAD 1007.2 1866.1 1.387 -0.259 Anglofemale4 BIT BID 636.8 2395.5 -0.427 0.708 Anglofemale4 BOOT BOONE 543.9 1604.4 -0.882 -0.737 Anglofemale4 BET BET 932.1 2071.8 1.019 0.117 Anglofemale4 BIT BIDS 644.8 2408.4 -0.388 0.732 Anglofemale4 BIT BIN 597.8 2346.4 -0.618 0.618 Anglofemale4 BOOT BOOTS 438.4 1706.7 -1.399 -0.55 Anglofemale4 BOT BONFIRE 832.7 1270.1 0.532 -1.348 Anglofemale4 BEAT BEADS 415.1 2947.1 -1.513 1.716 Anglofemale4 BAT BAD 1012.3 1851.4 1.412 -0.286 Anglofemale4 BAN BANNED 814.9 2378.6 0.445 0.677 Anglofemale4 BURT BURT 671.5 2023.4 -0.257 0.028 Anglofemale4 BOT BOUGHT 1020.1 1321.3 1.45 -1.254 Anglofemale4 BAT BAT 1062.7 1821.2 1.658 -0.341 Anglofemale4 BEAT BEAT 413.2 3048.3 -1.523 1.9 Anglofemale4 BUTT BUTT 894.5 1765.5 0.835 -0.443 Anglofemale4 BET BED 835.2 2059.9 0.544 0.095 Anglofemale4 BET BEN 997 2004.3 1.337 -0.007 Anglofemale4 BEAT BEANS 444.5 3046.2 -1.369 1.897 Anglofemale4 BUTT BUDS 896 1770.2 0.842 -0.434 Anglofemale4 BUTT BUNS 873.9 1714 0.734 -0.537 Anglofemale4 BURT BURNT 712.4 1804.3 -0.057 -0.372 Anglofemale4 BURT BIRD 691.5 1942.6 -0.16 -0.119 Anglofemale4 BIT BIT 599 2295 -0.613 0.524 Anglofemale4 BAT BAD 1002.7 1919.8 1.365 -0.161 Anglofemale4 BOT BOTTLE 834.7 1258 0.542 -1.37 Anglofemale4 BIT BID 640.3 2441.1 -0.41 0.791 Anglofemale4 BOOT BOONE 556.1 1654.5 -0.823 -0.645 Anglofemale4 BET BET 880.1 2087.4 0.764 0.145 Anglofemale4 BIT BIDS 640.3 2462.5 -0.41 0.83 Anglofemale4 BIT BIN 723.7 2321.5 -0.002 0.573 Anglofemale4 BOOT BOOTS 425.6 1940 -1.462 -0.124 Anglofemale4 BOT BONFIRE 978.1 1425.7 1.244 -1.063 Anglofemale4 BEAT BEADS 432.1 3026.1 -1.43 1.86 Anglofemale4 BAT BAD 1003.3 1833.1 1.368 -0.319 Anglofemale4 BAN BANNED 808 2314.3 0.411 0.56 Anglofemale4 BEAT BEAD 460.5 3058.8 -1.291 1.92 Anglofemale4 BEAT BEAD 446.9 3124 -1.357 2.039 Anglofemale4 BIT BID 648.7 2459.7 -0.369 0.825 Anglofemale4 BIT BID 598.1 2400.8 -0.617 0.718 Anglofemale4 BET BED 818.8 2136.2 0.464 0.234 Anglofemale4 BET BED 848.8 2083.7 0.611 0.138 Anglofemale4 BAT BAD 993.2 1899.3 1.318 -0.198 Anglofemale4 BAT BAD 991.9 1829.6 1.312 -0.326 Anglofemale4 BOT BOTTLE 912.3 1307.9 0.922 -1.279 Anglofemale4 BOT BOTTLE 874.3 1299.9 0.736 -1.293 Anglofemale4 BUTT BUD 829 1868 0.514 -0.256 Anglofemale4 BUTT BUD 835.8 1761.4 0.547 -0.45 Anglofemale4 BOY BOYDE 542.5 908.4 543 2397.8 -0.889 -2.008 -0.887 0.712 Anglofemale4 BAIT BADE 609.1 2666.4 398.7 2745.1 -0.563 1.203 -1.594 1.347 Anglofemale4 BAIT BAIT 468.9 2667.8 418.6 2982.5 -1.25 1.205 -1.496 1.78 Anglofemale4 BITE BITE 979.9 1847.3 421.2 2919.5 1.253 -0.293 -1.483 1.665 Anglofemale4 BITE BIDE 994.8 1685.5 673.4 2361.4 1.326 -0.589 -0.248 0.646 Anglofemale4 BOUT BOWED 995.6 1738.7 748.8 1383.8 1.33 -0.492 0.121 -1.14 Anglofemale4 BOAT BOAT 737.1 1501.7 512 1232.3 0.064 -0.925 -1.039 -1.417 Anglofemale4 BOAT BODE 604.8 1222.1 488.9 1263 -0.584 -1.435 -1.152 -1.361 Anglofemale4 BOY BOYDE 492.9 930.9 520.3 1465.3 -1.132 -1.967 -0.998 -0.991
159
Anglofemale4 BAIT BADE 568.8 2725.4 466.5 2729 -0.76 1.311 -1.261 1.317 Anglofemale4 BAIT BAIT 449 2659.3 410.9 2922.9 -1.347 1.19 -1.534 1.671 Anglofemale4 BITE BITE 926.9 1855.7 466.7 2775.1 0.993 -0.278 -1.26 1.401 Anglofemale4 BITE BIDE 981.8 1511.1 706.9 2415.6 1.262 -0.907 -0.084 0.745 Anglofemale4 BOUT BOWED 1009.9 1846.8 719.2 1374.3 1.4 -0.294 -0.024 -1.157 Anglofemale4 BOAT BOAT 735.9 1544.7 546.9 1255.7 0.058 -0.846 -0.868 -1.374 Anglofemale4 BOAT BODE 608.7 1351.8 504.3 1377.2 -0.565 -1.198 -1.076 -1.152 Anglofemale4 BOAT BODE 683.2 1571.7 557.1 1243.9 -0.2 -0.797 -0.818 -1.395 Anglofemale4 BOAT BODE 669.2 1472.1 448.5 1189.9 -0.269 -0.979 -1.35 -1.494 Anglofemale4 BAIT BADE 598.1 2564.5 487.7 2617.8 -0.617 1.017 -1.158 1.114 Anglofemale4 BAIT BADE 547.5 2651.9 444 2772.1 -0.865 1.176 -1.372 1.396 Anglofemale4 BITE BIDE 1001.5 1613.3 688 2369.9 1.359 -0.721 -0.177 0.661 Anglofemale4 BITE BIDE 967 1641.1 698.7 2426.9 1.19 -0.67 -0.124 0.765 Anglofemale4 BOY BOYDE 504.6 1002.9 493.1 1263.7 -1.075 -1.836 -1.131 -1.359 Anglofemale4 BOY BOYDE 512.2 965.1 551.8 1406.5 -1.038 -1.905 -0.844 -1.098 Anglofemale4 BOUT BOWED 902.6 1712.5 707.3 1497.4 0.874 -0.54 -0.082 -0.932 Anglofemale4 BOUT BOWED 879.7 1914.4 734.1 1369.1 0.762 -0.171 0.049 -1.167
160
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