Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community
Abstract
:1. Introduction
2. Background Studies
2.1. The Southeast as a New Dialect Region/“New Destination” Community
2.2. New Dialect Formation in Language Contact Settings
2.3. The Initial Variable Swarm
2.3.1. Realization of Intervocalic /bdg/
2.3.2. Vowel Space and Convex Hull Area (CHA)
2.3.3. Prosodic Rhythm (nPVI)
2.3.4. Bilingual Discourse Markers (DMs)
2.3.5. Summary of the Initial Swarm
2.4. New Swarm Variables
2.4.1. Subject Pronoun Expression (SPE)
2.4.2. Code Switching
- Single word switch: Ella estaba bien surprised ‘She was very surprised’.
- Intersentential switch: ¿Cómo te puedo decir? The right path ‘How can I say it (for you)? The right path’.
- Intrasentential switch: O como cuando van hunting in the woods ‘Or like when they go hunting in the woods’.
2.4.3. Filled Pauses
2.4.4. The Realization of Orthographic b~v
2.4.5. Growing the Swarm
3. Materials and Methods
3.1. General Methods
3.2. Methodology: Subject Pronoun Realization (SPE)
3.3. Methodology: Code Switching (CS)
3.4. Methodology: Filled Pauses (FP)
3.5. Methodology: The Realization of Orthographic <b/v>
4. Results
4.1. Subject Pronoun Expression (SPE)
Factor | Log Odds | N | % Overt Pro | p-Value |
---|---|---|---|---|
Person/Number and Definiteness | <0.001 * | |||
él-ella.definite | 1.902 | 267 | 38.2 | |
1st singular—yo | 0.847 | 1214 | 21.6 | |
3rd plural—ellos-ellas.definite | 0.567 | 209 | 18.2 | |
2nd singular—tú.definite | −0.352 | 58 | 8.6 | |
2nd singular—tú.indefinite | −0.494 | 151 | 6.6 | |
1st plural—nosotros-nosotras | −0.589 | 292 | 8.6 | |
3rd plural—ellos-ellas.indefinite | −1.881 | 74 | 2.7 | |
Switch Reference | <0.001 * | |||
Complete switch | 0.643 | 945 | 25.5 | |
Partial switch | −0.284 | 181 | 18.2 | |
No switch | −0.359 | 1139 | 15.0 | |
Reflexivity | <0.001 * | |||
Non-reflexive | 0.392 | 1997 | 20.7 | |
Reflexive | −0.392 | 268 | 11.6 | |
Distinctiveness of TAM | <0.001 * | |||
Non-distinctive | 0.248 | 475 | 26.1 | |
Distinctive | −0.248 | 1790 | 17.9 | |
Lexical Content | 0.002 * | |||
Estimative | 0.676 | 99 | 43.4 | |
Stative | −0.132 | 562 | 22.0 | |
External activity | −0.220 | 1229 | 17.4 | |
Mental activity | −0.324 | 375 | 17.1 | |
Generation | 0.094 | |||
G1 | 0.238 | 1173 | 19.9 | |
G2 | −0.238 | 1092 | 19.2 | |
Sex | 0.24 | |||
Female | 0.173 | 1282 | 21.6 | |
Male | −0.173 | 983 | 17 | |
Region | 0.60 | |||
Central America | 0.08 | 686 | 24.2 | |
Mexico | −0.08 | 1579 | 17.6 |
N | df | intercept | overall prop | AIC | R2.fixed | R2.random | R2.total |
2265 | 18 | −2.348 | 0.196 | 1970.175 | 0.224 | 0.063 | 0.287 |
4.2. Code Switching
4.3. Filled Pauses (FPs)
4.4. The Realization of Orthographic <b/v>
5. Discussion: The Swarm Analysis
5.1. Speaker Rankings
5.2. Correlations across Variables
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Participant | Sex | Birth Year | Generation | Region | Years in U.S. |
---|---|---|---|---|---|
2010-16 | F | 1957 | G1 | CAm | 25 |
2014-13 | M | 1985 | G1 | CAm | 19 |
2012-01 | F | 1957 | G1 | Mex | 33 |
2013-21 | F | 1983 | G1 | Mex | 1 |
2011-05 | F | 1988 | G1 | Mex | 10 |
2013-03 | M | 1993 | G1 | Mex | 10 |
2012-09 | F | 1992 | G1 | Mex | 9 |
2013-15 | M | 1962 | G1 | Mex | 35 |
2013-24 | M | 1984 | G1 | Mex | 2 |
2013-23 | M | 1981 | G1 | Mex | 2 |
2011-18 | M | 1992 | G1 | Mex | 3 |
2013-26 | M | 1982 | G1 | Mex | 1 |
2015-08 | F | 1992 | G2 | Mex | 20 |
2011-21 | F | 1989 | G2 | CAm | Since birth |
2014-10 | F | 1992 | G2 | CAm | Since birth |
2012-15 | F | 1988 | G2 | CAm | Since birth |
2012-22 | F | 1992 | G2 | CAm | Since birth |
2012-08 | F | 1989 | G2 | CAm | Since birth |
2013-19 | M | 1989 | G2 | Mex | Since birth |
2013-18 | F | 1993 | G2 | Mex | Since birth |
2014-19 | F | 1992 | G2 | Mex | Since birth |
2013-28 | M | 1991 | G2 | Mex | Since birth |
2013-02 | M | 1992 | G2 | Mex | Since birth |
Appendix B
Factor | Log Odds | N | % Overt Pro | p-Value |
---|---|---|---|---|
Person/Number and Definiteness | <0.001 * | |||
él-ella.definite | 3.659 | 92 | 38.0 | |
yo | 2.971 | 502 | 24.7 | |
ellos-ellas.definite | 2.594 | 50 | 20.0 | |
tú.definite | 1.860 | 30 | 13.3 | |
nosotros-nosotras | 1.773 | 157 | 10.2 | |
tú.indefinite | 0.883 | 104 | 3.8 | |
ellos-ellas.indefinite | −13.740 | 46 | 0.0 | |
Switch Reference | <0.001 * | |||
Complete switch | 0.693 | 421 | 24.5 | |
No switch | −0.210 | 480 | 16.0 | |
Partial switch | −0.484 | 80 | 16.2 | |
Lexical Content | 0.0047 * | |||
Estimative | 0.916 | 46 | 52.2 | |
Stative | −0.164 | 221 | 23.1 | |
External activity | −0.358 | 555 | 16.2 | |
Mental activity | −0.393 | 159 | 17.6 | |
Distinctiveness of TAM | 0.013 * | |||
Non-distinctive | 0.27 | 176 | 26.7 | |
Distinctive | −0.27 | 805 | 18.1 | |
Reflexivity | 0.0185 * | |||
Non-reflexive | 0.36 | 865 | 20.7 | |
Reflexive | −0.36 | 116 | 12.1 |
n | df | intercept | overall proportion | AIC | R2.fixed | R2.random | R2.total |
981 | 15 | −4.187 | 0.197 | 859.63 | 0.781 | 0.012 | 0.793 |
Factor | Log Odds | N | % Overt Pro | p-Value |
---|---|---|---|---|
Person/Number and Definiteness | <0.001 * | |||
él-ella.definite | 8.721 | 25 | 56.0 | |
yo | 7.637 | 107 | 20.6 | |
ellos-ellas.definite | 6.251 | 21 | 9.5 | |
nosotros-nosotras | 5.868 | 25 | 12 | |
tú.definite | −8.910 | 3 | 0.0 | |
ellos-ellas.indefinite | −9.191 | 10 | 0.0 | |
tú.indefinite | −10.376 | 1 | 0.0 | |
Switch Reference | <0.001 * | |||
Partial switch | 0.613 | 17 | 35.3 | |
Complete switch | 0.567 | 87 | 28.7 | |
No switch | −1.180 | 88 | 11.4 | |
Lexical Content | 0.009 * | |||
Stative | 5.187 | 62 | 37.1 | |
External activity | 4.158 | 98 | 16.3 | |
Mental activity | 3.310 | 28 | 7.1 | |
Estimative | −12.655 | 4 | 0.0 | |
Distinctiveness of TAM | 0.849 | |||
Non-distinctive | 0.049 | 53 | 26.4 | |
Distinctive | −0.049 | 139 | 119.4 | |
Reflexivity | 0.144 | |||
Non-reflexive | 0.463 | 158 | 23.4 | |
Reflexive | −0.463 | 34 | 11.8 |
n | df | intercept | overall proportion | AIC | R2.fixed | R2.random | R2.total |
192 | 15 | −13.359 | 0.214 | 173.926 | 0.88 | 0.0 | 0.88 |
Factor | Log Odds | N | % Overt Pro | p-Value |
---|---|---|---|---|
Person/Number and Definiteness | <0.001 * | |||
él-ella.definite | 5.596 | 13 | 15.4 | |
yo | 5.137 | 396 | 17.9 | |
ellos-ellas.definite | 5.076 | 60 | 15.0 | |
ellos-ellas.indefinite | 4.999 | 12 | 8.3 | |
tú.indefinite | 3.910 | 41 | 4.9 | |
tú.definite | −11.768 | 24 | 0.0 | |
nosotros-nosotras | −12.951 | 52 | 0.0 | |
Distinctiveness of TAM | <0.001 * | |||
Non-distinctive | 0.564 | 106 | 20.8 | |
Distinctive | −0.564 | 492 | 12.8 | |
Lexical Content | 0.00144 * | |||
Estimative | 1.269 | 34 | 50.0 | |
Mental activity | −0.247 | 125 | 15.2 | |
External activity | −0.348 | 310 | 10.6 | |
Stative | −0.674 | 129 | 12.4 | |
Reflexivity | 0.00163 * | |||
Non-reflexive | 1.151 | 535 | 15.7 | |
Reflexive | −1.151 | 63 | 1.6 | |
Switch Reference | 0.0431 * | |||
Complete switch | 0.646 | 236 | 18.2 | |
No switch | 0.101 | 315 | 12.7 | |
Partial switch | −0.747 | 47 | 4.3 |
n | df | intercept | overall proportion | AIC | R2.fixed | R2.random | R2.total |
598 | 15 | −7.662 | 0.142 | 420.84 | 0.905 | 0.013 | 0.918 |
Factor | Log Odds | N | % Overt Pro | p-Value |
---|---|---|---|---|
Person/Number and Definiteness | <0.001 * | |||
tú.definite | 10.809 | 1 | 100.0 | |
tú.indefinite | 2.161 | 5 | 80.0 | |
él-ella.definite | −0.570 | 137 | 37.2 | |
ellos-ellas.definite | −2.268 | 78 | 21.8 | |
yo | −2.424 | 209 | 21.5 | |
ellos-ellas.indefinite | −3.632 | 6 | 16.7 | |
nosotros-nosotras | −4.077 | 58 | 10.3 | |
Switch Reference | <0.001 * | |||
Complete switch | 0.885 | 201 | 34.8 | |
Partial switch | −0.127 | 37 | 32.4 | |
No switch | −0.757 | 256 | 16.8 | |
Lexical Content | 0.481 | |||
External activity | 0.404 | 266 | 28.2 | |
Stative | 0.162 | 150 | 22.0 | |
Mental activity | 0.053 | 63 | 23.8 | |
Estimative | −0.619 | 15 | 13.3 | |
Distinctiveness of TAM | 0.713 | |||
Non-distinctive | 0.05 | 140 | 29.3 | |
Distinctive | −0.05 | 354 | 23.7 | |
Reflexivity | 0.428 | |||
Non-reflexive | 0.153 | 439 | 25.7 | |
Reflexive | −0.153 | 55 | 21.8 |
n | df | intercept | overall proportion | AIC | R2.fixed | R2.random | R2.total |
494 | 15 | 0.308 | 0.253 | 485.02 | 0.322 | 0.133 | 0.455 |
1 | Note that many lexical FPs are also analyzable as discourse markers. |
2 | It should be noted that in our own data, the majority of the auditorily labiodental tokens were also approximants rather than fricatives. Thus, the presence of the labiodental approximant [ʋ] complicates the classification of potential contact forms, as a bilingual speaker could produce a hybrid form that utilizes the labiodental point of articulation from English alongside the approximant mode of articulation from Spanish. In this way, bilingual labiodentals may not correspond exactly with English fricative /v/. |
3 | Technical aspects regarding FASE are described in greater depth in Wilbanks (2015) and Ronquest et al. (2020). Regarding the reliability of automatic alignment with FASE, Wilbanks (2015) compares FASE alignment to the alignment produced by trained human phoneticians. He finds that the refined, adapted FASE segmentation was similar to human segmentation: boundary differences between the two human coders had a mean of 14.47 ms, compared to a mean difference of 20.81 ms between the human coders and the trained FASE model. |
4 | For example, the full model AIC was compared to the AIC of a model with all variables except one (e.g., Switch Reference). The difference in AIC values indicates the importance of the variable in the full model, with larger differences denoting a stronger effect on the model. Kapatsinski (2012) demonstrates why this method is superior to the range of coefficients, the traditional method of determining the constraint hierarchy in sociolinguistic studies, which can be biased towards variables/factors with more levels. |
5 | An acoustic analysis of phonological filled pauses, as well as an examination of lexical pauses (e.g., sea, este) and silent pauses is forthcoming. |
6 | Data are frequently skewed to the right when there is a lower boundary to the measurement; in this case, COG cannot be a negative number. See https://www.itl.nist.gov/div898/handbook/eda/section3/histogr6.htm, accessed on 4 March 2023. |
7 | There are only two Central American G1 speakers in the present corpus, and some of these variables may achieve significance in a larger sample. Still, the match between Mexican and Central American G1 speakers speaks to the robustness of these constraints across Spanish varieties, even when few speakers are analyzed. |
8 | However, in some contexts, bilinguals have been found to produce fewer FPs than monolinguals but higher rates of silent pauses, which were not studied here (García-Amaya 2022). Additionally, although not coded in our data, impressionistically some monolinguals may have compensated for lower rates of phonological FPs by using more lexical FPs (pues, este, etc.). Further study is warranted and underway. |
9 | A more detailed analysis of <b> and <v> in NC Spanish is forthcoming. |
10 | http://www.sthda.com/english/wiki/correlation-matrix-an-r-function-to-do-all-you-need, accessed on 4 March 2023. |
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Variable | Levels |
---|---|
Dependent | |
SPE | Overt Null |
Independent | |
Person/number/definiteness | Yo Tú (definite) Tú (indefinite) Él/ella (definite) Nosotros/nosotras Ellos/ellas (definite) Ellos/ellas (indefinite) |
Distinctiveness of TAM | Distinctive Non-distinctive |
Switch reference | Complete switch Partial switch No switch |
Lexical content | External activity Mental activity Estimative Stative |
Generation | G1 G2 |
Sex | Male Female |
Region of origin | Mexico Central America |
Speaker | Random intercept |
Variable | Levels |
---|---|
Dependent | |
Code-switch type | Sentence-level code switching (Intrasentential + intersentential) (analysis 1) Word Intrasentential (analysis 2) Intersentential + Word |
Independent | |
Generation | G1 G2 |
Sex | Male Female |
Region of origin | Mexico Central America |
Speaker | Random intercept |
Variable | Levels |
---|---|
Dependent | |
Filled pause vowel | [ə] + [a] [e] |
Independent | |
Generation | G1 G2 |
Sex | Male Female |
Region of origin | Mexico Central America |
Speaker | Random Intercept |
Variable | Levels |
---|---|
Dependent | |
COG | Continuous variable (analysis 1) COG difference <v>—<b> (analysis 2) |
Independent | |
Following vowel | [i] [e] [a] [o] [u] |
Word position | Initial Medial |
Grapheme | <b> <v> |
Generation | G1 G2 |
Sex | Male Female |
Region of origin | Mexico Central America |
Speaker | Random intercept |
Word | Random intercept |
Mexican G1 | Central American G1 | Mexican G2 | Central American G2 |
---|---|---|---|
1. Person/Number * | 1. Person/Number * | 1. Person/Number * | 1. Person/Number * |
2. Switch * | 2. Switch * | 2. Lexical Content * | 2. Switch * |
3. Lexical Content * | 3. Lexical Content * | 3. TMA Distinctive * | 3. Lexical Content |
4. TMA Distinctive * | 4. TMA Distinctive | 4. Reflexivity * | 4. TMA Distinctive |
5. Reflexivity * | 5. Reflexivity | 5. Switch * | 5. Reflexivity |
Switch Type | N | % of Data |
---|---|---|
Single word | 702 | 90.1% |
Intersentential | 57 | 7.3% |
Intrasentential | 20 | 2.6% |
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Michnowicz, J.; Ronquest, R.; Chetty, S.; Green, G.; Oliver, S. Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community. Languages 2023, 8, 168. https://doi.org/10.3390/languages8030168
Michnowicz J, Ronquest R, Chetty S, Green G, Oliver S. Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community. Languages. 2023; 8(3):168. https://doi.org/10.3390/languages8030168
Chicago/Turabian StyleMichnowicz, Jim, Rebecca Ronquest, Sarah Chetty, Georgia Green, and Stephanie Oliver. 2023. "Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community" Languages 8, no. 3: 168. https://doi.org/10.3390/languages8030168
APA StyleMichnowicz, J., Ronquest, R., Chetty, S., Green, G., & Oliver, S. (2023). Spanish in the Southeast: What a Swarm of Variables Can Tell Us about a Newly Forming Bilingual Community. Languages, 8(3), 168. https://doi.org/10.3390/languages8030168