List of tables
Chapter 2
Table 1.
Optional use of ‑le by native speakers
28
Table 2.
Use of ‑le by CSL learners: Internal constraints
29
Table 3.
Use of ‑le by CSL learners: External constraints
30
Table 4.
Optional use of –le by CSL learners
31
Table 5.
Post-verbal ‑le use by native speakers (optional)
32
Table 7.
Sentence final ‑le use by native speakers (optional)
33
Table 8.
Sentence final ‑le by CSL learners (optional)
34
Table 9.
Errors of ‑le use
34
Chapter 3
Table 1.
Selection of phonological variables that distinguish MSM, NorM, SSM, and CSM varieties of Mandarin
46
Table 2.
Major B = background C = categories for VOCS Mandarin participants
51
Table 3.
Stimuli variation across guises using the example “画(儿
)上有五个小星星” (‘The picture has five little stars.’)
52
Table 4.
Summary of target items analyzed in the picture-naming task
54
Table 5.
Overall realization distribution and fixed effects included in best-fit generalized linear mixed-effects models for
retroflex (sh, zh, ch), dental (s, z, c) and palatal variables (x), with random effect of participant
60
Chapter 4
Table 1.
Frequency (%) of NOM argument realizations, classified by linguistic factors
78
Table 2.
Frequency (%) of NOM argument realization patterns in animate and inanimate NPs, classified by verb type
80
Table 3.
Frequency (%) of ACC argument realizations, classified by linguistic factors
81
Table 4.
Frequency (%) of Type 1 Variation in NOM and ACC, classified by linguistic factors
83
Table 5.
Frequency (%) of NOM and ACC argument realizations, classified by source and learner type
85
Table 6.
Multinomial logistic regression analysis of type 2 variation by learner type
87
Table 7.
Frequency (%) of type 1 Variation in NOM and ACC, classified by source
88
Table 8.
Logistic regression analysis of type 1 variation for NOM and ACC by learner type
89
Chapter 5
Table 1.
Cantonese tense vowels (adapted from Zee 1999)
104
Table 2.
Cantonese lax vowels (adapted from Zee 1999)
104
Table 3.
Toronto English monophthongs (Adapted from Walker 2015, 81)
105
Table 4.
Distribution of second-generation Toronto (GEN 2) speakers
107
Table 5.
Token distribution based on phonetic environment
108
Table 6.
Summary of independent variables
108
Table 7.
Sample EOQ questions
109
Table 8.
Interview excerpt from C2F24A
112
Table 9.
Mixed effects model for the F2 of /y/
116
Table 10.
Mixed effects model for the F2 of /u/
118
Chapter 6
Table 1.
Rhotic distribution in Spanish
129
Table 2.
Participant background and language experience
135
Table 3.
Rbrul results for all rhotic data for phonological context
143
Table 4.
Rbrul results for target tap data
145
Chapter 7
Table 1.
Key independent variables for the variation of Spanish simple present and estar progressive
164
Table 2.
Baseline speaker groups in the current study
169
Table 3.
Learner groups in the current study
169
Table 4.
Verbs and lexical aspectual classes used in the written contextualized task
171
Table 5.
Items in written contextualized task with lexical aspect and adverb coding
173
Table 6.
Distribution of forms
174
Table 7.
GEE linear mixed model for progressive allowed vs. simple present
175
Table 8.
GEE linear mixed model for progressive allowed vs. simple present by group
175
Table 9.
Simple present vs. progressive allowed (%) by baseline and learner groups
for stative verbs
176
Table 10.
Simple present vs. progressive allowed (%) by baseline and learner groups for activity verbs
178
Table 11.
Simple present vs. progressive allowed (%) by baseline and learner groups for accomplishment verbs
179
Table 12.
Simple present vs. progressive allowed (%) by baseline and learner groups for achievement verbs
181
Chapter 8
Table 1.
/s/-weakening in BAS
203
Table 2.
Participant characteristics
206
Table 3.
BAS ([ʃ] or [ʒ]) versus non-BAS ([ʝ] or [ʤ]) (application value = [ʃ] or [ʒ])
211
Table 4.
Percentage of /s/-weakening by individual, SNSS score, and interview time
212
Table 5.
Vos verb forms versus tú verb forms (application value = vos verb forms)
214
Chapter 9
Table 1.
Summary of characteristics of corpora
233
Table 2.
Summary of levels of French language exposure across the corpora
234
Table 3.
Mixed-effects logistic regression model of à use in à contexts across the FL1–FL2 continuum
239
Table 4.
Mixed-effects logistic regression model of au use in au contexts across the FL1–FL2 continuum
240
Table 5.
Mixed-effects logistic regression model of en use in en contexts across the FL1–FL2 continuum
241
Table 6.
Mixed-effects logistic regression model of IUF on à use in à contexts across the FL1–FL2 continuum
243
Table 7.
Mixed-effects logistic regression model of influence of IUF on en use in en contexts across the FL1–FL2 continuum
244
Table 8.
Use of à versus en/dans in à contexts according to ‘+/– motion’ verbs across the FL1–FL2 continuum
245
Table 9.
Use of en/dans versus à in en contexts according to ‘+/– motion’ verbs across the FL1–FL2 continuum
246
Table 10.
Rates of expected à and en use by FL2 high school students and by FL1 minority students according to IUF
247
Table 11.
Rates of inter-systemic transfer in à and en contexts in the speech of the FL2 high school students and the FL1 minority
and majority students
248
Table 12.
Rates of expected à and en use according to IUF
249
Table 13.
Rates of inter-systemic transfer in à and en contexts
250
Chapter 10
Table 1.
Factor groups with examples from the corpus
259
Table 2.
Ne deletion by Polish L2 speakers of French
261
Table 3.
Speakers, social characteristics, and individual results
261
Chapter 11
Table 1.
Rates of schwa deletion by linguistic factor group
291
Table 2.
Rates of schwa deletion by extralinguistic factor group
293
Table 3.
Implicational scale showing schwa deletion by speaker/clitic type
297
Table 4.
Rbrul factor weights, schwa deletion %, and final SNSS score by speaker
299
Appendix A.
Speakers’ biographical information
307
Appendix B.
Social network strength scale
308
Chapter 12
Table 1.
Hierarchy of types of objects proposed in G uardiano (2010)
315
Table 2.
Coding of variables with illustrative examples from the HLVC corpus
320
Table 3.
Ethnic orientation questionnaire sections analyzed
322
Table 3.
Model of DOM for all speakers combined
323
Table 5.
Comparison of models for four speaker groups (headings labeled as in Table 2)
325
Table 6.
Distribution of objects with DOM from the bottom of the Guardiano hierarchy
327
Chapter 13
Table 1.
Subject population according to native language group
343
Table 2.
Summary of mixed-effects linear regression model fit to bilinguals’ laterals
347