PAGE 1
1 University of Florida Connecting the dots: Social Network a pproaches to capture variability across the lifespan of bilinguals and its consequences for cognition REINALDO CABRERA PEREZ Dr. Eleonora Rossi, Advisor Department of Linguistics April 2023
PAGE 2
2 Acknowledgements I would like to express my gratitude to my research advisor and mentor, Dr. Eleonora Rossi, for always providing me with new opportunities to grow as a researcher. Many thanks to Dr. Diego Pascual y Cabo for his feedback and recommendations during the writing of my senior thesis manuscript. I would not being able to complete this project without the help and s upport of the Brain, Language, and Bilingualism (BLaB) team and the generous funding from the Ronald E. McNair Program and the University Scholars Program. Also, thank you to Dr. Ester Navarro and Dr. David Cañarte for their contributions to this social ne tworks and bilingualism study. Finally, a heartfelt thank you to my mother, Raysa Perez for always encouraging me to follow my dreams and always being there for me. A mi mamá , por darme todo sin esperar nada a cambio .
PAGE 3
3 Table of Contents Page .. . . 2 .3 . . . .5 .. .6 NETWORK SCIENCE OVERVIEW . 8 . .11 . .12 6 3 5 4 9 5 ... 45 APPENDIX . 53 5
PAGE 4
4 Abbreviations AoA: Age of Acquisition PSN: Personal Social Network RT: Reaction Time SN: Social Network(s) SNA: Social Network Analysis SNS: Social Network Science
PAGE 5
5 Abstract The need to communicate is a ubiquitous experience for humans, from infancy to older age. Recent research has sought new methods to describe the variability of bilingual language experience through measures to evaluate and characterize individual differences in bi/multilinguals and how they use language in different communicative and social co ntexts. In turn, little to no data is available on how characteristics of Personal Social Networks (PSN) can demonstrate variability in language use and multiplicity of language variation in different social environments. The present study adds to the emer ging area of research that investigates bilingualism through the lens of PSN. A study was designed to investigate the relationships between bilingual language use and social use of two languages (i.e., Spanish, English) in different social settings, and ov er the lifespan of a bilingual speaker. The main goal of this study Spanish/English bilinguals were tested virtually. Participants were asked to complete a series o f behavioral measures to assess their cognitive control and an extensive SN interview that probed the SN from ages (0 13) and (14 present). Overall, the findings provide evidence that e control tasks and how their network fluctuates across lifespan. Keywords : bilingualism, social network science, personal networks, language use, linguistic variability.
PAGE 6
6 1. Introduction Language development and use are embedded in social interactions throughout life. In other words, language is not developed in a vacuum, but in a social context. Learning and speaking two languages is a known example of continuous life experience that induces to its environment through repetitive actions (e.g., speaking another language), and these neural changes hav e recently been elucidated with advanced technology, such as Magnetic Resonance structural and functional changes with increased exposure to a second language thro ughout their 2007), language development and use are embedded in social interactions throughout life. In other words, language is not developed in a vacuum but i n a social context. Relatedly, recent research has demonstrated that a more diverse PSN promotes better language acquisition in monolingual and bilingual children (Scheele & Mayo, 2010; Hoff et al., 2012). Critically, g language use, are not static but vary constantly due to dynamic changes that occur in different phases of life. Until very recently, bilingualism has been described as a binary phenomenon. However, as evidenced by previous research, it is better characterized as a continuum . languages are in constant change based on their interactions, experiences, and exposure to their language(s) as well as moving into different stages in life (e.g., moving between towns or countries ) . R es earch has indeed evidenced how variability in individual bilingual experiences independent cognitive functions associated with bilingual language regulation ( e.g. , Gullifer &Titone, 2020; Tiv et al., 2 022,
PAGE 7
7 2021). Despite this encouraging new avenue, little research is available to understand how variability in bilingual personal social networks (PSN) critically, beyond the speaker self, may affect linguistic and cognitive performance. It is worth noting the seminal work by Milroy and her contributions to S ocial N etworks in linguistics (Milroy, 1980; Milroy & Milroy, 1985). Milroy and work examined a set of linguistic norms in a community in Belfast looking at s tandard and non Milroy developed a Network Strength Scale based on owledge of other individuals in the community, the workplace, and leisure activities and the survey was distributed in three neighborhoods in Belfast. Her scholarship laid a foundation for early applications of Social Network Science (SNS) in language beca use her findings demonstrate correlation between a high Network Strength score and phonological variation of the vernacular or non standard language. In sum, increasing research in language sciences describes bilingualism as a fluid experience, and not a fixed one (Bialystok, 2010), and this experience can change across the lifespan of speakers (Navarro, DeLuca & Rossi, 2022; Rossi et al., in preparation). 1.1 New directions to bilingualism research Research on bilingualism has grown tremendously sinc e the early 1990s. Historically, research has largely focused on studying bilingualism as a dichotic trait ( e.g., Surrain & Luk, 2019) . Bilingualism is a multidimensional construct that is shaped by individual and contextual factors. In fact, neurocognitiv e effects of bilingualism are indexed by the degree of variability in bilingual language experience. To date, most studies assess bilingualism language experience using complex experience tools (e.g., extensive history questionnaires, etc.) or by assessing
PAGE 8
8 language proficiency with objective measures both in comprehension and production ( e.g., Luo, Luk & Bialystok, 2010; Blumenfeld, Bobb & Marian, 2014 ) . Lately, there has been a new shift in research that has furthered the field by incorporating social netw ork analysis measures (e.g., Gullifer &Titone, 2020; Gullifer et. a l ., 2018). Recent neurobehavioral models of bilingual language use propose how language control processes adapt to certain environments based on the interactional context (Green & Abutalebi , 2013), as well as socio linguistic diversity, background and culture (DeLuca et al., 2019; Gullifer et al., 2018; Marian, & Hayakawa, 2021; Navarro, DeLuca, & Rossi, 2022, Cuartero et al., 2023, Rossi et al., in preparation). However, these studies still rely on extensive Language History Questionnaires ( LHQs ) that probe individual and interactional contexts diversity questions (e.g., Tiv et al., 2022 use network science to describe the language use), but they rarely include: 1) language use variability of the surrounding network of the speaker (alter alter ties), and 2) changes that might occur in individual and interactional contexts thr oughout the lifespan shape bilingual language measures. 1.2 Network Science Overview 1.2.1 Size, composition, and structure of egocentric or personal networks Everyone has a personal network. From the moment of our birth, we start developing our SN. Personal networks are formed through a combination of external factors and personal choices. For example, moving to a new city or country can shape and change drasti cally our interactions with people. As a result, we have some control over our personal network because we can decide who do we want to be friends with and whether we want to introduce them to our family members. However, we have no control of our country of origin, our social class, ethnic group, etc. Furthermore, we are born into a biological family, which constitutes of a set of biological family relationships. We decide who we want to have a closer relationship with and
PAGE 9
9 daily interactions in the family circle. Throughout our lives, we make different choices, such as where we want to live, who we want as friends and coworkers, etc. As a result, our contacts, friends, co workers, and acquaintances will shape how we use language in different linguistic cont exts and domains (McCarty et al., 2019). One of the main components of the SN is the network composition, which refers to the considered network composition by co llecting data on various categories of network actors: family members, friends, romantic partners, classmates, co workers, and others. Each of these with differ in size varying the number of people in the network. As a result, the structure of the network might vary depending on the relationship between actors (McCarty et al., 2019). As a result, Social Network Analysis allows researchers to use compositional and structural characteristics to gain an understanding of the effects of personal networks. The people we interact with, our connection between each other, and our communication can shape our attitudes, behavior, and outcomes. The shape, composition, and structure of SN are quite complex because we construct them based on our preferences and at the same time we are constrained by them (McCarty et al., 2019). 1.2.2 Egos, Alters, and Eg ocentric Networks SNA is the study of the pattern of relationships between a set of actors or nodes and the ties among them or edges (i.e., the lines connecting the nodes). Egocentric network analysis studies the SN of selected people or person. The focal person(s) of which these networks are focused on are called egos and their network members are called alters . Egocentric network
PAGE 10
10 analysis can be constrained to social relationship between people in a specific context (e.g., household, school, etc.) and unc contexts or settings. The goal of personal networks is to study the effects of the set of relationships that surround an individual. Figure 1. Two personal networks with similar networ k composition but different structural arrangements. Nodes (alters) are actors linked to a central ego (no boundary). Ties are all relations (of a given type) among those actors. Each of the colors represents a different group. The black node represents th e ego which is connected to the alters. The white nodes are family members, the light nodes are university friends, the dark shade of gray represents peers known since childhood, and the darkest shade of gray represents people from work. Examples taken fro m (McCarty et al., 2019:114).
PAGE 11
11 Figure 2. Personal networks representative of the seven types of the subgroup based typology dataset (taken from Vacca, 2019:11). 1.2.3 Example of two Egos with different life experiences To understand the fluidity of life experiences, we must look at how language(s) change in different life domains and between different people. We know that if we compare two people, they will not have the same language experiences. For example, Yania was b orn in Cuba and learned Cuban Spanish at home. Then, she moved to Tampa, Florida at the age of four and started learning English in school. At the same time, Arantxa was born in Galicia, Spain and learned Spanish and Galician at home. At the age of five sh e entered the school system (a bilingual school), where she was exposed to, and interact primarily in English. Then, at the age how bi/multilingual speakers are very different from each other and how their language experiences are not the same. SNS gives researchers the opportunity to capture variability in language use by creating a linguistic profile of participants with the goal of understanding how language use cha nges in different life domains over their lifespan. 1.2 Current Study Given the above discussion, the goal of this study is to understand differences in bilingual behavior (alters and alter and language use change in different life use domains (i.e. fami ly, friends, and work), and (c) whether metalinguistic awareness (i.e., language(s) use) predicts cognitive performance in tasks
PAGE 12
12 that measure domain general cognitive control processes (i.e. Stroop, Simon, Flanker) once measured. The current study uses a combination of SNS, cognitive, and linguistic predictors to examine causational ties between bilingual language use and changes in SN, and conversely, capture how changes in the SN might shape changes in bilingual langua ge use at the individual and at the community level over the lifespan. Additionally, this study can serve as a tool to better capture how changes (or lack of changes) in bilingual language use across the lifespan might modulate and predict neurocognitive m easures. Furthermore, it is a first step to understand whether variability in linguistic behavior and interactions of various linguistic and social settings reported from childhood, adolescence, and adulthood for the individual and their network may impact bilingual language outcomes and performance in the cognitive control tasks. 2. Materials and Methods 2.1 Design and Participants Participants were recruited via email diffusion through colleagues and contacts in highly bilingual U.S. locations. Other forms of recruitment were student organizations at various higher education institutions, advertisement using the Brain, Language, and Bilingualism (BLaB) website and Twitter account, and interpersonal communication between participants 1 . To qualify for the stud y, participants had to be fluent and had to learned both languages (i.e., Spanish, English) simultaneously or before the age of seven and must reside in the United States. The participants were mainly located in areas with high Spanish English populations, such as Florida, Texas, California, etc. 1 Participants with similar social networks ( i.e., connections or relationships) were excluded from participating in the study because of similarities and overlaps in alter naming. For example, a brother and a sister could not participate due to having the same familial relationships and friendships.
PAGE 13
13 After removing pilot participants and incomplete responses, the fi nal size was N =51 (Mean age = 22.61, SD age = 3.72) . Table 1 displays the sample demographic details including gender , country of origin, country of residence, occupation, education of parents, etc. The literature establishes that women outnumber men in be havioral studies and this study is not the exception because 75% of the participants identified as female. For country of origin, 56% of the sample were born in the United States and the U.S. is the country of resident for 98% of them. Most of the particip ants are college students (90%) and 59% hold an associate degree. Also, it is worth noting that participants have more years using Spanish (Mean age= 21.18, SD Age= 3.94) than English (Mean age= 13.49 SD age= 3.94). (For a more detailed breakdown, see t abl e 1 ). Table 2 and table 3 summarize the age in which participants started using their native languages in terms of listening, speaking, reading, and writing and current abilities in using their languages. Participants reported that they started to read an d write in English before than they did in Spanish (see table 2 for a full breakdown). Participants reported their current abilities in terms of listening, speaking, reading, and writing of their language using a Likert scale ranging from 1 very poor to 7 excellent (see table 3 for a full breakdown).
PAGE 14
14 Table 1 : Sample demographic details (N=51) Mean SD Frequency Age 22.61 3.72 Female Male Non binary 75% 22% 3% Country of origin U.S: 56%, Cuba: 14% Mexico: 8%, Venezuela: 8% Spain: 4%, DR: 2% Guatemala: 2%, Honduras: 2% Italy: 2%, Peru: 2% Puerto Rico: 2% Country of residence United States: 98% Honduras: 2% Occupation Full time student : 90 % Part time job: 41 % Full time job: 10% Unemployed: 2% education Associate degree: 59% High s chool: 35% High school : 33% 27% Associate s degree: 10% Middle school : 10% Doctorate degree: 6% Elementary school : 4% Other: 4% High school: 29% Associate degree: 12% Middle school : 10%, Elementary school : 8% Doctorate degree: 6% Other: 4% Years using Spanish 21.18 3.94 Years using English 13.49 3.94 Years using other languages 0.50 3.00 Note: Most of the participants are full time students and have a part time job.
PAGE 15
15 Table 2: Age participants started using their native languages in terms of listening, speaking, reading, and writing (N=51) Mean SD Listening to Spanish 0.12 0.71 Listening to English 1.02 1.68 Listening to other languages 0 0 Speaking Spanish 1.35 0.98 Speaking Spanish 1.96 2.08 Speaking other languages 0.05 0.27 Reading in Spanish 4.86 1.52 Reading in English 3.29 2.72 Reading in other languages 0.14 1.06 Writing in Spanish 5.67 2.21 Writing in English 3.51 2.77 Writing in other languages 0.15 1.11 Table 3: in their native languages (N=51) Mean SD Listening to Spanish 6.53 0.81 Listening to English 4.49 2.23 Listening to other languages 0.17 1.01 Speaking in Spanish 6.12 1.05 Speaking in English 4.49 3.23 Speaking in other languages 0.15 0.90 Reading in Spanish 6.14 1.00 Reading in English 4.59 3.29 Reading in other languages 0.16 0.90 Writing in Spanish 5.69 1.09 Writing in English 4.45 3.22 Writing in other languages 0.14 0.76
PAGE 16
16 2.2 Measures 2.2.1 Simon Task The Simon Task is a behavioral measure of interference and conflict resolution developed by J.R. Simon (Simon & Small, 1969). The Simon task is an assessment of inhibition that measures participants accuracy in their performance calculated by reaction time (RT). Participants are provided with a link to Tatool soft ware, an open source experiment software, where they complete the practice and the task trails . In th e Simon task, participants ar e asked to respond to visual stimuli by making a rightward response (e.g., red circle) or a leftward response (e.g., green cir cle) using the right or left key on the keyboard (see figure 1). The stimuli can be presented on the right or left side of the display. Therefore, the location where the stimuli appear does not affect the accuracy of the performance on the task. The positi on can patterns by matching color and position (i.e., congruent trials) or not matching color and position reveals an increase in RT respond to an auditory stimulus using high and low pitch tones with their right or left hands. The dependent measures used are (i) reaction time and (ii) accu racy between congruent and incongruent trials. The Simon effect is indicated by the difference in accuracy or reaction time between trials (i.e., congruent, incongruent). This effect is taken as a measure of interference between a target component (i.e., s hape or color of a geometric figure) and a non target component (i.e., the location of the shape).
PAGE 17
17 Figure 1. Simon Task procedure displayed in Tatool software. 2.2.2 Flanker Task The Flanker Task, also known as the Eriksen Flanker Task, was developed by Eriksen and Eriksen in 1974 (Eriksen & Eriksen, 1974). The Flanker Task is a set of inhibition tests used to assess selective attention and inhibitory function and the ability to su ppress responses that are irrelevant in a specific context. This task has multiple variations, but most used include a similar pattern with arrows p articipants have to respond to a target stimulus, an arrowhead (< or >) focusing on the middle arrow and dec ide if the arrow is pointing to the left or to the right (e.g., << > <<). In the current study, participants complete the Flanker task in Tatool, where they see the practice and testing trials displayed on their screen as a letter stimulus is used composed of seven characters (consonants and vowels). The target stimulus is always centered in a display of seven stimuli (see figure 2). The left arrow key represents the center vowel stimulus, and the right arrow key represents the center consonant stimulus. Therefore, participant s must press the appropriate key accordingly. The dependent variables are normally response speed and accuracy. Eriksen and work demonstrates the correlation between RT between congruent and incongruent compatible noise (noise identical and
PAGE 18
18 noise same response conditions) gave longer RTs at the closest stimulus spacings compared with the no noise mixed con Figure 2. Flanker Task procedure displayed in Tatool software 2.2.3 Stroop Task The Stroop Color and Word Test was developed and published in 1935 by John Ridley ference in participants when presented with a color word printed in an ink color that did not match the word. This caused participants to take more time to read those stimuli than the same color words printed in black ink (Stroop, 1935). The test involves one section where participants read color words that are printed in black ink, another section where participants name squares of certain colors, and an incongruent section where color words are printed in conflicting ink colors that do not match the word. Then, the participant must colors and 100 stimuli on each card, and he compared the time it took in seconds to read the stimuli from each card (Jensen, 19 65). In the incongruent section, participants must suppress the more automatic task of reading the word to perform the less automatic task of naming the ink color, which creates cognitive interference and explains why the participants take longer to comple te the
PAGE 19
19 incongruent section than the congruent sections (Scarpina & Tagini, 2017). This phenomenon is now known as the Stroop Effect and has been demonstrated many times in the literature (e.g., MacLeod, 1991; Scarpina & Tagini, 2017). For example, the Stro op Effect in bilinguals has shown to have better interference suppressions ( i.e., better performance than monolinguals) (Bialystok, Craik & Luk, 2008; Sabourin & V n erte, 2015). Similarly, to the Simon Task, this test is used to assess the ability to inhi bit cognitive interference that occurs when the processing of a specific stimulus feature (e.g., the color filling of a printed color word) impedes the simultaneous processing of a second stimulus attribute (e.g., the script of a printed word). The Stroop effect is a delay in the reaction time between congruent and incongruent stimuli. In other words, the mismatch between the name of a color word (i.e., the filling of the word matches the printed color) and the printed one (i.e., the filling of a word does not match the printed color). For this study, a variation of the task was created using numbers instead of printed words , where participants see the practice and testing trials displayed on their screens. For example, four characters are shown and each represent ing the numerical number 4. The purpose of this task is to focus on one aspect and not the other (i.e., count how many characters are in each stimulus and not the number character number) (see figure 3).
PAGE 20
20 Figure 3. Flanker Task procedu re display ed in Tatool software. 2.2.4 Social Background History Questionnaire For this study, we designed a novel social networks survey in Egoweb (Kennedy, 2009) using social network analysis methodology (Molina et al., 2019) to examine different components of pa rticipants and their networks language use and experience. An extensive language history questionnaire and social background history questionnaire was constructed using validated resources already available in the literature ( e.g., Anderson et al., 2018; M arian, Blumenfeld & Kaushanskaya, 2007; Rodriguez Fornells et al., 2012; Li et al., 2019; Navarro, DeLuca & Rossi, 2022). The study follows the general PSN analysis guidelines presented in McCarty et al., 2019 where a SN interview has four modules or phase s: 1) an ego elicitation module in which questions are asked about the participant, 2) a network elicitation module in which the participant is asked to nominate their alters ( name generator ), 3) a module on questions asked about each alter ( name interpret ers ), and 4) an alter alter tie module that asks the participant about ties or relationships between alters ( edge interpreters ). Questions about in different s ocial contexts, which include household, school, work, extracurricular, etc. Many of these questions were collected via a Likert scale , which can be converted as a numeric number during data analysis. In addition, the study collects data to understand the switching tendencies, context, and use with their networks. The questionnaires are divided in two sections (i.e., early life (0 13 years old) and late life (14 current)). Each participant first responded to an extensive sociodemogra phic questionnaire, which included age, gender, nationality/country of origin, occupation, education, schooling information etc . In the first section of the survey (0 13 years old) (adapted from Anderson et al., 2018;
PAGE 21
21 Marian, Blumenfeld & Kaushanskaya, 2007) , participants named the language(s) they learned at birth before the age of five (i.e., first, second, and third language (if applicable)) based on their dominance. Then, they were prompted to answer questions about the age(s) they began speaking the ir language(s) and rate their current ability in terms speaking, listening, reading, and writing and the social contexts of language use (e.g., at home, at school, with friends, at work, social media, etc.). Other questions included cultural identification , total number of years using/speaking native language(s), and if the participant have lived or traveled in countries other than the country of residence/origin for more than three months (see appendix II). Then, a set of quantitative questions were incor porated asking about an estimation of how many hours did the participant spent using their language(s) in terms of leisure 2 , speaking with family members, friends, classmates/co workers, etc. After completing the native language(s) section, participants we re asked a similar set of questions for their non native language(s) (i.e., languages learned after the age of five). The second section include general language skills questions about what language participants could understand and speak between age rages 3 , ability to learn languages, language mixing with different groups, best comfortable language to communicate, etc. (questionnaire adapted from Rodriguez Fornells et al., 2012) (see appendix II). Participants completed a set of questions about language m ixing and switching attitudes in different linguistic contexts as well as a series of different scenarios to see if they experience 2 ( i.e., watching television or online streaming, listening to the radio ( e.g., music, news, podcasts , etc. ), using social media/the internet, and reading). 3 (0 4), (5 10), (11 17), and (18+)
PAGE 22
22 any linguistic changes in the past three months 4 . After completing the general language skills section, participants had to nominate 15 people (5 family members, 5 friends, 5 classmates that were not their friend s ) that they knew when they were between the ages of 0 to 13. After participants had to ans wer some questions about their SN. These include first interaction and current age, gender, racial category, nationality/country of origin, whether they feel emotionally closed with each nominee. Also, they were asked about the category of their connection s (i.e., family, friends, partners, etc.), whether they communicate between one another, language switching between connections, and language of preference. Then, participants completed the SN language pair. To the best of their knowledge, they had to say whether alter 1 and alter 2 communicate regularly or maintain a regular relationship with each other when the participant was 0 13, the language(s) used between alters, and an estimation of language switching engagement. After completing the first portion of the study, participants nominated 15 more people (family 5 , friends, classmates, co workers) that they have known/interacted with between the ages 14 present. Similarly, questions about the relationship between their connections are asked. 2.2.4.1 Social Networks Level Data Visualization The online study collected data in three levels (ego, ego alter, alter alter) that were then used to create data visualizations. Figure 4 provides a representation of the family context of a participant when they we re asked to nominate five family members. For example, if a 4 Participants had to think back on their life over the past thre e months and determine whether any of the scenarios presented happened to them in the past three months. Examples include being (un)comfortable about people who only speak Spanish/English, having a hard time understanding others when they speak English/Spa nish. 5 Participants were allowed to nominate the same family members, but the name had to include a number to make a distinction between the two stages.
PAGE 23
23 they know who their nominations are. The ego level data collects information that describes the featur es and characteristics of the ego. The ego alter level data collects information about the relationship, communication, and linguistic features between the participants and their connections. A lter alter level data collects information about the interactio n, and communication Figure 4 : Representation of five family nominations in three level of current and childhood experience of participants and their social networks. (A) represents ego level data, (B) represents ego alter level data, and (C) represents alter alter level data 2.3 Procedure Participants (N=51) received an email confirmation with a Zoom link of their selected time slot in Calendly. The experiment was conducted in an interview format onli ne and synchronous using Zoom videoconferencing for data collection, where the interviewer shared the
PAGE 24
24 screen and asked the participant to provide answers to survey questions (Banyai, 1995). The survey took approximately two and a half to three hours to com plete, and participants received five minute breaks after each section. There are three main sections of the survey: a short battery of cognitive control tasks, questions about language background, and questions about their SN. First, participants read the consent form (see appendix I) at the beginning of the survey and click unique participant identification composed of their first three letter of the first name a nd last would be ing_marr_May242021PM_rcp. This de identification ensures the anonymity of the data collected (McCarty et al., 2019). The participants then proce eded to complete the cognitive control tasks 6 in Tatool, an experiment software (von Bastian, 2013). After completion, they received a code that was entered into the survey session. Then, they proceed to complete the language history questionnaire, the soc ial background history questionnaire, and the SN history questionnaire. All participants completed the tasks and survey in the same order, as it is the norm of studies of this nature to avoid biasing within the effects and discrepancies in participants res ponses. After all the SN interviews have been conducted, the collected data in EgoWeb is stored into data matrices at the ego, ego alter, and alter alter levels. During data analysis, the matrices are used to compute network structure variables. Each of th e cells in these files represents the tie (i.e., relationship) between all pairs of alters. The structural and compositional extracted data is represented numerical ly based on the code book designed for the study. Upon completion, 6 (See 2.2.1, 2.2.2, 2.2.3 for the description of the Simon, Flanker, and Stroop tasks)
PAGE 25
25 participants received cou rse credit for their participation or an Amazon e gift card varying from $20 $30 USD. 2.4 Analyses Each participant responded to approximately 500 questions of the language and social network questionnaire and completed the three cognitive control tasks (i .e., Stroop, Simon, and Flanker). A composite score was collected and averaged across the information provided (e.g., language use, switches, language use for ego and alter). The scores were calculating using the total number of alters and nominations and separated by language or alter group category. Specifically, the scores were based questions about a particular question (e.g., switching with L1 and L2, L3, Lx average use, time spent per week in minutes watching TV, listening to music, speaking with family, friends, classmates, etc. Other information used for the analyses is the languages used across the lifespan of the ego, current and childhood languages us ed between egos alter, and alter h people in their network (see t able s 4 9). In addition to the SN data, a metalinguistic composite score was calculated based on the sks and using their language interaction information (e.g., switches, language(s) . The study uses PSN structure to understand variability in cognitive performance in bilinguals with the goal to capture bilingual language use over time. Given that previous studies demonstrated how bilinguals have a faster RT in their performance for congruent and incongruent trials (e.g., Bialystok et al., 2005), it was important to identify how Spanish English bilingual s perform during executive function tasks because they have shown to have a positive effect on efficiency and outperforming other groups (e.g.,
PAGE 26
26 monolinguals. In particular, the Simon task responses w ere used as a dependent variable and correlated with three measures of SNS (i.e., network size, be tweenness, and language entropy). Network size refers to the total number of alter nominees network ( e.g., 30) . The network size can be compared to the level of density of the network , where the higher the language use and interaction with the ego can lead to a higher density. Betweenness is a measure of centrality of the network that serves as a function of age, race, or language behavior. In b etweenness centrali ty , alter(s) who formed the shortest path between all nodes (i.e., other alters and excluding the ego from the network ) domina tes the network structure in terms of betweenness. Language entropy is the level of variability of language use (e.g., language use between ego and alters). Specifically, language entropy is a measure of certainty of language use that captures within person individual differences with respect to the balance of language use generally and across varied social communicative contexts (e.g., language use at home, work, in social setting, etc.) (Gullifer & Tito ne, 2020. These three SNS measures were correlated with participants results in the Simon task , while evaluating how code switching modulates the effec t. This study allows us to capture bilingualism as a multidimensional construct, which is shaped by indi vidual and contextual factors. Capturing variability of language use across the lifespan in speakers helps us understand how their language trends and interactions change over time by employing extensive language and social network history questionnaire s. The degree of variability in bilingual language experience is calculated by indexing individual and contextual factors as modulator of linguistic and neurocognitive effects of bilingualism. It is calculated by using ego of their language use in different social context s and settings and measured with alter interactions. The dynamic of the SN (i.e., relationships) creates new paths shaping
PAGE 27
27 various domains of executive function, or neurocognitive measures. This analysis aims to dem onstrate that all input is not necessarily used at any given time, and probe d opportunities (indexes) (see d iagram 1). Additionally, a composite summary of community detection was used to identify the cohesiveness of the group or clusters in the network ( Jokar & Mosleh, 2018). The composite summary was created by examining regular interactions between the ego nominations and separated by individual settings (household, school, work). This component is important since the community structure (i.e., cluster of nodes that are interconnected) can reveal the hierarchical organization of nodes. For example, a person may concurrently belong to different groups in college, school, friends , family etc. indicating differences in engagement and interaction among nodes . Also, a summary of early and late ego objects, and alter alter ties was calculated using an igraph algorithm in R Studio to show the relationship among the nodes in the network. Lastly, ographical location and correlated with other variables taken from the survey (i.e., education, socio economic status, etc.) (see f igure 6).
PAGE 28
28 Figure 6: N= 51 current and alternate zip codes. Florida: Figure A (20 Alachua County, (6 Broward County), (1 Citrus County), (1 Collier County), (17 Hillsborough County), (1 Indian River County), (1 Lee County), ( 9 Miami Dade County), (1 Palm Beach County), (1 Palm Beach County), (2 Pasco County ), (1 St. Johns County), (1 St. Lucie County). Texas: Figure B (13 County of El Paso), (1 Travis County). Pennsylvania: Figure C (1 Allegher County). Kentucky:
PAGE 29
29 Figure D (McCracken County), (1 Jefferson County). Maryland: Figure F (1 Harford C ounty). Georgia: Figure G (1 Paulding County). California: Figure H (2 San Bernardino). Not shown: Iowa (1 Sioux County). An R Programming Language (R Core Team, 2020) was used to inspect SN data using the statistical package egor (Krenz et al., 2 020), and the visualization package igraph (Csardi & Nepusz, 2006). Figure 5 shows two different examples of network structures from Cuartero et al., 2023 alters, many aspects o f the network can be correlated between the community of alters and their trends. Fi gure 5: (A) represents a sparser network with a core periphery and (B) shows a denser network with two clusters in which alters are connected (Cuartero et al., 2023).
PAGE 30
30 Diagram 1: Visualization of information co llected during the ego interview. Table 4: Descriptive statistics. Language use in different contexts (N=51) Mean SD Spanish at home 0.98 0.14 English at home 0.39 0.49 Other languages at home 4 0.16 Spanish with friends 0.78 0.42 English with friends 0.67 0.48 Other languages at home 0 0 Spanish at school 0.51 0.50 English at school 0.67 0.48 Other languages at school 0.02 0.14 Spanish at work 0.41 0.50 English at work 0.51 0.50 Other languages at work 0 0
PAGE 31
31 Table 5: Estimation in minutes of media consumption (N=51) Mean SD Using social media in Spanish 0.65 0.48 Using social media in English 0.65 0.48 Using social media in other languages 0 0 Using other media in Spanish 0.31 0.47 Using other media in English 0.55 0.50 Other media in other languages 0 0 Watching TV in Spanish 3.88 4.76 Watching TV in English 5.75 6.46 Watching TV in other languages 0.05 0.44 Listening to the radio in Spanish 6.86 7.74 Listening to the radio in English 7.12 10.14 Listening to the radio in other languages 0.05 0.37 Reading in Spanish 3 4.70 Reading in English 12.08 15.28 Reading in other languages 0.04 0.34 Using the Internet in Spanish 6.82 8.56 Using the Internet in English 10.65 13.86 Using the Internet in other languages 0.09 0.75 Table 6: Language use with different people (N=51) Mean SD Using Spanish with family 21.67 25.44 Using English with family 7.02 17.40 Using other languages with family 0.80 0.80 Using Spanish with friends 9.14 14.91 Using English with friends 13.04 20.41 Using other languages with friends 0.01 0.16 Using Spanish with classmates 2.29 4.48 Using English with classmates 8.35 15.57 Using other languages with classmates 0.02 0.24
PAGE 32
32 Using Spanish with others 6.24 10.76 Using English with others 8.24 11.50 Using other languages with others 0.01 0.11 Table 7: Introspective language use (N=51) Mean SD Thinking in Spanish 4.49 1.42 Thinking in English 4.06 2.98 Thinking in other languages 0.14 0.80 Self talking in Spanish 4.16 1.67 Self talking in English 3.63 2.94 Self talking in other languages 0.11 0.67 Expressing emotion in Spanish 5.14 1.36 Expressing emotion in English 3.72 2.81 Expressing emotion in other languages 0.10 0.65 Dreaming in Spanish 0.39 1.90 Dreaming in English 3.47 2.96 Dreaming in other languages 0.07 0.39 Table 8: Language mixing with network (N=51) Frequency Family Always: 31% Regularly: 31 % Usually: 14% Sometimes: 10% Often: 12% Rarely: 2% Friends Regularly: 29% Always: 17% Often: 20% Usually: 20%
PAGE 33
33 Sometimes: 14% Rarely: 2% Classmates Regularly: 68% Sometimes: 14% Rarely: 8% Often: 6% Always: 4% Usually: 0% Others Regularly: 52% Sometimes: 20% Often: 14% Always: 8% Rarely: 4% Usually: 2% Table 9: Comfort of using native languages in different contexts (N=51) Frequency Home Listening Spanish: 78% English: 16% Spanish/English: 4% Spanish/Cantonese: 2% Speaking Spanish: 67% English: 27% Spanish/English: 4% Spanish/Cantonese: 2% Reading English: 61% Spanish: 33% Spanish/Cantonese: 2% Spanish/English: 4% Writing English: 65% Spanish: 29% Spanish/English: 4% Spanish/Cantonese: 2% Friends Listening English: 65% Spanish: 29% Spanish/English: 4% Spanish/Cantonese: 2% Speaking English: 69% Spanish: 25% Spanish/English: 6% Reading English: 75% Spanish: 20% Spanish/English: 6% Writing English: 76% Spanish: 18% Spanish/English: 6%
PAGE 34
34 School Listening English: 92% Spanish/English: 6% Spanish: 2% Speaking English: 90% Spanish/English: 8% Spanish: 2% Reading English: 92% Spanish/English: 6% Spanish: 2% Writing English: 92% Spanish/English: 6% Spanish: 2% Work Listening English: 55% Spanish: 6 % Spanish/English: 4% Speaking English: 55% Spanish: 6% Spanish/English: 4% Reading Spanish/English: 64% English: 57% Spanish: 4% Writing English: 57% Spanish: 4% Spanish/English: 4% 3. Results The descriptive statistics and correlations are presented in t ables 4 8. For this study, I will focus on the correlation of the scores from the network size, betweenness, and language entropy in early and late life with the imon Task (see figures 7 9 and t able 11). The Simon composite scores were inputted with the variables previously mentioned. The composite scores were plotted into a graph and separated based on the results between low and hig h switches in early and late life. In addition to the main analysis presented below , the descriptive data provides important information on language use and attitudes towards their languages. Participants reported that Spanish is predominantly use at home ( 0.98, SD 0.14) and with family members ( 21.67, SD 25.44). These findings indicate how Spanish is present in the household and less in other life domains ( see t ables 4 and 6 for a detailed breakdown). Participants are more com fortable using English in terms of listening, speaking, reading, and writing with friends, at school, and at work. It is worth noting that participant felt more comfortable using Spanish at home with 78% for listening and 67% for speaking, which suggests t hat their parents might have limited knowledge of English (see t able 9 for a full breakdown ) . Additionally, participants
PAGE 35
35 provided a frequency of language mixing with their network (i.e., family, friends, classmates, and others) (table 8 provides a full bre akdown with percentages). In the introspective questionnaire, participants reported that they are more Spanish dominant in terms of thinking ( 4.49, SD 1.42) , self talking ( 4.16, SD 1.67) , and expressing emotion ( 5.14, SD 1.36) , but English dominant in dreaming ( 3.47, SD 2.96) , which aligns with Joseph d e Koninck 1980s work on language learning and fluency (e.g., de Koninck et al., 1988) (see table 7 for more details). Participants also provided an estimation in minutes of media consumption using their native languages. The use of Spanish and English for social media is consistent and divided equally between both languages ( 0.65, SD 0.48). In other categories, they reported using more English, such as in watching television ( 5.75, SD 6.46), lis tening to the radio ( 7.12, SD 10.14), reading ( 12.08, SD) , and using the Internet ( 10.65, SD 13.86) (see table 5 for more information). The results of network density show a representation of the proportion of ties (e.g., family, friends, etc.) in ea rly and late life. Figure 7 shows the correlation between early and late network density and the Simon scores. Network density had an impact on participants who are low switchers. If the network is very dense, the Simon effect overall is better. Participan ts with a low network density do not perform as well. For networks (i.e., ego, alters) that code switch all the time, the Simon effect does not seem to be too drastic, and this is a compensatory effect for code switching. Code switching seems to be an impo rtant aspect for modeling the effect. Additionally, alters are more likely to provide support to the ego when they are part of more cohesive (dense) networks. However, for other network densities it can play an important role. The results from
PAGE 36
36 between earl y and late network density are consistent among the three trials (i.e., incongruent, congruent, Simon Effect). Figure 7 Network Density: Left graph represents the Simon scores with low and high switches for early network density. The right graph represe nts the Simon scores with low and high switches for late network density. There are three trial types: green (congruent), blue (incongruent), and red (Simon effect). Similarly, betweenness shows similar results where we can observe that there is an effect in level of code switching but also on people who reported low code switching. Higher levels of betweenness centralization are presented and have an effect on cognitive performance. Betweenness centralization is important in a network because it relates t o alters becoming connected between clusters (i.e., groups of people). Figure 8 displays the results between early and late betweenness and how the Simon effect varies. This change might be due to a change in minations.
PAGE 37
37 Figure 8 Betweenness: Left graph represents the Simon scores with low and high switches for early betweenness. The right graph represents the Simon scores with low and high switches for late betweenness. There are three trial types: green ( congruent), blue (incongruent), and red (Simon effect). Lastly, f igure 9 displays the results for language entropy in the friendship and family context. It can be observed that a higher level of language entropy for low switches and the possible influence on the Simon Effect. If there is higher language entropy, it resu lts in more complexity and variability in the network. The results shown were calculated per context in which ego and alters speak their languages (e.g., L1, L2, L3). Low switches in the family context are composed of the closest relatives of the ego that might or might not speak English (e.g., mother, father, grandmother, grandfather, etc.) whereas in the friendship context are composed of early connections, English dominant alters, or monolingual friends.
PAGE 38
38 Figure 9 Language Entropy: Left graph represents the Simon scores with low and high switches for language entropy in the friendship context. The right graph represents the Simon scores with low and high switches for language entropy in the family context. There are three trial types: gr een (congruent), blue (incongruent), and red (Simon effect). Table 10: Result from the Simon Task Mean SD Simon congruent 597.21 135.93 Simon incongruent 684.57 160.42 Simon effect 0.01 0.92 Table 11: Network characteristics Mean SD Network size (early) 14.92 0.39 Network size (late) 14.94 0.31 Density (early) 0.10 0.12 Density (late) 0.11 0.11 Mean degree (early) 1.43 1.70 Mean degree (late) 1.53 1.50 Mean betweenness (early) 1.07 2.80 Mean betweenness (late) 1.03 1.68 Mean degree of centrality (early) 0.16 0.11 Mean degree of centrality (late) 0.18 0.11
PAGE 39
39 size, density, mean betweenness, and mean degree of centrality. The network scores between e arly and late are similar and consistent across stages. Table 12 displays demographics and characteristics of different groups of nodes clustered or partitioned in the community detection for N=52. Community detection divided into five different characteri stics of the network. It displays the distribution of the networks using a p value of the Kruskal Wallis rank sum test, a non parametric method for testing whether samples originate from the same distribution. Table 12: Community detection N=52 ego characteristics . Characteristic s 1 , N= 8 1 2 , N=12 1 3 , N=14 1 4 , N=7 1 5 , N =10 1 p value 2 Ceb.n.large 0.00 (0.00) 1.25 (0.45) 1.00 (0.00) 2.57 (0.53) 2.00 (0.67) <0.001 Ceb.n.small 13.88 (0.83) 8.25 (0.75) 10.79 (0.58) 1.43 (0.79) 4.90 (0.88) <0.001 Ceb.mod 0.20 (0.27) 0.26 (0.21) 0.15 (0.21) 0.32 (0.13) 0.37 (0.21) 0.14 Unknown 3 0 0 0 0 0 1 Mean (SD) 2 Kruskal Wallis rank sum test 4. Discussion The goal of this study was to examine the role of personal networks in a set of relationships that surround an individual . A pplying social network measures to look at the effects of bilingualism for language and cognition permits us to have a better idea of how language is used in different contexts. Spe cifically, this study had three main goals: first, we attempted to describe and capture participants language use in different life use domains (i.e. family, friends, and work) and changes that might occur in individual and interactional contexts throughou t the lifespan; second, we created a comprehensive language history questionnaire and social background history questionnaire that captures language use variability of the surrounding network to the speaker (alter alter ties); and third, we compared cognit ive performance in three
PAGE 40
40 (e.g., code switching, language use) to determine the relationship between the network and the co activation of their languages in vario us contexts. As previously stated, this study serves as a first stepping stone to better capture the variability in language use and how language, social, and cultural experiences shape bilingual speakers. For example, bilingualism seems better represented as a multifactor model of related but separate constructs of language experience and use. Preliminary evidence of some components that form individual differences in language experience (Bialystok, 2018; N oble et al., 2012). This suggests that a given individual could present higher or lower levels of one or more of these traits, potentially allowing to better understand variable effects of bilingualism on cognitive performance and linguistic abilities. It is important to continue conduct ing empirical research to better capture variability among bilingual speakers. As mentioned before, r esearchers in the field of bilingualism are moving forward using a dynamic set of traits, that is, a bi factor model, such as assessing variability such the interplay. There are diff erent dimensions or components between these variables and models for language experience that vary across participants that could explain those relationships better than just studying them from a dichotomous perspective. Furthermore, the result of this s tudy attempts to cast causational ties between bilingual language use and changes in social networks, and conversely, capture how these changes might shape bilingual language use at the individual and at the community level. Additionally, it has the potent ial to serve as a tool to better capture how changes (or lack thereof) in bilingual
PAGE 41
41 language use across the lifespan might modulate and predict neurocognitive measures. In terms of its impact on social networks and bilinguals, the finding from this study a dds to the emerging body of literature indicating the complexity in language variability among heritage bilingual speakers. For example, the novel assessment tool (i.e., language history questionnaires and social background history questionnaires) proposed in this study can serve as an initial tool to assess various populations. The presented findings demonstrate the importance of capturing variability in language taking into consideration many linguistics and SN measures. For example, capturing time (i.e. , in years) of the participant was crucial because bilingualism research has shown, especially on SNS, how individual variables and social variables are not static and change in time. In fact, researchers such as Titone & Tiv, 2022 and the Douglas Fir Grou p have proposed models to capture this variability beyond the individual. The emergence of research and the synergy between SNS and bilingualism is only in its inception. As demonstrated by the Systems Framework of Bilingualism (Titone & Tiv, 2022) and ech field of bilingualism research needs a model that captures the complexity of bilingual speaker. It needs to consider sociolinguistic variation, which influences and shape different aspects, such as language use, development, psycholinguistic behavior, neurocognition, an d neuroplasticity (see example f igure 10 taken from Tiv et al. (in press)).
PAGE 42
42 Figure 10: A Systems Framework of Bilingualism shows interdependen t layers of individual or ego. These layers include interpersonal, ecological and societal spheres of influence. Finally, developmental or historical time can exert s ubtle temporal influences on the 2022:5). Similarly, in second language acquisition research (SLA), the Douglas Fir Group, 2016 created a transdisciplinary framework for SLA in a multilingual world inspired by Bronfenbrenner's ecological framework for human development (Bronfenbrenner, 1979; Bronf enbrenner & Morris, 2007). They designed a multilayered complexity of L2 learning, which distinguishes three levels of mutually de pendent influences (i.e., macro level of ideological structures, meso level of sociocultural institutions and communities, and micro level of social activity) (see f igure 11 for a visual representation) .
PAGE 43
43 Figure 11: The Multifaceted Nature of Language Learning and Teaching ( the Douglas Fir Group, 2016 :25). The intersectionality between SNS and bilingualism is important, and the growing body of literature helps to understand different variables that before were difficult to measure or capture. Recent studies use SNS to describe the language diversity of bilin gual speakers. For across languages and communicative contexts. Similarly, Marian & Hayakawa (2020) use a fitting a model of two types of bilinguals. Some of the components they incorporate are age of acquisition (AoA), manner of acquisition, proficiency, language use, language identity, and language switching. Specifically, some of the components can dictate these changes. Such as pluritculturality, early acquisition of language, language switching, bilingual SN (e.g., many people might speak different languages), formal second language training, might use second language (English) in adulthood. Additionally, Navarro, DeLuca & Rossi, 2022 used SNS to identify the effect of individual differences in bilingual experience for theory of mind (ToM). The results of their study suggest
PAGE 44
44 that some aspects of the bilingual experience predict task performance (e.g . , direc tor task 7 , metalinguistic awareness tasks developed by Cartwright et al., 2017) but not others, and these predictors align with the two system theory of ToM. The study previously mentioned demonstrates the importance of using SNS to better capture various aspects of bilinguals employing this tool to shed light on individual variability as well as on community language use. This study is not without limitations. For example, the LHQ had a handful number of quantitative questions about the ego and alters lan guage use in minutes. Also, in SNS it is not recommended to ask questions about the past (e.g., when the ego was a child) because the information could not be completely accurate. Therefore, participants were asked to provide information about language beh aviors during childhood . After reading the current methodologies and meeting various social networks specialists, it was necessary to ask these types of questions . As a precaution, our questions, such as how confident you are ab during childhood should be taken with a grain of salt because it is possible that some degree of error was introduced by requiring the recollection of retroactive memories and their responses should be c questionnaire tools include the reporting of behaviors at different points throughout the lifetime, the responses in the current SN are not expected to be more skewed than the ov erall pool of ro, DeLuca & Rossi, 2022: 487). Overall, our study demonstrates a correlation between ego per f o rm ance in cognitive control tasks and the ir language use and interaction in their networks , especiall y showing the 7 The director task is a perspective taking assesses mentalizing and non emerging aspects of ToM (Quesque & Rossetti, 2020).
PAGE 45
45 most variability in switches in the language entropy measures of f riends and family context s . Also, it was important for us to have a representative sample of bilingual participants of different varieties of Spanish from across the United Spanish . For example, p codes) can reveal information about where they live, such as economic and employment opportunities education, average household income, etc. Also, the information can be compared with U.S. Census data . 5. Conclusion This honors thesis aims to shine some light on the new trends of bilingualism research and how researchers are steering the field to a new direction . As a result, it leads to an emergence and new interpretation s of what it means to be bilin gual with empirical evidence demonstrating multilingualism as a dynamic experience as well as how language behavior changes across contexts. The scope of social network analysis goes beyond this paper because SN A can help us by incorporating contextual effects as explanatory variables for individual outcomes . Our study shows that as bilinguals moved from childhood to early adulthood , they become more English dominant because of education and employment opportunities. The present study also shows interactional variation in which participants were more Spanish centric early in life because they were dependent of their parent, but more English centric after fourteen years old indicating a mobility independence to expand their connections. 6. Future directions As Valente (2012) demonstrated, network analysis can inform of interventions to promote behavioral changes (e.g., adoption of bilingual language schooling), changes in network structures (e.g., increase cohesion in gr oups), and provide information to other people (e.g., parents, political leaders, parents, etc.). A future goal is to expand the SN questionnaire including
PAGE 46
46 a third stage which captures language variation in adulthood. During adulthood, an ego can undergo t he most change because of employment , career opportunities , starting their own family , and moving between places . Therefore, there can be a range in variability in language and connections. At this st age, the ego can cement their networks and have long las ting relationships that can demonstrate continuity in language use over time. language experience is an identity, not by choice but by the need to adapt and live. It i s neither The main purpose of this paper is to emphasize the importance of research that captures variability in language use and how people navigate their l i ves with multiple languages.
PAGE 47
47 List of References A Transdisciplinary Framework for SLA in a Multilingual World. (2016). The Modern Language Journal , 100: 19 47. Anderson, J.A.; Mak, L.; Keyvani Chahi , A.; Bialystok, E. (2018). The language and social background questionnaire: Assessing degree of bilingualism in a diverse population. Behavioral Research Methods , 50, 250 263. Banyai, I. (1995). Zoom. New York :Viking. Bialystok E. The bilingual adaptat ion: How minds accommodate experience. (2017). Psychological Bulletin Journal . 143(3):233 262. Bialystok, E. (2010). Bilingualism. Wiley interdisciplinary reviews: Cognitive science . 1(4), 559 572. Bialystok, E., Craik, F. I., Grady, C., Chau, W., Ishii, R ., Gunji, A., & Pantev, C. (2005). Effect of bilingualism on cognitive control in the Simon task: evidence from MEG. NeuroImage , 24 (1), 40 49. Bialystok , E. , Craik , F. , & Luk , G. ( 2008 ). Cognitive control and lexical access in younger and older bilinguals . Journal of Experimental Psychology: Learning, Memory, and Cognition , 34 (4) , 859 873 . Blumenfeld , H. K, Bobb , C. S., & Marian , V. (2016) . The role of language proficiency, cognate status and word frequency in the assessment of Spanish fluency, International Journal of Speech Language Pathology , 18:2, 190 201 . Bronfenbrenner, U. (1979). The ecology of human develop ment: Experiments by nature and design. Cambridge, MA: Harvard University Press .
PAGE 48
48 Bronfenbrenner, U., & Morris, P. A. (2007). The bioecological model of human development. In W. Da mon & R. Lerner (Eds.) Handbook of Child Psychology (pp. 793 828). New York: Wiley. Cartwright, K.B.; Bock, A.M.; Coppage, E.A.; Hodgkiss, M.D.; Nelson, M.I. (2017). A comparison of cognitive flexibility and metalinguistic skills in adult good and poor comprehenders. Journal of Research in Reading , 40, 139 152. Csardi, G., & Nepus z, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems , 1695(5), 1 9. Cuartero, M., Rossi, E., Navarro, E., & y Cabo, D. P. (2023). Mind the net! Unpacking the contributions of social network science for heritage and Bilingualism research. Research Methods in Applied Linguistics , 2 (1), 100041. Deluca, V., Rothman, J., & Pliatsikas, C. (2019). Linguistic immersion and structural effects on the bilingual brain: A longitudinal study. Bilingualism , 22(5), 1160 1175. De Koninck et al., 1988 J. De Koninck, G. Christ, N. Rinfret, G. Proulx Dreams during language learning: When and how is the new language integrated? Psychiatric Journal of the University of Ottawa , 13 (1988), pp. 72 74 . Ellwardt, L., Van Tilbur g, T. G., & Aartsen, M. J. (2015). The mix matters: Complex personal networks relate to higher cognitive functioning in old age. Social Science & Medicine , 125, 107 115. Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identificat ion of a target letter in a nonsearch task. Perception & Psychophysics, 16 (1), 143 149. Green, D.W.; Abutalebi, J. (2013). Language control in bilinguals: The adaptive control hypothesis. Journal of Cognitive Psychology , 25, 515 530.
PAGE 49
49 Gullifer , J. W., Chai, X. J., Whitford, V., Pivneva, I., Baum, S., Klein, D., & Titone, D. (2018). Bilingual experience and resting state brain connectivity: Impacts of L2 age of acquisition and social diversity of language use on control networks. Neuropsychologi a , 117 , 123 134. Gullifer, J. W., & Titone, D. (2018). Compute language entropy with {languageEntropy}. Retrieved from https://github.com/jasongullifer/languageEntropy Gullifer, J., & Titone , D. (2020). Characterizing the social diversity of bilingualism using language entropy. Bilingualism: Language and Cognition , 23(2), 283 294. Hoff, E., Core, C., Place, S., Rumiche, R., Señor, M., & Parra, M. (2012). Dual language exposure and early bilin gual development. Journal of Child Language , 39(1), 1 27. Jensen, A. R. (1965). Scoring the Stroop test. Acta Psychologica , 24, 398 408. Jokar, E., & Mosleh, M. (2019). Community detection in social networks based on improved Label Propagation Algorithm a nd balanced link density. In Physics Letters, Section A: General, Atomic and Solid State Physics (Vol. 383, Issue 8). Keller, T. A., & Just, M. A. (2016). Structural and functional neuroplasticity in human learning of spatial routes. NeuroImage , 125, 256 2 66. Kennedy, D. (2009, 2022). EgoWeb 2.0, computer software, http://egoweb.info . Krenz, T., Krivitsky, P. N., Vacca, R., Bojanowski, M., & Herz, A. (2020). egor: Import and analyze ego centered network data. R package. V ersion 0.20.03 https://CRAN.R pr oject.org/package=egor. Developmental science , 10(1), 110 120.
PAGE 50
50 Li, P., Zhang, F., Yu, A., & Zhao, X. (2019). Language History Questionnaire (LHQ3): An enh anced tool for assessing multilingual experience. Bilingualism: Language and Cognition , 23, 938 944. Applied Psycholinguistics, 1 15. Luo, L., Luk , G., & Bialystok, E. (2010). Effect of language proficiency and executive control on verbal fluency performance in bilinguals. Cognition , 114(1), 29 41. MacLeod, C. M. (1991). Half a century of reseach on the stroop effect: An integrative review. Psycholo gical Bulletin , 109(2), 163 203. Applied Psycholinguistics, 42 (2), 527 548. Marian, V.; Blumenfeld, H.K.; Kaushanskaya, M. (2007). The Language Experience and Proficiency Questionnaire (LEAP Q): Assessing Language Profiles in Bilinguals and Multilinguals. Journal of Speech Language & Hearing. Res .,50, 940 967. Milroy, L. (1980). Social network and language maintenance. Language, Communication and Education , 70. Milroy, J., & Milroy, L. (1985). Linguistic change, social network and speaker innovation. Journal of Linguistics , 21(2), 339 384. Molina, J.L.; McCarty, C.; Lubbers, M.J.; Vacca, R. Conducting Personal Network Research: A Practical Guide; Guilford Pu blications : New York, NY, USA, 2019. Navarro, E., DeLuca, V. & Rossi, E. (2022). It Takes a Village: using network science to identify the effect of individual differences in bilingual experience for theory of mind. Brain Sciences ,12, 48 506.
PAGE 51
51 Navarro, E.; DeLuca, V.; Rossi, E. It Takes a Village: Using Network Science to Identify the Effect of Individual Differences in Bilingual Experience for Theory of Mind. Brain Sciences . 2022, 12, 487. Noble KG, Houston SM, Kan E, Sowell ER. (2012). Neural correlates of socioeconomic status in the developing human brain. Developmental Science, 15:516 527. Quesque, F.; Rossetti, Y. What Do Theory of Mind Tasks Actually Measure? Theory and Practice. Perspectives of Psychological Science . 2020, 15, 384 396 . R C ore Team. (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R project.org . Rodriguez Fornells, A.; Krämer, U.M.; Lorenzo Seva, U.; Festman, J.; Mün te, T.F. (2012). Self Assessment of Individual Differences in Language Switching. Frontiers in Psychology , 2, 388. Sabourin, L., & V n erte, S. (2015). The bilingual advantage in the Stroop task: Simultaneous vs. early bilinguals. Bilingualism: Language and Cognition, 18 (2), 350 355. Scarpina, F., & Tagini, S. (2017). The stroop color and word test. Frontiers in Psychology , 8(APR). Scheele, A., Leseman, P., & Mayo, A. (2010). The home language environment of monolingual and bilingual children and their language proficiency. Applied Psycholinguistics , 31(1), 117 140. Simon, J. R., & Small, A. M., Jr. (1969). Processing auditory information: Interference from an irrelevant cue. Journal of Applied Psychology , 53(5), 433 435. Stroop, J. R. (1935). Studies o f interference in serial verbal reactions. Journal of Experimental Psychology , 18(6), 643 662 .
PAGE 52
52 Surrain, S., & Luk, G. (2019). Describing bilinguals: A systematic review of labels and descriptions used in the literature between 2005 2015. Bilingualism: Lang uage and Cognition , 22(2), 401 415. Tiv, M., Kutlu, E., & Titone, D. (2021). Bilingualism Moves us Beyond the Ideal Speaker Narrative in Cognitive Psychology. In W. Francis (Ed.), Bilingualism across the lifespan: Opportunities and challenges for cognitive research in a global society (1st ed. pp. 1 18). Routledge . Tiv, M., Kutlu, E., Gullifer, J. W., Feng, R. Y., Doucerain, M. M., & Titone , D. A. (2022). Bridging interpersonal and ecological dynamics of cognition through a systems framework of bilingualism. Journal of Experimental Psychology: General, 151 (9), 2128 2143. nd Perspectives: General and LanguageSpecific Social Network Structure Predict Mentalizing Across Diverse Sociolinguistic Contexts. Canadian Journal of Experimental Psychology . Tiv, M.; Gullifer, J.W.; Feng, R.Y.; Titone, D. Using network science to map w hat Montréal bilinguals talk about across languages and communicative contexts. J. Neurolinguist. 2020, 56, 100913. Vacca, R. (2020). Structure in personal networks: Constructing and comparing typologies. Network Science, 8 (2), 142 167. Valente, T. W. (2012). Network interventions. In Science (Vol. 336, Issue 6090). von Bastian CC, Locher A, Ruflin M. (2013). Tatool: a Java based open source programming framework for psychological studies. Behavioral Research Methods . Mar;45(1):108 15.
PAGE 53
53 Appendix I Informed Consent Please read this document carefully before you decide to participate in this research study. Your participation is voluntary, and you can decline to participate, or withdraw consent at any time, with no consequences. Study Title: The effect of language on decision making (IRB202100964) Person(s) conducting the research: PI: Dr. Eleonora Rossi: Eleonora.rossi@ufl.edu (Department of Linguistics) Purpose of the research study: You are invited to take part in a research project. The goal is to understand how bilingual language use changes across the life span, and how that can shape our social network. In addition, we will try to understand how bilingual language use can shape cognition. Eligibility: To participate, you need to be between the ages of 18 45. You will be a native speaker of English who also speaks Spanish from childhood. What you will be asked to do in the study: During the study, you will meet with UF researchers via Zoom for a virtual social network interview. The researchers will ask you some simple questions regarding your language use, and how you use it with your friends and family members. After the social network survey, you will complete three short cognitive t asks (online) via your computer. The researcher will guide you in the process, and will explain how you can complete the tasks. In order to participate, you will make an appointment with the researchers and you will briefly interact via Zoom before startin g the study. During the Zoom interaction with the researcher, you will have the chance to be introduced to the tasks and ask any questions before starting the study. Time required: This study will take between 2.5 and 3 hours. There will be a short break in between for you to relax. Risks and Benefits: Risks: The risks that you run are no more than what a typical person experiences on a regular day. In this task you will answer some easy questions on your language use and how you use your languages with your family friends and family; you will also complete a short battery of cognitive tasks. You will be able to decide not to start the study and/or you will be able to terminate it at any time. You might experience some screen fatigue, but you can termina te the study at any time. You can decide to withdraw from the survey at any time for any reason, and you will still be compensated for your time. Benefits: We do not expect the study to
PAGE 54
54 benefit you personally, but you will experience what it means to parti cipate in a psycholinguistic online study. This study is also intended to benefit the general scientific community. Compensation: This study will be voluntary, and you will be compensated $30. The study will last between 2.5 and 3 hours, and you will be compensated via an Amazon gift card for your time. Were you to decide to stop the study you will be able to do so at any time, and you will still be compensated for the time you participated. Confidentiality: Your participation will be confidential to the extent provided by law. Your identity will be kept completely de identified and confidential. Your information will be de identified and you will be given a random ID number and none of your personal information will be shared. Only the researchers wi ll have access to the information we collect online. There is a minimal risk that security of any online data may be breached, but since no identifying information will be collected, and the tool we use (EgoWeb and FindingFive) uses encryption and other fo rms of protections, it is unlikely that a security breach of the online data will result in any adverse consequence for you. Voluntary participation: Your participation in this study is completely voluntary. There is no penalty for not participating. Right to withdraw from the study: You have the right to withdraw from the study at any time without consequence. Who to contact if you have questions about the study Eleonora Rossi Ph.D.; Department of Linguistics, University of Florida, Gainesville, FL; phone 352 294 7453 If you wish to discuss the information above or any discomforts you may experience, please ask questions now or contact one of the research team members listed at the top of this form. If you have any questions regarding your right s as a research subject, please contact the Institutional Review Board (IRB02) office (University of Florida; PO Box 100173; Gainesville, FL 32610; (352) 392 0433 or irb2@ufl.edu.)
PAGE 55
55 Appendix II Interview Questions Ego ID close this window. ---Please enter the first three letters of your fi rst name in lowercase. ---Please enter the first three letters of your last name in lowercase. ---Please enter today's date and the time at which you are taking the survey. ---To the experimenter: Please input the code that is unique to you. --Complete the tasks at https://www.tatool web.com/#!/public/8591e0ba e809 4770 82a4 7e8346f0dd6c and enter your completion code here. ---You have finished part 1 of the experiment. If you would like, you may now take a 5 minute break.
PAGE 56
56 1) Sociodemographics First, we will ask you some questions about yourself. ---[age_ego] {Numeric} 1.1 In what year were you born? ---[gender] {Select one} 1.2 What is your gender? Male = 1, Female = 2, Non binary = 3, Other = 4 (Specify) ---[his panic_general] {Select one} 1.3 Do you identify as a person of Hispanic or Latino/a origin? No = 0, Yes = 1, Unsure = 2 ---[hispanic_specific] {Select one} 1.3.1 [If yes = 1 OR unsure = 2 in 1.3] Please select the ethnic origin that best applies to you. Mexican, Mexican American, Chicano/a = 1, Puerto Rican = 2, Cuban = 3, Other Hispanic origin = 4 (Specify) ---[race] {Select one} 1.4 Please select the racial category that best applies to you. White (Spaniard, Portuguese, Italian, Middle East, etc.) = 1, Black or Afro Latino, African Diaspora = 2, Indigenous (Mayan, Quechua, Aymara, etc.) = 3, Asian (Chinese, Japanese, Filipino, South Asian, etc.) = 4, Multiracial (If your ancestry combines two or more races) = 5 (Specify) ---[handedness] {Select one} 1.5 Are you right handed? Yes = 1, No = 0
PAGE 57
57 ---[occupation] {Select one or more} 1.6 What is your occupation? Select all that apply. If you select either of the two job options, a box will pop up where you can specify the industry in which you work. part time student = 1, full time student = 2, part time job (ex. hourly job, internship, work/study) = 3 (specify industry), full t ime job = 4 (specify industry), self employed = 5, unemployed = 0 ---[education] {Select one} 1.7 What is your highest completed level of education? elementary school = 1, middle school = 2, high school = 3, = 5 doctorate degree = 7, other = 8 ---[education_detail] {Text response} 1.8 Please provide more detail about your schooling background when you were under the age of 18, including the number of different schools you attended, whet her they were public or private, and whether they were in your neighborhood or not. Please avoid using terms like "elementary school," "middle school," and "grade" in your response, as the ages defined by these terms vary depending on location. Example re sponse: I attended one private school from the ages of 5 to 13 which was not in my neighborhood. Then, I attended one public school in my neighborhood from the ages of 14 to 17. ---[mother_education] {Select one} completed level of education? If her degree was completed outside the US, please select the closest equivalent from this list. elementary school = 1, middle school = 2, high school = 3, doct orate degree = 7, other = 8
PAGE 58
58 ---[father_education] {Select one} outside the US, please select the closest equivalent from this list. elementary school = 1, middle school = 2, high school = 3, doctorate degree = 7, other = 8 ---[country_origin] {Text response} 1.11 In what country were you born? ---[country_residence] {Text response} 1.12 What is your current country of permanent residence? In other words, in what country do you live most of the time? ----[zipcode_current] {Numeric} 1.13 What is your current zip code? ---[zipcode_alternate] {Numeric} 1.14 If you would say you also live/ha ve lived in another American zip code for a prolonged amount of time (ex. your childhood home), please list the zip code here. If not, please enter 999. ---[travel] {Select one} 1.15 Have you ever lived or traveled in countries other than your country o f residence or country of origin for three months or more? yes = 1, no = 0 ---[countries_traveled] {Text response} 1.15.1 [If yes = 1 in 1.15] Please name the country/countries. If you have lived in or traveled to more than one country, please list them all separated by commas.
PAGE 59
59 2) Native Language Information [native_languages] {Name generator} 2.1 Please mention the language(s) you learned at birth or before the age of five, also known as your native language(s). A native language is a language you started learning at birth and/or that you were exposed to within your family starting from childhood. ---[native_years] {Numeric} 2.2 What is the total number of years you have spent using your native language(s)? ---[native_age_listening] {Numeric} 2.3 At what age did you start listening to your native language(s)? If you learned a language from birth, please input an age of 0. If you never listened to your native language(s), please input 999. ---[native_age_speaking] {Numeric} 2.4 At what age di d you start speaking your native language(s)? For example, if you began speaking a language at the age of 1, please input 1. If you never spoke your native language(s), please input 999. ---[native_age_reading] {Numeric} 2.5 At what age did you start re ading in your native language(s)? For example, if you began reading in a language at the age of 5, please input 5. If you never read in your native language(s), please input 999. ---[native_age_writing] {Numeric} 2.6 At what age did you start writing in your native language(s)? For example, if you began writing in a language at the age of 5, please input 5. If you never wrote in your native language(s), please input 999. ---[native_ability_listening] {Select one} 2.7 Rate your current ability in terms of listening to your native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7
PAGE 60
60 ---[native_ability_speaking] {Select one} 2.8 Rate your current ability in terms of speaking in your native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7 ---[native_ability_reading] {Select one} 2.9 Rate your current ability in terms of reading in your native language(s). Very poor = 1, Poor = 2, Limited = 3, Avera ge = 4, Good = 5, Very good = 6, Excellent = 7 ---[native_ability_writing] {Select one} 2.10 Rate your current ability in terms of writing in your native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7 ---[contexts_native] {Select one or more} 2.11 Indicate the social contexts in which you use your native language(s). Check all that apply. at home = 1, with friends = 2, at school = 3, at work = 4, social media = 5, other media (ex. language softwa re, print or online news article) = 6 ---[tv_native] {Numeric}
PAGE 61
61 2.12 Estimate how many hours per week you spend watching television or online streaming in each of your native languages. Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[radio_native] {Numeric} 2.13 Estimate how many hours per week you spend listening to the radio (music, news, podcasts, etc.) in each of your native languages. Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[reading_native] {Numeric} 2.14 Estimate how many hours per week you spend reading (e.g. for school/work, for fun) in each of your native languages. Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[internet_native] {Numeric} 2.15 Estimate how many hours per w eek you spend using social media/the internet in each of your native languages. Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[family_native] {Numer ic} 2.16 Estimate how many hours per week you spend speaking with your family members in each of your native languages. Please only use one number in your estimation. ---[friends_native] {Numeric} 2.17 Estimate how many hours per week you spend speaking with your friends in each of your native languages. Include significant others in this category if you did not include them as family members (e.g. married partners). Please only use one number in your estimation. ---[classmates_native] {Numeric} 2.18 Estimate how many hours per week you spend speaking with classmates in each of your native languages. If you do not have classmates, please put 999. Please only use one number in your estimation.
PAGE 62
62 ---[others_native] {Numeric} 2.19 Estimate how many hours per week you spend speaking with others (e.g. co workers, roommates) in each of your native languages. Include anyone in the work environment in this category (e.g. if you are a teacher, include students as co workers). Please only use one number in your e stimation. ---[thinking_native] {Select one} 2.20 How often do you think in your native language(s)? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[selftalk_native] {Select one} 2.21 How often do you talk to yourself in your native language(s)? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[emotion_native] {Select one} 2.22 How often do you express emotion in your native language(s)? This includes shouting, cursing, showing affection, etc. never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[dreaming_native] {Select one} 2.23 How often do you dream in your native language(s)? never = 1, rarely = 2,
PAGE 63
63 sometimes = 3, regu larly = 4, often = 5, usually = 6, always = 7 3) Non Native Language Information [nonnative_languages] {Name generator} 3.1 Please mention any language(s) you have learned/started learning after the age of five, also known as your non native language(s). If you have not learned any languages after this age, please proceed to the next question. ---[nonnative learning] {Select one or more} 3.2 Indicate the way you learned your non native language(s). NB: Immersion refers to immigrating to another country where the dominant language is different from your native language. Therefore, you learn this language through immersion in the language environment. immersion = 1, classroom instruction = 2, self learning = 3, other = 4 (specify) ---[n onnative_years] {Numeric} 3.3 What is the total number of years you have spent using your non native language(s)? ---[nonnative_age_listening] {Numeric} 3.4 At what age did you start listening to your non native language(s)? If you never listened to you r non native language(s), please input 999. ---[nonnative_age_speaking] {Numeric} 3.5 At what age did you start speaking your non native language(s)? If you never spoke your non native language(s), please input 999. ---[nonnative_age_reading] {Numeri c} 3.6 At what age did you start reading in your non native language(s)? If you never read in your non native language(s), please input 999. ---[nonnative_age_writing] {Numeric}
PAGE 64
64 3.7 At what age did you start writing in your non native language(s)? If yo u never wrote in your non native language(s), please input 999. ---[nonnative_ability_listening] {Select one} 3.8 Rate your current ability in terms of listening to your non native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7 ---[nonnative_ability_speaking] {Select one} 3.9 Rate your current ability in terms of speaking in your non native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7 --[nonnative_ability_reading] {Select one} 3.10 Rate your current ability in terms of reading in your non native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7 ---[nonnative_ability_writing] {Select one} 3.11 Rate your current ability in terms of writing in your non native language(s). Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6, Excellent = 7
PAGE 65
65 ---[contexts_nonnative] {Select one or more} 3.12 Indicate the socia l contexts in which you use your native language(s). Check all that apply. at home = 1, with friends = 2, at school = 3, at work = 4, social media = 5, other media (ex. language software, print or online news article) = 6 ---[tv_nonnative] {Numeric} 3.13 Estimate how many hours per week you spend watching television or online streaming in your non native language(s). Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately a s possible. ---[radio_nonnative] {Numeric} 3.14 Estimate how many hours per week you spend listening to the radio (music, news, podcasts, etc.) in your non native language(s). Please only use one number in your estimation. *Note that the hours do not n eed to total to any amount. Please estimate as accurately as possible. ---[reading_nonnative] {Numeric} 3.15 Estimate how many hours per week you spend reading (e.g. for school/work, for fun) in your non native language(s). Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[internet_nonnative] {Numeric} 3.16 Estimate how many hours per week you spend using social media/the internet in your non native l anguage(s). Please only use one number in your estimation. *Note that the hours do not need to total to any amount. Please estimate as accurately as possible. ---[family_nonnative] {Numeric} 3.17 Estimate how many hours per week you spend speaking with your family members in your non native language(s). Please only use one number in your estimation.
PAGE 66
66 ---[friends_nonnative] {Numeric} 3.18 Estimate how many hours per week you spend speaking with your friends in your non native language(s). Include significant others in this category if you did not include them as family members (e.g. married partners). Please only use one number in your estimation. ---[classmates_nonnative] {Numeric} 3.19 Estimate how many hours per week you spend speaking with c lassmates in your non native language(s). Please only use one number in your estimation. ---[others_nonnative] {Numeric} 3.20 Estimate how many hours per week you spend speaking with others (e.g. co workers, roommates) in your non native language(s). In clude anyone in the work environment in this category (e.g. if you are a teacher, include students as co workers). Please only use one number in your estimation. ---[thinking_nonnative] {Select one} 3.21 How often do you think in your non native languag e(s)? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[selftalk_nonnative] {Select one} 3.22 How often do you talk to yourself in your non native language(s)? never = 1, rarely = 2, sometimes = 3, regularly = 4 , often = 5, usually = 6, always = 7 ---[emotion_nonnative] {Select one} 3.23 How often do you express emotion in your non native language(s)? This includes shouting, cursing, showing affection, etc. never = 1, rarely = 2,
PAGE 67
67 sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[dreaming_nonnative] {Select one} 3.24 How often do you dream in your non native language(s)? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 4) General Language Skills [languages_0 4] {Text response} 4.1.1 Indicate what language(s) you could understand and speak in the following age ranges. If you could understand and speak more than one language in the same age range, please list all of the languages separated by commas . Be sure to include all the languages you have listed up to this point (your native and non native languages). (0 4) ---[languages_5 10] {Text response} 4.1.2 Indicate what language(s) you could understand and speak in the following age ranges. If you could understand and speak more than one language in the same age range, please list all of the languages separated by commas. Be sure to include all the languages you have listed up to this point (your native and non native languages). (5 10) ---[langu ages_11 17] {Text response} 4.1.3 Indicate what language(s) you could understand and speak in the following age ranges. If you could understand and speak more than one language in the same age range, please list all of the languages separated by commas. Be sure to include all the languages you have listed up to this point (your native and non native languages). (11 17) ---[languages_18+] {Text response} 4.1.4 Indicate what language(s) you could understand and speak in the following age ranges. If you cou ld understand and speak more than one language in the same age range, please list all of the languages separated by commas. Be sure to include all the languages you have listed up to this point (your native and non native languages). (18+)
PAGE 68
68 ---[language_ skill] {Select one} 4.2 Rate your language learning skill. In other words, how good do you feel you are at learning new languages, relative to your friends or other people you know? Very poor = 1, Poor = 2, Limited = 3, Average = 4, Good = 5, Very good = 6 , Excellent = 7 ---[mix_family_languages] {Text response} 4.3.1.1 If you use mixed languages in daily life, please indicate the languages that you mix with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. If you do not mix languages with a particular group of people, please enter "N/A" into the box. (family members) Example response: "English, Spanish" ---[mix_friends_languages] {Text response} 4 .3.1.2 If you use mixed languages in daily life, please indicate the languages that you mix with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. If y ou do not mix languages with a particular group of people, please enter "N/A" into the box. (friends) Example response: "English, Spanish" ---[mix_classmates_languages] {Text response} 4.3.1.3 If you use mixed languages in daily life, please indicate t he languages that you mix with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. If you do not mix languages with a particular group of people, please enter "N/A" into the box. (classmates) Example response: "English, Spanish" ---[mix_others_languages] {Text response} 4.3.1.4 If you use mixed languages in daily life, please indicate the languages that you mix with the following groups of people. Lang uage mixing would include using both languages with the same person and using both languages in the same conversation. If you do not mix languages with a particular group of people, please enter "N/A" into the box. (others) Example response: "English, Spa nish"
PAGE 69
69 ---[mix_family_frequency] {Select one} 4.3.2.1 [If response in 4.3.1.1] Please estimate how much you mix in normal conversation with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. (family members) rarely = 1, sometimes = 2, regularly = 3, often = 4, usually = 5, always = 6 ---[mix_friends_frequency] {Select one} 4.3.2.2 [If response in 4.3.1.2] Please estimate how much you mix in normal conversation with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. (friends) rarely = 1, sometimes = 2, regularly = 3, often = 4, usually = 5, alway s = 6 ---[mix_classmates_frequency] {Select one} 4.3.2.3 [If response in 4.3.1.3] Please estimate how much you mix in normal conversation with the following groups of people. Language mixing would include using both languages with the same person and us ing both languages in the same conversation. (classmates) rarely = 1, sometimes = 2, regularly = 3, often = 4, usually = 5, always = 6 ---[mix_others_frequency] {Select one} 4.3.2.4 [If response in 4.3.1.4] Please estimate how much you mix in normal c onversation with the following groups of people. Language mixing would include using both languages with the same person and using both languages in the same conversation. (others) rarely = 1, sometimes = 2, regularly = 3, often = 4,
PAGE 70
70 usually = 5, always = 6 ---[comfort_home_listen] {Text response} 4.4.1 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at home? You may indicate the same language for all or some of the fields below. (listening) ---[comfort_home_speak] {Text response} 4.4.2 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at home? You may indicate the same language for all or some of the fields below. (speaking) ---[comfort_home_read] {Text response} 4.4.3 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at home? You may indicate the same language for all or some of the fi elds below. (reading) ---[comfort_home_write] {Text response} 4.4.4 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at home? You may indicate the same language for all or some of t he fields below. (writing) ---[comfort_friends_listen] {Text response} 4.5.1 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing with friends? You may indicate the same language for al l or some of the fields below. (listening) ---[comfort_friends_speak] {Text response} 4.5.2 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing with friends? You may indicate the same language for all or some of the fields below. (speaking) ---[comfort_friends_read] {Text response} 4.5.3 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing with friends? You may indic ate the same language for all or some of the fields below. (reading) ---
PAGE 71
71 [comfort_friends_write] {Text response} 4.5.4 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing with friends? You may indicate the same language for all or some of the fields below. (writing) ---[comfort_school_listen] {Text response} 4.6.1 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing a t school? You may indicate the same language for all or some of the fields below. If you do not currently attend school, please write N/A. (listening) ---[comfort_school_speak] {Text response} 4.6.2 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at school? You may indicate the same language for all or some of the fields below. If you do not currently attend school, please write N/A. (speaking) ---[comfort_school_read] {Text resp onse} 4.6.3 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at school? You may indicate the same language for all or some of the fields below. If you do not currently attend school, p lease write N/A. (reading) ---[comfort_school_write] {Text response} 4.6.4 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at school? You may indicate the same language for all or some of the fields below. If you do not currently attend school, please write N/A. (writing) ---[comfort_work_listen] {Text response} 4.7.1 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at work? You may indicate the same language for all or some of the fields below. If you do not currently work, please write N/A. (listening) ---[comfort_work_speak] {Text response} 4.7.2 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at work? You may indicate the same language for all or some of the fields below. If you do not currently work, please write N/A. (speaking) ---[comfort_work_read] {Text response} 4.7.3 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at work? You may indicate the same language for all or some of the fields below. If you do not currently work, please write N/A. (reading )
PAGE 72
72 ---[comfort_work_write] {Text response} 4.7.4 In which language do you communicate best or feel most comfortable in terms of listening, speaking, reading, and writing at work? You may indicate the same language for all or some of the fields below. If you do not currently work, please write N/A. (writing) ---[dialect_general] {Select one} 4.8 Do you also speak/use any dialects of the language(s) you know? A dialect is broadly defined as a spoken language that might not be officially recognized but is still used for communication within a certain geographical region. If you select yes, a box will pop up where you can specify what dialect(s) you speak. yes = 1 (specify), no = 0 ---[dialect_hours] {Numeric} 4.8.1 [If yes = 1 in 8.8] How many hours per week do you speak in dialect(s)? ---In the following questions, please try to answer to what degree each description is representative of the manner you use to talk or speak in the language(s) you know. Some of these questions ask you to report yo ur tendency to switch or mix languages during a conversation. Switching and mixing languages is a characteristic of some bilingual contexts or environments. If you have doubts about how to rate yourself in the following questions, please try to compare you r manner of speaking and talking with that of most people, or those who you know very well. [BSQ1] {Select one} 4.9.1 I do not remember or I cannot recall some words in Spanish when I am speaking in English. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ1A] {Select one} 4.9.2 I do not remember or I cannot recall some words in English when I am speaking in Spanish. never = 1, very infrequently = 2, occasionally = 3, frequently = 4,
PAGE 73
73 always = 5 [BSQ2] {Select one} 4.9.3 I tend to switch languages during a conversation (for example, I switch from English to Spanish or vice versa). never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ3] {Select one} 4.9.4 I do not realize when I switch the lan guage during a conversation (e.g., from English to Spanish) or when I mix the two languages; I often realize it only if I am informed of the switch by another person. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ4] {Select one} 4.9.5 When I switch languages, I do it consciously. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ5] {Select one} 4.9.6 It is difficult for me to control the language switches I introduce during a conversa tion (e.g., from English to Spanish). never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ6] {Select one} 4.9.7 Without intending to, I sometimes produce a word in Spanish faster when I am speaking in English. never = 1, ver y infrequently = 2, occasionally = 3, frequently = 4, always = 5
PAGE 74
74 [BSQ6A] {Select one} 4.9.8 Without intending to, I sometimes produce a word in English faster when I am speaking in Spanish. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ7] {Select one} 4.9.9 There are situations in which I switch between the two languages. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 [BSQ8] {Select one} 4.9.10 There are certain topics or issues for whi ch I normally switch between the two languages. never = 1, very infrequently = 2, occasionally = 3, frequently = 4, always = 5 ---For the following questions, think back on your life over the past three months. Then, read each scenario below. Choose the answer that corresponds to whether or not the scenario has occurred in your life in the past three months. [MASI1_occurred] {Select one} 4.10.1.1 I feel uncomfortable being around people who only speak Spanish. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI1A_occurred] {Select one} 4.10.1.2 I feel uncomfortable being around people who only speak English. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI2_occurred] {Select one} 4.10.1.3 I feel pressure to learn Spanish. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0
PAGE 75
75 [M ASI2A_occurred] {Select one} 4.10.1.4 I feel pressure to learn English. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI3_occurred] {Select one} 4.10.1.5 I have a hard time understanding others when they speak Spanish. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI3A_occurred] {Select one} 4.10.1.6 I have a hard time understanding others when they speak English. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI4_occurred] {Select one} irly. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI4A_occurred] {Select one} Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI5_occurred] {Select one} 4.10.1.9 It bothers me when people assume that I speak Spanish. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI5A_occurred] {Select one} 4.10.1.10 It bothers me when people assume that I speak English. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI6_occurred] {Select one} 4.10.1.11 I have been discriminated against because I have difficulty speaking Spanish. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 [MASI6A_occurred] {Select one} 4.10.1.12 I have been discriminated against because I have difficulty speaking English. Yes, this has happened to me in the past three months. = 1 No, this has not happened to me in the past three months. = 0 ---
PAGE 76
76 For the following questions, indicate on the scale below how stressful each situation was for you when it occurred in the past three months. [MASI1_stressful] {Select one} 4.10.2.1 [If yes = 1 in 4.10.1.1] I feel uncomfortable being around people who only speak Spanish. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI1A_stressful] {Select one} 4.10.2.2 [If yes = 1 in 4.10.1.2] I feel un comfortable being around people who only speak English. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI2_stressful] {Select one} 4.10.2.3 [If yes = 1 in 4.10.1.3] I feel pressure to learn Spanish. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI2A_stressful] {Select one} 4.10.2.4 [If yes = 1 in 4.10.1.4] I feel pressure to learn English. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI3_stressful] {Select one} 4.10.2.5 [If yes = 1 in 4.10.1.5] I have a hard time understanding others when they speak Spanish. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5
PAGE 77
77 [MASI3A_stressful] {Select one} 4.10.2.6 [If yes = 1 in 4.10.1.6] I have a hard time understand ing others when they speak English. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI4_stressful] {Select one} Spanish well, people have treated me rudely or unfairly. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI4A_stressful] {Select one} 4.10.2.8 [If yes = 1 in 4.10.1 or unfairly. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI5_stressful] {Select one} 4.10.2.9 [If yes = 1 in 4.10.1.9] It bothers me when people assume that I speak Spanish. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI5A_stressful] {Select one} 4.10.2. 10 [If yes = 1 in 4.10.1.10] It bothers me when people assume that I speak English. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI6_stressful] {Select one} 4.10.2.11 [If yes = 1 in 4.10.1.11] I have been discriminated against because I have difficulty speaking Spanish.
PAGE 78
78 not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extremely stressful = 5 [MASI6 A_stressful] {Select one} 4.10.2.12 [If yes = 1 in 4.10.1.12] I have been discriminated against because I have difficulty speaking English. not at all stressful = 1, slightly stressful = 2, somewhat stressful = 3, moderately stressful = 4, extre mely stressful = 5 ---[comments_ego] {Text response} 4.11 Use the comment box below to provide any other information you feel is important to include with your responses. This may include providing additional answers to any of the questions above in a w ay that you feel better describes your language background or usage. ---You have finished part 2 of the experiment. You may now take a 5 minute break.
PAGE 79
79 Social Network Questions Early Name Generator & Interpreters Now we will ask you to think back on your life when you were a child, between the ages of 0 and 13. Please take a moment to think about the relationships you had during this time with anyone from family to friends and peers. ---Please mention the names of 15 people that you knew when you were between the ages of 0 and 13 (until you finished middle school). You do not need to have contact with them today to include them here. Please only include people that you interacted with on at least a weekly basis during that time. 1) First, write do wn five family members that you interacted with during this time. 2) Then, write down five friends that you interacted with during this time. 3) Finally, write down five classmates that you weren't friends with that you interacted with during this time. *Note that you do NOT need to enter the full names of these people as they will not be contacted few brief questions about each of the people you mention here. ---You will now be asked questions about your relationships with each of the individuals you mentioned in the previous question. Socio Demographic Information Early Period [age_first_early] {Numeric} 5.1 Approximately how old was each person the first time you interacted when you were between 0 and 13 years old? ---[age_current_early] {Numeric} 5.2 Approximately how old is each person now? If they have passed away, please enter 999. ---[gender_early] {Select one} 5.3 What gender category best applies to each person?
PAGE 80
80 Male = 1, Female = 2, Non binary = 3, Other = 4 (Specify) ---[hispanic_genera l_early] {Select one} 5.4 Are any of these people of Hispanic or Latino/a origin? no = 0 yes = 1, unsure = 2 ---[hispanic_specific_early] {Select one} 5.4.1 [If yes = 1 OR unsure = 2 in 5.4] Please select the ethnic origin that best applies to each pers on. Mexican, Mexican American, Chicano/a = 1, Puerto Rican = 2, Cuban = 3, Other Hispanic origin = 4 (Specify), ---[race_early] {Select one} 5.5 Please select the racial category that best applies to each person. White (Spaniard, Portuguese, Italian, Middle East, etc.) = 1, Black or Afro Latino, African Diaspora = 2, Indigenous (Mayan, Quechua, Aymara, etc.) = 3, Asian (Chinese, Japanese, Filipino, South Asian, etc.) = 4, Multiracial (If their ancest ry combines two or more races) = 5 (Specify) ---[country_origin_late] {Text response} 5.6 In what country was each person born? 2 ---[relationship_early] {Select one} 5.7 What type of relationship did you have with eac h person when you were between the ages of 0 and 13? If two of these categories apply to the same person, please just select the one that is the most characteristic of your relationship with them. Close family (e.g. parents/guardians, siblings, grandpare nts) = 1, Extended family (e.g. aunts/uncles, cousins) = 2, Elementary/middle/high school friend = 3, Classmate/workmate/colleague = 4,
PAGE 81
81 Other = 5 (Specify) ---[closeness_early] {Select one} 5.8 How emotionally close did you feel to each person when you were between the ages of 0 and 13? not at all close = 1, slightly close = 2, somewhat close = 3, moderately close = 4, extremely close = 5 Early Period [language_early] {Text response} 6.1 What languages did y ou use with each person every time you interacted when you were between 0 and 13 years old? Please list all applicable languages for each individual separated by commas. ---Some people switch between the languages they know during a conversation. For e xample, while interacting with someone in one language, they may use sentences or words from the other [switch_frequency_early] {Select one} 6.2 How often do you estimate that you e ngaged in language switching with each person when you were between 0 and 13 years old? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---[comments_early] {Text response} 6.3 Is there any other information about the language(s) you used in your typical interactions with each person when you were between 0 and 13 years old that you feel is important to note? 7) Pair Language Information Early Period [pair_early] {Select one} 7.1 To the best of your knowledge, d id $$1 and $$2 communicate regularly or maintain a regular relationship with each other when you were between 0 and 13 years old?
PAGE 82
82 yes = 1, no = 0, maybe = 2 ---[language_pair_early] {Text response} 7.1.1 [If yes = 1 OR maybe = 2 in 7.1] What language(s) did $$1 and $$2 generally use with each other when you were between 0 and 13 years old? Please list all applicable languages separated by commas. ---[pair_switch_frequency_early] {Select one} 7.1.2 [If yes = 1 OR maybe = 2 in 7.1] How often do you esti mate that $$1 and $$2 engaged in language switching when you were between 0 and 13 years old? never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 [comments_pair_early] {Text response} 7.1.3 [If yes = 1 OR maybe = 2 in 7.1] Is there any other information about the relationship between $$1 and $$2 that you feel is important to note? Late Name Generator & Interpreters Please mention the names of 15 people that you have known/interacted with from when you were between 14 years old to today. To the experimenter: if the participant repeats a name from 1) First, write down five family members that you interact with. 2) Then, write down five friends that you interact with. 3) Finally, write down five classmates or coworkers that you aren't friends with that you interact with. ---You will now be asked questions about your relationships with each of the individuals you mentioned in the pre vious question. Demographic Information Late Period
PAGE 83
83 [age_first_late] {Numeric} 8.1 Approximately how old was each person the first time you interacted in the time when you were between 14 years old to today? ---[age_current _late] {Numeric} 8.2 Approximately how old is each person now? If they have passed away, please enter 999. ---[gender_late] {Select one} 8.3 What gender category best applies to each person? Male = 1, Female = 2, Non binary = 3, Other = 4 (Specify) ---[hispanic_general_late] {Select one} 8.4 Are any of these people of Hispanic or Latino/a origin? no = 0 yes = 1, unsure = 2 ---[hispanic_specific_late] {Select one} 8.4.1 [If yes = 1 OR unsure = 2 in 8.4] Pleas e select the ethnic origin that best applies to each person. Mexican, Mexican American, Chicano/a = 1, Puerto Rican = 2, Cuban = 3, Other Hispanic origin = 4 (Specify) ---[race_late] {Select one} 8.5 Please select the racial category t hat best applies to each person. White (Spaniard, Portuguese, Italian, Middle East, etc.) = 1, Black or Afro Latino, African Diaspora = 2, Indigenous (Mayan, Quechua, Aymara, etc.) = 3, Asian (Chinese, Japanese, Filipino, South Asian, etc.) = 4, Multiracial (If their ancestry combines two or more races) = 5 (Specify) ---[country_origin_late] {Text response} 8.6 In what country was each person born?
PAGE 84
84 2 ---[relationship_late] {Select one} 8.7 What typ e of relationship do/did you have with each person? Think about the time period from when you were 14 years old to today. If two of these categories apply to the same person, please just select the one that is the most characteristic of your relationship w ith them. Close family (e.g. parents/guardians, siblings, grandparents) = 1, Extended family (e.g. aunts/uncles, cousins) = 2, Elementary/middle/high school friend = 3, College/university friend = 4, Classmate/workmate/colleague = 5, Partner = 6, Other = 7 (Specify) ---[closeness_late] {Select one} 8.8 How emotionally close do/did you feel to each person? Think about the time period from when you were 14 years old to today. not at all close = 1, slightly close = 2, somewhat close = 3, moderately close = 4, extremely close = 5 Late Period [language_late] {Text response} 9.1 What languages did/do you use with each person every time you interacted/interact? Think about the time period from when you were 14 years old to today. Please list all applicable languages for each individual separated by commas. ---[switch_frequency_late] {Select one} 9.2 How often do you estimate that you engaged/engage in language switching with each person? Think about the tim e period from when you were 14 years old to today. never = 1, rarely = 2, sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 ---
PAGE 85
85 [comments_late] {Text response} 9.3 Is there any other information about the language(s) you used in your typic al interactions with each person that you feel is important to note? Think about the time period from when you were 14 years old to today. 10) Pair Language Information Late Period [pair_late] {Select one} 10.1 To the best of your knowledge, did/do $$1 and $$2 communicate regularly or maintain a regular relationship with each other? Think about the time period from when you were 14 years old to today. no = 0, yes = 1, maybe = 2 ---[language_pair_late] {Text response} 10.1.1 [If yes = 1 OR maybe = 2 in 10.1] What language(s) did/do $$1 and $$2 generally use with each other? Think about the time period from when you were 14 years old to today. Please list all applicable languages separated by commas. --[pair_switch_frequency_late] {Select one} 10.1.2 [If yes = 1 OR maybe = 2 in 10.1] How often do you estimate that $$1 and $$2 do/did engage in language switching? Think about the time period from when you were 14 years old to today. never = 1, rarely = 2 , sometimes = 3, regularly = 4, often = 5, usually = 6, always = 7 [comments_pair_late] {Text response} 10.1.3 [If yes = 1 OR maybe = 2 in 10.1] Is there any other information about the relationship between $$1 and $$2 that you feel is important to note?
xml version 1.0 encoding UTF-8 standalone no
fcla fda yes
!-- Connecting the dots: Social Network approaches to capture variability across lifespan of bilinguals and its consequences for cognition ( Book ) --
METS:mets OBJID AA00092456_00001
xmlns:METS http:www.loc.govMETS
xmlns:xlink http:www.w3.org1999xlink
xmlns:xsi http:www.w3.org2001XMLSchema-instance
xmlns:daitss http:www.fcla.edudlsmddaitss
xmlns:mods http:www.loc.govmodsv3
xmlns:sobekcm http:digital.uflib.ufl.edumetadatasobekcm
xmlns:lom http:digital.uflib.ufl.edumetadatasobekcm_lom
xsi:schemaLocation
http:www.loc.govstandardsmetsmets.xsd
http:www.fcla.edudlsmddaitssdaitss.xsd
http:www.loc.govmodsv3mods-3-4.xsd
http:digital.uflib.ufl.edumetadatasobekcmsobekcm.xsd
METS:metsHdr CREATEDATE 2023-05-10T13:43:16Z ID LASTMODDATE 2023-05-10T10:58:54Z RECORDSTATUS COMPLETE
METS:agent ROLE CREATOR TYPE ORGANIZATION
METS:name UF,University of Florida
OTHERTYPE SOFTWARE OTHER
Go UFDC - FDA Preparation Tool
INDIVIDUAL
UFAD\renner
METS:dmdSec DMD1
METS:mdWrap MDTYPE MODS MIMETYPE textxml LABEL Metadata
METS:xmlData
mods:mods
mods:abstract lang en The need to communicate is a ubiquitous experience for humans, from infancy to older age. Recent research has sought new methods to describe the variability of bilingual language experience through measures to evaluate and characterize individual differences in bi/multilinguals and how they use language in different communicative and social contexts. In turn, little to no data is available on how characteristics of Personal Social Networks (PSN) can demonstrate variability in language use and multiplicity of language variation in different social environments. The present study adds to the emerging area of research that investigates bilingualism through the lens of PSN. A study was designed to investigate the relationships between bilingual language use and social use of two languages (i.e., Spanish, English) in different social settings, and over the lifespan of a bilingual speaker. The main goal of this study is to understand if language(s) use shapes individuals’ social networks (SN). A total of 51 Spanish/English bilinguals were tested virtually. Participants were asked to complete a series of behavioral measures to assess their cognitive control and an extensive SN interview that probed the SN from ages (0-13) and (14-present). Overall, the findings provide evidence that participants’ SN play an important role on their performance on cognitive control tasks and how their network fluctuates across lifespan.
mods:accessCondition Copyright Reinaldo Cabrera Perez. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
mods:language
mods:languageTerm type text English
code authority iso639-2b eng
mods:location
mods:physicalLocation University of Florida
mods:name
mods:namePart Cabrera Perez, Reinaldo
mods:role
mods:roleTerm creator
mods:note Awarded Bachelor of Arts, summa cum laude, on April 29, 2022. Major: Linguistics
College or School: Liberal Arts and Sciences
Advisor: Eleonora Rossi. Advisor Department or School: Linguistics. Advisor: . Advisor Department or School:
mods:originInfo
mods:publisher University of Florida
mods:dateIssued 2023
mods:recordInfo
mods:recordIdentifier source sobekcm AA00092456_00001
mods:recordContentSource University of Florida
mods:relatedItem series
mods:part
mods:detail Year
mods:caption 2023
mods:subject
mods:topic Undergraduate Honors Thesis/Project
mods:titleInfo
mods:title Connecting the dots: Social Network approaches to capture variability across the lifespan of bilinguals and its consequences for cognition
mods:typeOfResource text
DMD2
OTHERMDTYPE SOBEKCM SobekCM Custom
sobekcm:procParam
sobekcm:Aggregation ALL
UFIR
IUF
UFHONORS
UNDERGRADWORKS
sobekcm:MainThumbnail Cabrera Perez_Reinaldo_Honors_Projectthm.jpg
sobekcm:Wordmark UFIR
sobekcm:Tickler 2231_SPRING_2023_HONORS
sobekcm:bibDesc
sobekcm:BibID AA00092456
sobekcm:VID 00001
sobekcm:Publisher
sobekcm:Name University of Florida
sobekcm:Source
sobekcm:statement UF University of Florida
sobekcm:SortDate 738520
METS:amdSec
METS:digiprovMD DIGIPROV1
DAITSS Archiving Information
daitss:daitss
daitss:AGREEMENT_INFO ACCOUNT PROJECT UFDC
METS:techMD TECH1
File Technical Details
sobekcm:FileInfo
METS:fileSec
METS:fileGrp USE reference
METS:file GROUPID G1 PDF1 applicationpdf CHECKSUM 31b54dc981efd1d7c9a7e97dc4d1c045 CHECKSUMTYPE MD5 SIZE 1729713
METS:FLocat LOCTYPE OTHERLOCTYPE SYSTEM xlink:href Cabrera%20Perez_Reinaldo_Honors_Project.pdf
G2 TXT2 textplain
Cabrera%20Perez_Reinaldo_Honors_Project_pdf.txt
G3 METS3 unknownx-mets d77fb16dfdcf993566dc7b27e1ef0006 7378
AA00092456_00001.mets
METS:structMap STRUCT2 other
METS:div DMDID ADMID ORDER 0 main
ODIV1 1 Main
FILES1 Page
METS:fptr FILEID
FILES2 2
FILES3 3
|