Month: July 2022

Intro and Background 

Generation Z (those born between 1997 and 2012) grew up and learned how to communicate post-advent of the invention of instant messaging. Their texting style and speaking styles are intertwined and take inspiration from each other. On the other hand, those of Generation X (born between 1965 and 1980) had to transfer previously-established styles of humor and communication to the new technological medium (Downs, 2019). This accounts for the disconnect between considering texting to be a form of writing (like an email or letter) and considering it simply as talking put onto a screen. The term “written speech,” coined by John McWhorter, gives a name to the adaptation of texting to account for all the complexities of face-to-face communication that change how the content of a message is received: emotion, formality, humor, tone, body language and facial expression. Across platforms from iMessage to TikTok, young texters use unspoken and quickly changing combinations of punctuation, capitalization, and symbols to directly translate trends and slang into the digital world.

Methods

Following our belief that Gen X and Gen Z would communicate humor over text in significantly different ways and a path laid out by a study conducted by Sánchez-Moya and Cruz-Moya (2015), we chose to create a survey that focused on responder’s opinions on texting and their texting habits. We specifically targeted people’s habits in the use of humor markers like emojis and typed laughter by asking them to choose the most appropriate option to represent a feeling or as a response to various tonal and emotional contexts. Once we had our responses, we organized our data in terms of type of marker (emoji/emoticon/capitalization) and focused on whether the marker was used literally or creatively in relation to each generation. We expected a wider range of responses in Gen Z and more similar, literal responses from Gen X.

Results and Analysis  

We began our analysis by categorizing the responses we received in terms of whether they were literal or not, and we additionally compared the use of emoticons and capitalization. Further, we then also analyzed the frequency of answers we received for each question. We will present examples of each of these analyses and the contexts in which they were applied.

Beginning with our analysis of literal vs. non-literal use of markers, figure 2 presents a strong difference in Gen X and Gen Z’s preferences for literal and non-literal emojis.

The above graph illustrates a strong example of a general trend we found in our data: that overall, Gen X preferred to utilize emoji and other humor makers literally. In comparison, Gen Z showed a preference for less literal uses. Also, specifically for this question, within the categories of literal and non-literal, Gen X preferred a laughing emoji (😂) to show that they were laughing in 55% of their responses whereas Gen Z preferred a crying emoji (😭)–the exact opposite–to show that they were laughing in 42% of their responses. This was an even stronger non-literal response than expected suggesting a much higher degree of irony in Gen Z’s texting than in Gen X’s.

Moreover Figure 2.1 presents another strong case for Gen X’s preference for literal marker use and Gen Z’s preference for non-literal outside of just emojis. Figure 2.2 presents the response options as well as their categorization as either literal or non-literal.

Not only was Gen X’s preference for literal answers and Gen Z’s preference for non-literal answers illustrated in their selection of emojis but also in their preference for other answer types too. In the above example we took the unmarked and expected literal responses to the presented situation to be congratulatory, positive, and generally aligned with the topic of the context, whereas the non-literal responses demonstrate an indirect type of response by focusing on a non-topicalized part of the context (i.e. the bathroom). Again, we observed a strong preference from Gen X for a literal or positive response and a strong preference from Gen Z for a non-literal or indirect response.

In addition to studying the differences in how humor markers were used to convey literal and non-literal meaning we also wanted to provide insight into the different variations in the types of markers commonly used. Generally, we expected to see a more diverse use of these markers and variations, not just emojis, in Gen Z’s texting, leading us to figure 3. Figure 3 illustrates the overall differences in emoji (😂,😩) and emoticon ( :(, 🙂 ) use according to generation.

We chose to study emoji vs. emoticon use specifically as we believed that there would be a strong difference between the generations. However, both Gen X and Gen Z tended to prefer emojis. Unexpectedly, Gen X overwhelmingly preferred to use emojis over emoticons. We had thought that due to their longer history and generally less ambiguous and more established static meaning that Gen X would favor emoticons (Bai et al., 2019). This was not the case. Interestingly too, Gen Z actually tended to use more emoticons than Gen X. This result however supports our belief that Gen Z would demonstrate a broader range of humor marker use, splitting their results more evenly between emoji and emoticon. This could also demonstrate that Gen Z is exhibiting more creativity or nuanced flexibility in how they use these markers and what they take them to mean.

Next, we chose to study another variational marker, capitalization (OR SHOUTING). We chose to study capitalization in addition to emoji/emoticon differences as it is a unique action in texting that specifically denotes tone (McCulloch, 2019). Figure 4 below illustrates our comparison of capitalization use according to generation.

As shown above, Gen Z favored the use of capitalization while Gen X preferred messages that mixed capitalization and lowercase. This illustrates a stronger preference in Gen Z for using messages that convey a stronger or louder tone and demonstrates McWhorter’s idea of “written speech” in the younger generations (2017). Interestingly too, the younger generations’ relatively strong preference for “shouting” over text could indicate a recent change in what all-caps texting “means” and illustrate a higher level of comfort with the nuance of tone that all capitalized text creates. In comparison, Gen X may still interpret it as simply yelling at someone and therefore use it more sparingly. However, to corroborate those claims more testing would need to be conducted.

Finally, we got even more specific with our analyses–we categorized and analyzed the answers to each question on the survey to measure the frequency of each response per question for each generation. We did this to examine the specific texting behavior of the generations on a smaller, context-dependent scale. Figure 5 is a particularly interesting example that demonstrates the general trend in the generational behavior we observed.

We discovered, as in the above example, that Gen Z’s responses were more evenly spread out across the response options creating a much more dispersed answer graph (seen in red). Meanwhile, Gen X tended to answer more similarly to one another, strongly favoring one answer, ‘terrible 😔,’ as can be seen by the single tall blue bar. This pattern was relatively consistent across all of our data and was in line not only with our prediction that Gen Z would show a wider range of responses, but also with our prediction that Gen X would tend to use more literal responses. Moreover, another point to note in figure 5 particularly is that Gen X answered ‘terrible 😭’ 20.43% of the time, which in this context was interpreted as a literal use of a negative emoji. However, given our results in figure 1, this could also denote a more sarcastic or ironic tone. Such an analysis could also be in line with the other trend illustrated above as Gen Z showed a greater preference for answers that denote a less literal more ironic tone (terrible 🙃, terrible 😁).

Overall, our data demonstrated that Gen X tended to use emojis more literally and more consistently while Gen Z preferred to use them less literally and showed a wider range in their use. In terms of emoticons, both Gen X and Gen Z preferred emojis with Gen X showing a much stronger preference, and in cases of capitalization, Gen Z used messages in all caps much more than Gen X.

With all that said, we would like to address some possible confounds that could affect our data and analyses. Firstly, there was quite a disparity in the number of responses we received from each generation, heavily skewing toward Gen Z. This may have been because this survey was distributed by us (members of Gen Z), which also brings to light another possible issue: our own generational biases in both the analysis of the data and the creation of the survey. Additionally, this study’s construction as a multiple-choice survey poses the possibility that the choice of answers may have directed people’s responses. Moreover, we did not notice a significant effect of gender in our study. However, it could be a very interesting avenue to pursue in future research.

Discussion and Conclusion  

As seen in our data analysis, we found that there is in fact a gap in the usage of humor markers between the two generations, which supported our initial predictions. More specifically, based on the overwhelming choice by Gen X to use literal meanings, it could be suggested that they tend to use them (especially emojis) at a surface level. Meanwhile, Gen Z’s varied usage of all four markers looks to be a bit more nuanced. Their choices reflect that they use ironic and non-literal meanings frequently in humorous contexts. The variation in their responses also suggests that each marker of humor could have its own unique function or meaning depending on the context. Such variety among Gen Z could be the result of their community of practice, which frequently takes part in internet culture and has therefore been able to develop their own unique understandings of humorous texts. It also reinforces McWhorter’s earlier suggestion that texting can involve more than words–it conveys natural human conversational gestures as well. Overall, it does therefore seem fair to say that there is more at play in Gen Z’s usage.

After conducting our study, we identified limitations in our methods that leave room for improvement. As mentioned earlier, the survey was created entirely by members of Gen Z. This could prove to be problematic because the response options are potentially more biased toward a typical Gen Z response and not adequately represent typical Gen X responses. Including the input of Gen X members could have created a more balanced selection of responses. Another less obvious limitation of our study is that we did not account for phone differences. We realize that the appearance of Android and iOS emojis differ and that this difference may procure different emotional responses and therefore be used in a different context than our survey initially accounted for.

So, what are the next steps? Our findings and conclusions tell us that there is definitely room for further research on intergenerational communication over text. Improving upon this study’s weaknesses and widening its scale could provide more insights into the big differences that lie between the text-language of Gen Z and Gen X. Some new topics of interest include: different attitudes towards the appearances of emojis (i.e. Android vs. iOS), the evolution and idiosyncrasies of Gen Z’s online language, and analyses of textual gaps that may occur on the basis of factors other than generation.

References:

Bai, Q., Dan, Q., Mu, Z., & Yang, M. (2019). A Systematic Review of Emoji: Current Research and Future Perspectives. Frontiers in psychology, 10, 2221. https://doi.org/10.3389/fpsyg.2019.02221

Downs, H. (2019). Bridging the Gap: How the Generations Communicate. Concordia Journal of Communication Research, 6. https://doi.org/10.54416/SEZY7453

McCulloch, G. (2019). Because Internet. Penguin Adult HC/TR & Riverhead Books.

McWhorter, J. H. (2017). Words on the move: Why English won’t- and can’t- sit still (like, literally). Picador, Henry Holt and Company.

Sánchez-Moya, A. & Cruz-Moya, O. (2015). Whatsapp, Textese, and Moral Panics: Discourse Features and Habits Across Two Generations. Procedia – Social and Behavioral Sciences, 173, pp. 300-306. https://doi.org/10.1016/j.sbspro.2015.02.069

 

 

 

These are the questions that prompted our research. An unprecedented level of media availability allows insight into how some speakers are utilizing code-switching (changing between different languages when speaking) in their daily lives today, almost in real-time. Some anecdotes that can give insight into how some Ukrainians are experiencing this change can be read in interviews in this article: Enemy tongue: eastern Ukrainians reject their Russian birth language | Ukraine | The Guardian. Another example is the subjects of our study, Ukrainian vloggers, who have made a noticeable shift from primarily speaking in Russian to primarily speaking in Ukrainian. Initially, before conducting this study, we anticipated that the subjects at first would most frequently code-switch from Russian to Ukrainian when they are telling jokes or just by inserting common words into their conversation.

The subjects of our study are three YouTube bloggers from a channel called “Lions on a Jeep” who spoke almost exclusively in Russian until after the full-fledged invasion of Ukraine started. They’re men in their late 20s – early 30s and were familiar with Ukrainian before, although they didn’t seem to actively use it on a daily basis. Starting March 3, 2022, they began to record live streams in their effort to collect donations for the Ukrainian military. Their first 2 streams were almost completely in Russian, but during the 3rd stream they started switching to Ukrainian at different rates. As of right now, they are still recording their streams and have transitioned to speaking Ukrainian for the most part. We collected over 70 speech samples from several live streams of theirs. The frequency, amount of videos in a short period of time, and the unedited and casual format of the conversation helped to consistently and closely analyze the transition.

Before gathering data, we divided the transition into 3 predicted stages: At the first stage they speak mostly Russian with some high frequency insertion of words/phrases from Ukrainian. At the second stage, they use more Ukrainian and there is continued high frequency insertion Ukrainian in addition to full switching between Russian and Ukrainian. Finally, at the third stage, they use mostly Ukrainian, occasionally borrowing words/phrases from Russian. We looked at the those stages individually for each speaker and then noted the code-switches that they had. We categorized each switch as a word, phrase, sentence, or clause, and counted the number of each type as they occurred. We then noted the context of each switch for further analysis so that we could more easily discover any code-switching patterns present later on.

When observing code switching, we used the categories of phrases, sentences, words, and clauses to organize cases. Phrases refer to switches from one language to the other halfway through a sentence, sentences refer to complete thoughts in one language, words to certain isolated switches, and clauses to small sentences embedded within larger ones. The main categories of contexts for code-switches in our data that we found were common Ukrainian word insertion, when showing national pride, humor, a slip, incorrectly using a Russian word believing it’s Ukrainian, and switching when not knowing the translation.

It’s clear to see these different kinds of contexts when looking at short examples such as in Figure 2. Here we can see that the speaker is inserting a Russian word into a Ukrainian sentence. Russian “уже” is a high-frequency word that closely resembles Ukrainian “вже”, so this is most likely a slip.

In the second example in Figure 3, we can see how wordplay is utilized. The word “сварка” means argument in Ukrainian and in Russian it means welding. One of the subjects said in Ukrainian that he had an argument (“сварка”) with his mom, and the speaker joked that they were making a metal structure with his mom, and thus there was “сварка”, meaning welding. Here we can see how the speaker used a word that exists in both languages but used it with Russian meaning for a comic effect.

In Figure 4, the speaker was clearly struggling to recall the right word, so he inserted the phrase in Russian into a Ukrainian sentence.

A clear example of the speakers assuming what they are saying is a correct word in Ukrainian can be seen in Figure 5.

The name of one of the speakers (Євген) is used in the nominative case, as it would be in Russian, whereas in Ukrainian, the vocative case (Євгене) should be used. “Bсе” is pronounced with a Ukrainian accent and is a hybrid of the Russian “всё” and the Ukrainian “усе”. The Russian word “понятно” is pronounced with a Ukrainian accent, and the speaker most likely assumes it to be a valid Ukrainian word. This seems to be a common pattern because we’ve seen several instances of it.

The speaker first uses masculine gender in Figure 6, because the Russian word for language “язык” is masculine, but then corrects himself and uses feminine gender, which is correct for the Ukrainian word “мова.” Also, you can see that he is inserting a clause in Ukrainian to prove that he has some proficiency in the language and show his Ukrainian identity.

Lastly, in Figure 7, the speaker is saying a common Ukrainian phrase that has been used extensively and is embedded by 2 sentences in Russian.

In cases of Ukrainian word insertion, speakers would add in phrases or words that are used regularly, such as greetings or slogans. Because of its fairly clear division amongst the stages in Table 1, we believe that the speakers first used phrases they were familiar and confident with as they began to transition as a way to clearly and immediately signal their solidarity and intent to distance themselves from Russian.

The speakers also used Ukrainian phrases and words to express national identity and pride. Similarly, to the case of common words and phrases, this behavior, as seen in Table 2, was utilized more in stage one than stages two and three to quickly and easily express their Ukrainian identity.

The use of this context eventually decreased, just like common words and phrases did, as the speakers grew more confident in Ukrainian and did not need to quickly express their pride, since speaking the language fluently accomplished the task. This use to express national identity was higher than we originally thought it would be, and it was somewhat surprising to see it happen so often.

Another pattern we observed was the use of code-switching in a humorous or comedic manner. This kind of code-switching is intentional and utilizes parts of both languages such as intonation and meaning to create a joke or a wordplay. However, the frequency of humor, shown in Table 2, was surprising, as we anticipated it to be far higher than it actually was in stage one. The use of humorous code-switching was present scarcely in stage one, not at all in stage two, and was most prominent in stage three.

Slips in our data involved a speaker starting a sentence in Ukrainian but accidentally reverting to Russian before they finished expressing their thought. In some cases, the speakers would realize they had slipped and correct themselves, but in others the speakers would continue, finishing the thought in Russian. Table 2 also shows that slips accounted for the majority of code-switches from stages two and three. This is likely due to the speakers using primarily Ukrainian for the second and third stages, so slips in the first stage are less common given that little Ukrainian is actually being used.

We were able to find recurring contexts related to speakers as well. As we previously mentioned, speakers would often code-switch at the start in order to index themselves as Ukrainians. The speakers did so relatively the same amount, but Speaker M did this slightly more than the other speakers, as shown in Table 3.

The use of humor however showed a greater disparity. Speaker V humorously code-switched to a far greater percentage than his counterparts. A better mastery and confidence of the language would likely allow the speakers to make more jokes and use differences between the two languages more effectively. We found that Speaker V seems to have the greatest ability of the three to speak Ukrainian. He demonstrated this by completely skipping stage two and barely needing any time to transition, so we believe that he was able to use the language more effectively to make jokes through his knowledge of both languages and their differences.

Since Speaker V displayed different code-switching patterns when compared with his counterparts and did less code-switching in general, he did not at any point use clause insertion when code-switching, as in Table 4, which showed more evidence as to his strength in the language. For Speaker A, we noticed that he code-switched more sentences than Speakers V and M, especially when switching from Ukrainian to Russian.

Looking further than these 3 subjects and this specific context, the data from our study may be a useful reference when looking at rapid language transition in other countries or perhaps what people tend to struggle with versus what they find easy when changing their primary language both in Ukraine and in other places. As this kind of research continues, we might be able to gain insight into how this rapid language transition could result in, or perhaps already has resulted in, new linguistic features such as an emerging accent or dialect and the creation of new words or slang from primarily Russian speakers becoming primarily Ukrainian speakers. If you are looking for additional information about the languages’ history and how they are being used in the ongoing war today, the following blog post, Ukrainian vs Russian: How Do These Languages Differ, is very useful.

 

References

Azhniuk, B. (2017). Ukrainian Language Legislation and the National Crisis. Harvard Ukrainian Studies, 35(1/4), pp. 311–329. http://www.jstor.org/stable/44983546

Gardner-Chloros, P. (2009). Code-switching. Cambridge, England: Cambridge University Press.

Krishnan, S., Noor, N., and Rasmani, K. (2011). Analysis on Stages of Code-switching by Bilingual Educators: A Case Study. International Conference on Applied Sciences, Mathematics and Humanities 2011, pp.  475-481. https://www.researchgate.net/publication/338357063_ANALYSIS_ON_STAGES_OF_CODE-SWITCHING_BY_BILINGUAL_EDUCATORS_A_CASE_STUDY

Mahootian, S. (2020). Bilingualism (Routledge Guides to Linguistics). London and New York: Routledge Taylor & Francis Group.

Myers-Scotton, C. (1993). Common and Uncommon Ground: Social and Structural Factors in Codeswitching. Language in Society, 22(4), pp. 475–503. http://www.jstor.org/stable/4168471

Rating Group. (2022, March 19). The Sixth National Poll: the Language Issue in Ukraine. Retrieved May 13, 2022, from https://ratinggroup.ua/en/research/ukraine/language_issue_in_ukraine_march_19th_2022.html

San, H. K. (2009). Chinese-English Code-switching in Blogs by Macao Young People (Publication No. 9877103) [Master’s thesis, The University of Edinburgh]. Edinburgh Research Archive.

State Statistics Committee of Ukraine. (2003-2004). All-Ukrainian population census 2001. Retrieved May 13, 2022, from http://2001.ukrcensus.gov.ua/eng/

Introduction and Background

The United States is becoming an increasingly multiracial, multilingual nation. While still constituting a relatively small portion of the population, people of mixed race make up the fastest growing demographic in America – in the past decade alone, the multiracial population within the United States has increased by 276 percent, from 9 million people in 2010 to 33.8 million people in 2020. Furthermore, since 1980, the number of people who speak a language other than English at home has more than doubled (US Census Bureau, 2020). In light of these changing demographics, research surrounding biracial identity and attitudes towards bilingualism is becoming particularly paramount.

In crossing over cultural boundaries and racial lines, biracial individuals exist at the crossroads of disparate backgrounds that at times may be at odds with one another. Existing within this liminal space “in between,” so to speak, can contribute to the formation of a “marginal” identity, feelings of conflict when negotiating identity (Poston, 1990), or distance from their cultural heritage (Bracey, Bámaca, & Umaña-Taylor, 2004). 

However, it is understood that when an individual perceives facets of their identity to be compatible, the individual’s sense of self becomes more unified, a process known as identity integration (Syed & McLean, 2016). Models of identity integration have been applied to examine the process of biracial identity negotiation in various domains. One framework of particular interest comes from Cheng and Lee (2009), who present four methods of identity indexation among those of biracial descent. These classifications represent how the individual navigates their cultural identity in society, and also serve as an indicator for the degree of conflict or turbulence that the individual has over their own identity. The classifications are as follows:

• Intersections: Identification with individuals of related groups
• Dominance: Identification with individuals of one primary group
• Compartmentalization: Identification with a group is situationally dependent
• Merger: Simultaneous, cross-group identifications

The present study applies Cheng and Lee’s framework to investigate the relationship between biracial individuals and their association or dissociation with their cultural identity. More specifically, we look at the role of heritage language maintenance in informing the stances and alignments of biracial individuals. Following the conclusions of Lee (2002), which suggests strong correlations between an individual’s heritage language proficiency and their cultural identity, there exists the question of whether dual language use within the home generates a hyper-salient cultural identity — or an aversion towards particular cultural indexations.

Using monoracial students as a point of reference, we hypothesized that biracial students may exhibit more conflicted, turbulent attitudes or be more ambivalent towards bilingualism due to parents of differing cultural backgrounds, which would be reflected in how they culturally identify themselves. We also hypothesized that monoracial students may be more inclined to learn the heritage language, as both parents are likely to show a unified attitude towards bilingualism and thus exhibit less cultural conflict.

Methods

We utilized survey methods and metalinguistic interviews to collect data. In total, we surveyed 32 college students and interviewed 9 college students. Out of those that we surveyed, 27 participants were of monoracial descent and 5 participants were biracial descent. 5 interviewees were of monoracial descent and 4 interviewees were of biracial descent. While participants came from a variety of cultural and linguistic backgrounds, the majority came from Asian backgrounds (n=26). All biracial participants were half white.

Our survey contained two sections. In the first section, we asked participants questions about their language demographic background information (e.g., What is your primary language? If you speak another language at home please list them.) We also asked whether they belong to a cultural community and/or they grew up in one. In the second section, participants ranked their agreements on a scale of 1-5 with a series of statements. Statements concerned both parents’ attitudes towards bilingualism (e.g., My parent thinks it’s important I learn another language.) as well as their personal attitudes (e.g., If I ever have kids, I would want them to know a second language.)

After surveying participants, we conducted interviews to further investigate their experiences and possible differences in attitudes towards bilingualism between parental units, especially if the student is of biracial descent. During the interviews, we focused more on how biracial students indexed themselves and looked at possible connections to their linguistic backgrounds (e.g., “What were your caregivers’ attitudes towards your heritage language(s)? Were they supportive, against learning it? Did their attitudes change as you got older?”)

Results

Unsurprisingly, both biracial and monoracial students had positive perceptions of bilingualism, and thought their parents had positive perceptions of bilingualism as well. However, these groups differed in how strong these positive perceptions were. Since the survey asked participants to rank how strongly they agreed with a series of positive and negative statements about bilingualism from a scale of 1 (strongly disagree) to 5 (strongly agree), we were able to observe the distribution of their responses. Figure 1 below shows the distribution of responses of monoracial students and Figure 2 shows the distribution of responses for biracial students regarding how much the participants agreed that their parents have positive attitudes towards bilingualism.

 

 

Although both monoracial and biracial students thought their parents had generally positive views towards bilingualism, the monoracial students agreed more strongly than the biracial students. The monoracial students picked “strongly” agree over 50% of the time, whereas the biracial students only picked that 30% of the time. Monoracial students also agreed (ranking either 4 or 5) with the positive statements over 70% of the time whereas the biracial students only ranked the statements 4 or 5 50% of the time. Although this is merely a correlation, it is an interesting observation to note that could lead to more studies in the future.

For the interviews, there was variation across both monoracial and biracial students in how strongly their parents advocated for their learning in the heritage language. This is unsurprising given how each household is different and the variety of factors that shape parents’ decisions to teach the heritage language or not. Time may be an important factor, and the parents’ own fluency in the language may hinder or encourage this passing on of language to their children.

However, we did notice specifically that for biracial students who later chose to learn the heritage language on their own, they emphasized a want to connect to their heritage, especially since it gives a sort of “validity” to their cultural identities. Elaine, a half-Peruvian half-White student stated, “Once I started learning Spanish I had… more validity to my identity as a Peruvian because it’s like even though I didn’t look like it, well…I can speak in this language.” Biracial students appeared more questioning of their identities compared to monoracial students since they were not necessarily as exposed to their heritage culture and may feel more “outside” the culture due to their mixed appearance. They appeared to be more questioning of their own identities especially if they couldn’t speak the heritage language well, as language is often seen as a pillar of cultural identity.

On the other hand, the monoracial students we interviewed appeared to comfortably identify with the X-American label, for example Asian-American or Mexican-American. When asked about cultural identity, one student whose parents are first-generation Korean immigrants stated that she identifies as “just Korean-American” and “never really questioned it because [she] grew up in [a predominantly Asian area with a lot of other Koreans”. Presumably, she grew up in a household that was unified in culture and language, and people would not question her “Koreanness” based on her appearance. It is interesting to note that so-called “hyphenated” Americans have earned a spot in the mainstream social discourse of American society, yet biracial students have not necessarily done so due to the diversity in their parents’ heritages. A biracial identity is not easily constructed across all groups because there is such a mix of cultures.

Discussion

Overall, there were not drastic differences between the attitudes of the parents of monoracial individuals versus biracial individuals. There was a large degree of uniformity in the belief that being multilingual is a beneficial skill to have, albeit varying degrees of implementation. There were significant differences in the participants themselves, however. Among our monoracial survey population, we see that the majority of them informally acquired their heritage language and that the heritage language is the dominant language of the home. Among our biracial survey population, English is the predominant language at home, with only half of our participants having acquired their heritage language. With the exception of a single participant, the heritage language was formally acquired.

The most interesting difference between these two groups was that those of the biracial population exhibited a demonstrated awareness of their language indexation that monoracial individuals did not. One participant, Yukari, shares of how her Japanese mother passed down the Japanese language to her:

“When I was living in Japan, I honestly felt I was pretty privileged since the people around me were also half Japanese, but a lot of them didn’t know how to speak Japanese and so I had the sense of pride that ‘Oh, I can speak Japanese’ and I thought it was a good thing because I consider Japan my home, so being able to communicate with not only my family, but the community was a really important thing to me… If I wasn’t able to speak Japanese, I feel like I would’ve connected more to my American side of the family. I would’ve considered myself more as white instead of Japanese.”

Yukari’s experience, building off of the information presented by Elaine previously, allows us to draw parallels between these two participant’s experiences. Each biracial individual indicated a high level of indexation through their heritage language. Both Elaine and Yukari used their heritage language to make a claim to their non-white identity. Not only was this consciously done, but each of them used their heritage language to navigate social circumstances and interactions. Considering the point made by Cheng and Lee (2009) (see quote below), it is evident that in the increasingly multicultural, multilingual United States, more and more biracial individuals are operationalizing their heritage language to make claim to a multifaceted and multicultural identity.

“People change their identification strategies depending on individual constraints such as attention and cognitive resources, and contextual factors such as situational cues that make a particular social identity more or less salient.” (Cheng & Lee, 2009).

One limitation to our study was that the survey responses we collected were not evenly distributed between monoracial (n=27) and biracial students (n=5). Furthermore, we tried to keep our survey as simple and concise as possible, so we were limited in the number of questions we could ask. There’s only so much a survey can cover in terms of nuances in attitudes towards bilingualism. Lastly, even with our interviews, the participants tended to only talk about topics adjacent to our questions, so this was only the tip of the iceberg as well. We hope that despite these limitations, our study serves as a foundation to more discourse and research about biracial students, language use, and cultural identity in the future.

In conclusion, there was little to no significant variation between parents of monoracial and biracial individuals in perceptions of bilingualism. The greatest factor for heritage language acquisition was its presence, or lack thereof, in the home. Our research did provide evidence for cognizant identity indexation through heritage language acquisition on the part of the biracial individuals. This was in direct contrast to the motivations for heritage language use in monoracial individuals. Moving forwards, it would be beneficial to investigate ways that language is encouraged through the maternal line, as our data gave some implications for this. Our sample size, however, does not provide enough variation or control to determine the validity of this statement.

 

Additional Resources 

This Ted Talk is given by two high school sophomores who talk about the experience of being biracial as well as some common misconceptions about biracial individuals. It’s a personal account of being biracial that also emphasizes the ways language can exclude people or deny their identities.

Check out this related Languaged Life blog post from a previous class to find out more about social factors that inform language maintenance within multilingual families!

 

References

Bracey, J.R., Bámaca, M.Y. & Umaña-Taylor, A.J (2004). Examining ethnic identity and self-Esteem among biracial and monoracial adolescents. Journal of Youth and Adolescence 33, 123–132. https://doi.org/10.1023/B:JOYO.0000013424.93635.68

Cheng, C., & Lee, F. (2009). Multiracial identity integration: Perceptions of conflict and distance among multiracial individuals. Journal of Social Issues, 65(1), 51-68. DOI: 10.1111/j.1540-4560.2008.01587.x

Foster-Frau, S., Mellnik, T., Blanco, A. (2021, October 8). ‘We’re talking about a big, powerful phenomenon’: Multiracial Americans drive change. The Washington Post. https://www.washingtonpost.com/nation/2021/10/08/mixed-race-americans-increase-census/

Lee, J. (2002). The Korean language in America: The role of cultural identity in heritage language learning, language, culture and curriculum, 15(2), 117-133, DOI: 10.1080/07908310208666638

Poston, W. S. (1990). The biracial identity development model: A needed addition. Journal of Counseling & Development, 69(2), 152–155. https://doi.org/10.1002/j.1556-6676.1990.tb01477.x

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