language and culture research article

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Speaking, writing and reading are integral to everyday life, where language is the primary tool for expression and communication. Studying how people use language – what words and phrases they unconsciously choose and combine – can help us better understand ourselves and why we behave the way we do.

Linguistics scholars seek to determine what is unique and universal about the language we use, how it is acquired and the ways it changes over time. They consider language as a cultural, social and psychological phenomenon.

“Understanding why and how languages differ tells about the range of what is human,” said Dan Jurafsky , the Jackson Eli Reynolds Professor in Humanities and chair of the Department of Linguistics in the School of Humanities and Sciences at Stanford . “Discovering what’s universal about languages can help us understand the core of our humanity.”

The stories below represent some of the ways linguists have investigated many aspects of language, including its semantics and syntax, phonetics and phonology, and its social, psychological and computational aspects.

Understanding stereotypes

Stanford linguists and psychologists study how language is interpreted by people. Even the slightest differences in language use can correspond with biased beliefs of the speakers, according to research.

One study showed that a relatively harmless sentence, such as “girls are as good as boys at math,” can subtly perpetuate sexist stereotypes. Because of the statement’s grammatical structure, it implies that being good at math is more common or natural for boys than girls, the researchers said.

Language can play a big role in how we and others perceive the world, and linguists work to discover what words and phrases can influence us, unknowingly.

How well-meaning statements can spread stereotypes unintentionally

New Stanford research shows that sentences that frame one gender as the standard for the other can unintentionally perpetuate biases.

Algorithms reveal changes in stereotypes

New Stanford research shows that, over the past century, linguistic changes in gender and ethnic stereotypes correlated with major social movements and demographic changes in the U.S. Census data.

Exploring what an interruption is in conversation

Stanford doctoral candidate Katherine Hilton found that people perceive interruptions in conversation differently, and those perceptions differ depending on the listener’s own conversational style as well as gender.

Cops speak less respectfully to black community members

Professors Jennifer Eberhardt and Dan Jurafsky, along with other Stanford researchers, detected racial disparities in police officers’ speech after analyzing more than 100 hours of body camera footage from Oakland Police.

How other languages inform our own

People speak roughly 7,000 languages worldwide. Although there is a lot in common among languages, each one is unique, both in its structure and in the way it reflects the culture of the people who speak it.

Jurafsky said it’s important to study languages other than our own and how they develop over time because it can help scholars understand what lies at the foundation of humans’ unique way of communicating with one another.

“All this research can help us discover what it means to be human,” Jurafsky said.

Stanford PhD student documents indigenous language of Papua New Guinea

Fifth-year PhD student Kate Lindsey recently returned to the United States after a year of documenting an obscure language indigenous to the South Pacific nation.

Students explore Esperanto across Europe

In a research project spanning eight countries, two Stanford students search for Esperanto, a constructed language, against the backdrop of European populism.

Chris Manning: How computers are learning to understand language​

A computer scientist discusses the evolution of computational linguistics and where it’s headed next.

Stanford research explores novel perspectives on the evolution of Spanish

Using digital tools and literature to explore the evolution of the Spanish language, Stanford researcher Cuauhtémoc García-García reveals a new historical perspective on linguistic changes in Latin America and Spain.

Language as a lens into behavior

Linguists analyze how certain speech patterns correspond to particular behaviors, including how language can impact people’s buying decisions or influence their social media use.

For example, in one research paper, a group of Stanford researchers examined the differences in how Republicans and Democrats express themselves online to better understand how a polarization of beliefs can occur on social media.

“We live in a very polarized time,” Jurafsky said. “Understanding what different groups of people say and why is the first step in determining how we can help bring people together.”

Analyzing the tweets of Republicans and Democrats

New research by Dora Demszky and colleagues examined how Republicans and Democrats express themselves online in an attempt to understand how polarization of beliefs occurs on social media.

Examining bilingual behavior of children at Texas preschool

A Stanford senior studied a group of bilingual children at a Spanish immersion preschool in Texas to understand how they distinguished between their two languages.

Predicting sales of online products from advertising language

Stanford linguist Dan Jurafsky and colleagues have found that products in Japan sell better if their advertising includes polite language and words that invoke cultural traditions or authority.

Language can help the elderly cope with the challenges of aging, says Stanford professor

By examining conversations of elderly Japanese women, linguist Yoshiko Matsumoto uncovers language techniques that help people move past traumatic events and regain a sense of normalcy.

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Language as a Facilitator of Cultural Connection

Understanding culture as a means of preventing or treating health concerns is growing in popularity among social behavioral health scientists. Language is one component of culture and therefore may be a means to improve health among Indigenous populations. This study explores language as a unique aspect of culture through its relationship to other demographic and cultural variables. Participants ( n = 218) were adults who self-identified as American Indian, had a type 2 diabetes diagnosis, and were drawn from two Ojibwe communities using health clinic records. We used chi-squared tests to compare language proficiency by demographic groups and ANOVA tests to examine relationships between language and culture. A higher proportion of those living on reservation lands could use the Ojibwe language, and fluent speakers were most notably sixty-five years of age and older. Regarding culture, those with greater participation and value belief in cultural activities reported greater language proficiency.

Ojibwe people call themselves “Anishinaabe,” which has been given various meanings by historians and linguists. Contextually, “Anishinaabe” can mean American Indian or, more specifically, Ojibwe. Most importantly, the term “Anishinaabe” unites people and, for our purposes, unites Indigenous people in the struggle and persistence to revitalize Indigenous languages and Indigenous culture for the health of all human beings.

Indigenous people make up roughly 5 percent of the world’s population. They speak thousands of different languages in over seventy different countries ( United Nations Secretariat 2009 ). Traditional activities within and across Indigenous nations vary significantly. It could be argued that many of these activities, although different, are embedded in similar cultural value systems. Health-based researchers have studied and are studying the connection between culture and improved health ( Rowan et al. 2014 ), yet we have not fully explored how language fits into the broader umbrella of cultural values and activities—an important undertaking that can direct efforts to promote cultural and language revitalization efforts. This paper explores the connection between Indigenous language proficiency, participation in traditional and spiritual activities, and cultural values within two Anishinaabeg communities representing a shared cultural group in the United States.

Based on the 2010 U.S. census, there are over 5.2 million people who self-identify as American Indian/Alaska Native (AI/AN) ( U.S. Census Bureau 2012 ). Of these people, 170,742 self-identify as Ojibwe, which is the fifth largest AI tribal grouping in the United States. Ojibwe people reside in urban, rural, and reservations settings across the United States and Canada. In the United States, Ojibwe communities make up over a dozen smaller reservations owing to various treaty negotiations in the nineteenth and early twentieth centuries that depleted land-bases and defined reservation boundaries ( Treuer 2010 ). While Ojibwe reservations are small in comparison to other tribal territories, Ojibwe reservations span a large geographical region that includes North Dakota, Minnesota, Wisconsin, Michigan, and southern Canada.

Although the Ojibwe language is considered severely endangered, as are many Indigenous languages ( Moseley 2010 ), it is also considered capable of revitalization based on the number of first- and second-language speakers ( Norris and MacCon 2003 ). With more than eight thousand speakers, over half (61%) of whom live outside of AI/AN reservations, Ojibwe ranks ninth in the number of Indigenous speakers in the United States ( Siebens and Julian 2011 ). While the census gives details on speakers by age and percentage of Indigenous language spoken in the home, information on Ojibwe speakers is limited because statistics are combined for all Indigenous languages in the United States, obscuring different historical and contemporary circumstances.

Indigenous Language Revitalization

Indigenous people across the globe are revitalizing their native languages. The Maori of New Zealand and Native Hawaiians have paved the way for language revitalization efforts, modeling abilities to improve endangered language when most first-language speakers have passed on. Communities in the Southwest United States have maintained a great deal of their first-language speakers but continue to support efforts to preserve language proficiency among the younger generations. Language revitalization efforts are receiving growing attention within Ojibwe communities, as well, as language immersion primary education programs, adult language nests, and local public policy declaring Ojibwe as the official language of tribes emerge ( Gunderson 2010 ; Hermes, Bang, and Marin 2012 ; Fahrlander 2015 ). Community members and linguists alike share in the urgency and importance of revitalizing languages and preserving local dialects, especially because time with elders—overwhelmingly the first-language speakers—is uncertain.

Language is important to community operation and therefore to community well-being. Language transmits ideas, beliefs, and knowledge, thereby enhancing social support, interpersonal relationships, and shared identity ( Chandler and Lalonde 1998 ). Speaking and understanding one’s Indigenous language has more significance than communication alone. Indigenous languages preserve important concepts and epistemologies that shape entire belief systems, and they define how people formulate ideas and make decisions ( Royal Commission on Aboriginal Peoples 1996 ; Crawford 1995 ; Norris 2004 ). Some scholars stress that less variety in languages equates to less variety in ideas, stifling personal and political progress ( Crawford 1995 ).

Songs, prayers, and ceremonial activities are often delivered strictly in the Indigenous language. Therefore, language preservation is critical to communication between generations, communication with the spirit world, and the transmission of teachings (concepts, symbolism, oral stories) within cultural, spiritual, and religious practices. Language use within these practices affects the identity, culture, and health of Indigenous populations ( King, Smith, and Gracey 2009 ). Without language, the intergenerational transmission of values and belief systems would be obstructed ( Indigenous Language Institute 2002 ), affecting the health of our future generations.

Researchers have looked increasingly to culture to improve health behaviors, compiling more evidence that culture may prevent and treat health outcomes such as depression and substance abuse ( Walters, Simoni, and Evans-Campbell 2002 ; Stone et al. 2006 ; Rieckmann, Wadsworth, and Deyhle 2004 ). How we use and define culture in studies varies—from cultural activities to cultural values to cultural symbols. Language is sometimes but not always used, and rarely is it considered as a separate construct.

Despite community emphasis on language revitalization, there is limited research highlighting Indigenous languages as a separate and distinct concept from culture. Within the available literature, discrepancies exist that fail to explain the full effect of language on health. The 2008 National Aboriginal and Torres Strait Islander Social Survey reported that Aboriginal youth aged fifteen to twenty-four years who spoke an Indigenous language were less likely to consume alcohol at risky levels or to have used illicit substances in the previous twelve months ( Australian Bureau of Statistics 2012 ). Hodge and Nandy (2011) reported that significantly greater percentages of individuals with the ability to speak their tribal language were in the “good wellness” group versus the “poor wellness” group, with “wellness” defined as feeling good and taking care of oneself physically, emotionally, mentally, and spiritually (17% vs. 29%). Two reports found positive relationships between language and health in Indigenous communities in Canada by measuring community-wide language preservation and community-wide measures of health behaviors. Hallett, Chandler, and Lalonde (2007) found that tribal groups with lower levels of language knowledge had six times more youth suicides than those with higher language knowledge. The study also measured other factors related to what Chandler and Lalonde (1998) consider cultural continuity factors, which determine whether a group of people maintains control over their communities. For the tribal groups that had all other cultural continuity factors, language still decreased youth suicide by almost 50 percent. Similarly, Oster and colleagues (2014) found that higher Indigenous language knowledge rates predicted lower prevalence rates of type 2 diabetes, even after adjusting for socioeconomic factors.

Whereas these statistics are promising, other studies have found negative relationships between Indigenous languages and health. A cross-sectional survey of Indigenous people of Australia found that speaking and understanding an Indigenous language and having an Indigenous language as the main language spoken in the home was associated with increased sadness ( Biddle and Swee 2012 ). Similarly, in Canada, Indigenous language was negatively associated with community well-being. Community well-being was defined through community level education, labor force, income, and housing conditions ( Capone, Spence, and White 2013 ). Indigenous-only language use in the home has also been associated with decreased access to health care ( Bird et al. 2008 ; Hahm et. al. 2008 ; Schumacher et al. 2008 ).

If taken literally, these results might discourage revitalization attempts. However, there are numerous contextual factors to consider when interpreting results. Communities with high language preservation often are also isolated geographically, which is how they maintain Indigenous language use because they are less affected by assimilation. Geographical isolation is associated with poverty, poor housing, less educational opportunity, and less economic opportunity. These factors could also lead to sadness and diminished community well-being as defined by one study ( Capone, Spence, and White 2013 ). Changing the way we define well-being impacts the interpretation of results. Having community members define well- being prior to using well-being as an outcome would be more meaningful. Geographic isolation combined with immersion in Indigenous languages may also hinder an individual’s ability to speak the dominant language, an inability that has been shown to decrease access to health care and increase racial discrimination in other minority populations ( Gee and Ponce 2010 ). Decreased access to health care and increased racial discrimination, especially in health-care settings, would impact health and well-being as it pertains to receiving routine check ups and specialty services. Individuals that use and learn their Indigenous language may also immerse themselves in traditional culture and find less meaning in Western education and Western economy ( Capone, Spence, and White 2013 ). Straying from these societal norms would affect education, employment, and income—all factors measured by the community well-being score.

Few researchers focus on Indigenous language as a separate concept from culture with unique qualities that may not only affect health outcomes but may also enhance the effects of other cultural variables (identity, traditional activities, beliefs, etc.) on health. Several researchers have found a positive relationship between cultural factors and improved mental health. These cultural factors had some similarities but often vary in definition. Participation in cultural activities included traditional food customs, traditional forms of socialization, and traditional forms of art ( Whitbeck et al. 2002 ; LaFromboise et al. 2006 ; Kading et al. 2015 ). Cultural identity varied considerably. While some followed Oetting and Beauvais’s (1990–1991) American Indian Cultural Identification Scale, which left the definition of identity open to the respondent ( Whitbeck et al. 2002 ; LaFromboise et al. 2006 ), others modified or created their own scale based on community- specific definitions ( Moran et al. 1999 ; Rieckmann, Wadsworth, and Deyhle 2004 ). Asking respondents whether they follow a specified way of life was also used to define enculturation or acculturation ( Wolsko et al. 2007 ). Others ( Moran et al. 1999 ; LaFromboise et al. 2006 ; Whitesell et al. 2014 ) incorporated language in their culture-based scales of cultural engagement, ethnic identity, and enculturation. Therefore, it is difficult from these studies to predict the relationship between language and health outcomes.

Often, researchers assume language is built into cultural frameworks of health, minimizing the focus on the direct benefits of language use on health outcomes. Language is considered simultaneously with other measures of culture, as demonstrated in the lack of language-specific health research. Certainly, culture and language interact in ways that make it hard to differentiate the unique health benefits. Participants of one qualitative study describe Indigenous language as a critical and inseparable aspect of culture without which Indigenous people would be incapable of surviving because it is the foundation by which people collectively live and practice culture ( Oster et al. 2014 ).

Given contradictions in the literature, this study intends to more clearly delineate the relationship between language, demographic variables, and other cultural variables in a study of Ojibwe adults. For both community members and researchers, this study advances our theoretical understanding of these constructs to better utilize community assets to improve the health and well-being of the people.

The data for this paper are from the larger community-based participatory research study Mino Giizhigad (Ojibwe for “A Good Day”) that examined how mental health factors relate to diabetes treatment and outcomes for American Indian adults with type 2 diabetes ( Walls et al. 2014 ). The Mino Giizhigad study included participants from two Ojibwe communities— the Lac Courte Oreilles and Bois Forte Bands of Chippewa. 1 The Mino Giizhigad study was approved by the Indian Health Service and the University of Minnesota Institutional Review Boards; tribal resolutions were also obtained prior to funding submission. Both tribes actively partnered with researchers from the University of Minnesota Medical School for this project, with regular meetings of the respective tribal Community Research Councils.

Study Participants

Potential participants were identified from health clinic records from each tribal clinic. Eligibility criteria included (a) being 18 years of age or older, (b) self-identifying as American Indian, and (c) having a type 2 diabetes diagnosis. Probability sampling was used to randomly select patients from each reservation clinic who met these inclusion criteria. Of the 289 identified and eligible individuals, 75 percent ( n = 218) consented to participate in the study and completed the self-report and interview-administered measures described below. Participants were given $30 and a pound of local wild rice for their time and effort. Further procedural details are provided in Walls and colleagues (2014) .

Demographics

We asked participants to provide their age as a continuous variable, gender (male = 0, female = 1), and educational attainment (“less than high school,” “high school or GED,” “some college, vocational or technical training,” “college graduate,” or “advanced degree”). We collapsed educational attainment into two groups (high school or less, and some college or more). Annual household income was reported in $10,000 ranges, and the midpoint of this range divided by the number of people living in the household was used to calculate the per capita income. Additionally, the federal poverty calculation was used to categorize participants as above or below the federal poverty level. We also asked if participants currently live on reservation land, or if they had lived on reservation land prior to age eighteen.

We categorized Ojibwe language understanding and speaking proficiency based upon self-report from four questions. Understanding Ojibwe was determined by asking participants if they could understand any spoken Ojibwe, and if so, whether they could easily understand spoken Ojibwe. We categorized participants’ understanding based on responses, provided by the survey, as “None” (0), “Any” (1), and “Easily” (2). Speaking Ojibwe language was assessed by asking participants if they could speak some Ojibwe language, and for those that could, if they could speak fluently. We categorized individuals’ speaking proficiency as “None” (0), “Some” (1), and “Fluent (2).

We queried several elements of Ojibwe cultural participation and values. Participation in traditional activities was measured with a seventeen-item traditional activities index ( Whitbeck et al. 2004 ). Participants were asked if they had participated in each activity within the past twelve months, with either a “Yes” (1) or “No” (0) response, resulting in a sum total with a range from zero to seventeen. Example scale items included “done any beading,” “gone ricing,” and “listened to elders tell stories.” The traditional activities index had a Cronbach’s alpha of 0.811. Participation in traditional spiritual activities was measured with a nine-item spiritual activity index ( Whitbeck et al. 2004 ) with similar prompt and response categories. The resultant scale had scores ranging from zero to nine, and included items such as “offered tobacco,” “gone to ceremonial feasts,” and “sought advice from a spiritual advisor.” The spiritual activities index had a Cronbach’s alpha of 0.791.

We asked how much the participant’s family does special things together that are based on Ojibwe culture, how much his or her family lives by or follows Ojibwe ways, and how much he or she lives by or follows Ojibwe ways. Response options for these questions were “A lot,” “Some,” “Not much,” and “None.” We collapsed “A lot” and “Some” into one category, and “Not much” and “None” into another category. We also asked how important traditional spiritual values are to the way participants lead their lives, with response categories of “Very important,” “Somewhat important,” “Not too important,” and “Not at all important.” We collapsed responses into “Very important” and all others.

We used SPSS (Version 20) for data analysis. Chi-square tests were used to examine differences between categories of language proficiency and several demographic characteristics. We used chi-square tests to compare language proficiency by nominal groups, and ANOVA tests, with Bonferroni correction to adjust for multiple comparisons, to examine relationships between language and traditional and spiritual activities.

Descriptive analyses revealed the mean age of participants in this study was 56.5 years (31.7% were aged 65 years or older), and the mean annual per capita income was $10,331, 44.4 percent falling below the federal poverty limit. Over half of the sample was female (56.4%) and had completed some college or higher (60.4%). Most had lived on reservation lands prior to age eighteen (80.7%), and 77.5 percent now lived on reservation lands.

Regarding understanding spoken Ojibwe, 76 (34.9%) of the participants in this study could easily understand, 93 (42.7%) could understand some, and 49 (22.5%) could not understand any. Concerning speaking Ojibwe, 14 (6.4%) reported being able to speak fluently, 138 (63.3%) could speak some, and 66 (30.3%) could not speak any.

Tables 1 and ​ and2 2 show the percent of participants understanding and speaking Ojibwe by demographic group. The proportion of respondents that understand any or easily understand spoken Ojibwe was significantly higher among people currently living on reservation lands ( p = 0.019) and those who lived on reservation land before age eighteen ( p = 0.005). The proportion speaking Ojibwe fluently was higher among individuals sixty-five years or older ( p = 0.003) compared to those younger than sixty-five, and significantly more of those speaking some or fluent Ojibwe currently lived on reservation lands ( p < 0.001).

Percent understanding proficiency by demographic categories

Percent speaking proficiency by demographic categories

ANOVA tests showed differences in mean number of traditional activities ( p = 0.001; p = 0.006) and spiritual activities ( p < 0.001; p < 0.001) across Ojibwe understanding and speaking categories, respectively. After applying the Bonferroni correction to p values, we saw significant differences between low and high Ojibwe proficiency, as shown in figures 1 and ​ and2. 2 . Overall, higher proficiency in both understanding and speaking was related to higher reports of traditional and spiritual activities.

ANOVA test with Bonferroni correction; * Significantly different than “No” and “Any” understanding groups; ** Significantly different than “No” speaking group

ANOVA test with Bonferroni correction; *Significantly different than “No” understanding group; **Significantly different than “No” and “Some” understanding groups; *** Significantly different than “No” speaking group

Of all participants in this study, 64.2 percent reported doing some or a lot of special things with their family based on Ojibwe culture. The majority of participants (66.4%) reported that their family lives by or follows Ojibwe ways some or a lot, and 70.8 percent felt that they lived by or followed Ojibwe ways some or a lot. Nearly half (46%) reported that traditional spiritual values are very important to the way they lead their lives. Comparisons of these variables by Ojibwe language proficiency groups are illustrated in figures 3 and ​ and4. 4 . Significant differences were found between proficiency, both understanding and speaking, for all of these culturally salient variables. The clear trend here is that those understanding easily and speaking proficiently have the highest percent affirming these four culturally salient items.

Percent within understanding proficiency category

Percent within speaking proficiency category

In this study, we examined Ojibwe language proficiency and its relationship to cultural variables in a sample of 218 Ojibwe adults with type 2 diabetes living in the northern Midwest United States. Thirty-five percent could easily understand the language, and six percent were fluent. Greater language proficiency was associated with living on the reservation (now as well as before age eighteen) and being older than sixty-five years of age. Language proficiency was associated with more participation in traditional and spiritual activities, as well as endorsing and living by traditional spiritual values. These findings highlight and further delineate the strong connection between Indigenous language and cultural values and participation, and they provide the basis for future investigations considering the relationship between language, cultural involvement, and health.

Results indicated individuals currently living on the reservation spoke and understood the language more than those who lived outside the reservation. This distinction is particularly of note given that individuals in this study were recruited based on their use of a tribal health clinic. In other words, even those that did not live on reservation lands lived close enough to access tribal health services on tribal lands. Living on the reservation connects community members with cultural opportunities not afforded to many off-reservation residents. The distance from reservation cultural and community assets (i.e., attendance at nontribal schools) may decrease the likelihood of language involvement enough to lead to a negative correlation between living off the reservation and language proficiency. Cultural activities, as we have also found in this study, were related to proficiency in the language.

We found that understanding the language was associated with living on the reservation before the age of eighteen; however, speaking the language was not associated. This result matches with how people develop language. People tend to understand a language before they are able to produce it, much like an infant. In that respect, if one grew up in the language, which might be linked to living on the reservation before the age of eighteen, and then moved away, it is likely that one would understand some but produce less.

Being a fluent speaker was associated with being aged sixty-five years or more. This fits with UNESCO’s Language Vitality and Endangerment framework, in which the most significant factor is intergenerational language transmission. Languages are termed more endangered as the younger generations stop using the language. It is most common in Indigenous communities that the first-language speakers and fluent speakers are elders. In a report from the 2006–2010 American Community Survey and Puerto Rico Community Survey, older people reported speaking their Indigenous language in the home at a much higher rate than the young people (11% of 15- to 17-year-olds vs. 22.3% of 65+ year-olds) ( Siebens and Julian 2011 ).

We measured culture by asking about participation in the last year in specific traditional activities such as spearfishing, making blankets, and listening to elder stories, but we also asked more general questions that allowed the participants to self-identify what Ojibwe culture meant to them. We asked about following life standards and living by traditional life ways. In both specific and broad ways of wording the questions, we found that culture was associated with proficiency in the language. This finding strengthens anecdotal literature that maintains that culture cannot exist without language and vice versa ( McIvor, Napoleon, and Dickey 2009 ).

Similar to the findings with traditional activities, participating in spiritual activities and considering spiritual values important were both associated with greater language proficiency. Language is a critical aspect of traditional spiritual activities. While many spiritual advisors and ceremonial leaders provide interpretation for those they are helping, much of the spiritual meaning is lost because concepts do not always translate into the dominant culture’s language. Because of this, greater language knowledge may facilitate participation in traditional spiritual activities. On the other hand, participation in spiritual activities conducted in the language may lead to greater language acquisition, or an increased interest in learning the language.

Both spiritual and cultural activities have important implications for health and healing, which makes understanding factors associated with participation in these activities especially valuable. For example, participation in traditional spiritual activities has been found to be associated with a lower likelihood of past-year alcohol abuse ( Whitbeck et al. 2004 ), and low enculturation has been found to be a strong predictor of alcohol problems ( Currie et al. 2011 ). Culture has been shown to be connected to positive mental health ( Kading et al. 2015 ), positive psychological well-being ( Moran et al. 1999 ), resiliency factors among adolescents such as positive attitude toward schools and reaching academic goals ( LaFromboise et al. 2006 ), greater happiness, and the use of religion or spirituality (versus substances) to cope with stress ( Wolsko et al. 2007 ). Health benefits of culture and spirituality have always been understood by tribal communities and often requested within treatment programs ( Legha and Novins 2012 ). Recently, scientific studies have also recognized this important relationship.

Limitations

The generalizability of these findings is limited to adults living with diabetes sampled from clinic records. The fact that these adults had at some point sought services at tribal clinics potentially suggests some degree of community involvement or may be an indicator of tribal enrollment or eligibility for IHS services.

Self-report questions were used to measure language, and more thorough or extensive measures would help improve our understanding of language and its relationship to culture and health. Our survey instrument, along with other health-based research methods, underestimates the complexity of Indigenous languages. Using an oral interview would be more sufficient but has its drawbacks as well, especially for endangered languages. The interviewer, even if trained in oral interview methods, must be consistent to make the test reliable across all subjects. The interviewer must also be well versed in the language in order to converse with each subject on contexts relevant to the subject’s life.

Survey questionnaires cannot capture the many contexts in which language is used. Because many individuals do not have the ability to use the Indigenous language to its fullest extent, individuals might not be aware of the complexities of using language within all aspects of life, from everyday conversations with family and peers to classroom use when studying complex mathematical or scientific concepts to sending prayers through spiritual realms.

One strength of this study is that it provided participants with a broad range of questions to dig into spirituality and culture. Participants were asked about their involvement in very specific and locally relevant traditional and spiritual activities. In addition, they were asked questions that allowed them to include their own interpretation of culture and spirituality. We used both types of measurement items within analyses.

There may also be deficits in the way we, as researchers, perceive and measure health. Ideas of community well-being and health can be much different than the dominant culture, and researchers should consider finding new ways to measure positive health variables. For example, while American Indians have disproportionately higher rates of depression when compared to national averages, over half (51.5%) of one study population also experienced flourishing positive mental health ( Kading et al. 2015 ).

Summary and Future Directions

Our findings from Ojibwe community members highlight the strong connection between culture and language proficiency and provide a point estimate of language proficiency among community members. Language and cultural participation are closely connected, and both are seen as key mechanisms for improving health and wellness in Indigenous communities. Because the data were cross-sectional, we do not know if language use facilitates participation in the cultural and spiritual activities, or if these activities encourage the development of the language. Both are likely occurring. Before relying heavily on quantitative research methods to understand language’s role in health, it would be beneficial to first seek qualitative knowledge that deciphers the role language plays in healthy behaviors. In addition, future research should investigate how language knowledge or acquisition may lead to improved health. Our findings suggest that language and cultural involvement complement each other. Language programs that include cultural teachings and cultural involvement may be more successful in language revitalization and language preservation. Because elders were most likely to be fluent, and because a minority of participants could easily speak the language, this study underscores the critical need for language revitalization efforts across Ojibwe communities to tap into the vital resources of our elders.

Biographies

MIIGIS B. GONZALEZ , MPH, Ph.D., is a recent graduate in the Social and Administrative Pharmacy Ph.D. Program and a research assistant in the School of Medicine at the University of Minnesota, Duluth campus. She is an enrolled member of the Lac Courte Oreilles Band of Lake Superior Ojibwe. Her research interests include culture, language, and community-based approaches to Indigenous health and wellness with an emphasis on mental health, substance abuse prevention, and adolescent development.

BENJAMIN D. ARONSON , PharmD, Ph.D., is an assistant professor of social and administrative pharmacy at the Ohio Northern University Raabe College of Pharmacy. His research interests include health professional student development, advancing health service access and quality, and improving health care services in underserved communities by understanding health behav-iors and other social and structural determinants of health. Dr. Aronson’s teaching interests include the principles of pharmaceutical care, health care systems, quality in health care, and professional and leadership development of student pharmacists.

SIDNEE KELLAR , community research council member for the Mino Giizhigad study, was born in Washington the day after her dad discharged from the army. After moving to Wisconsin, she lived by her mom’s family’s cranberry marsh and her dad’s reservation. An Ojibwe elder would come over for coffee. He’d ask, “Sid’nee, how do you say horse?” Years later she started working at the tribal college and that same elder was there, teaching Ojibwe. Now his question was, “Sid’nee, when are you going to take my class?” She did, eventually graduating with an interdisciplinary studies degree. She currently teaches high school Ojibwe.

MELISSA L. WALLS , Ph.D., is an associate professor in the Department of Biobehavioral Health and Population Sciences at the University of Minnesota Medical School, Duluth campus. Dr. Walls is affiliated with the Bois Forte and Couchiching First Nation Anishinaabe. She is a social scientist committed to collaborative research with tribal communities in the United States and Canada. Her involvement in community-based participatory research (CBPR) projects to date includes mental health epidemiology; culturally relevant, family-based substance use prevention and mental health promotion programming and evaluation; and examining the impact of stress and mental health on diabetes.

BRENNA L. GREENFIELD , Ph.D., is a psychologist and assistant professor in the Department of Biobehavioral Health and Population Sciences at the University of Minnesota Medical School, Duluth campus. Her research is strengths-based and focuses on identifying and intervening on determinants of substance use and misuse among Native Americans.

1 NOTE “Chippewa” has been the legal term used by the federal government in major legal and treaty negotiations and is included in the names of multiple tribes ( Satz 1991 ; Treuer 2010 ), but many members of this group prefer the terms “Anishinaabe” or “Ojibwe.”

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HYPOTHESIS AND THEORY article

Beyond english: considering language and culture in psychological text analysis.

• 1 Department of Psychology, Faculty of Education, University of South Bohemia in České Budějovice, České Budějovice, Czechia
• 2 Department of Psychology, College of Science, University of Arizona, Tucson, AZ, United States

The paper discusses the role of language and culture in the context of quantitative text analysis in psychological research. It reviews current automatic text analysis methods and approaches from the perspective of the unique challenges that can arise when going beyond the default English language. Special attention is paid to closed-vocabulary approaches and related methods (and Linguistic Inquiry and Word Count in particular), both from the perspective of cross-cultural research where the analytic process inherently consists of comparing phenomena across cultures and languages and the perspective of generalizability beyond the language and the cultural focus of the original investigation. We highlight the need for a more universal and flexible theoretical and methodological grounding of current research, which includes the linguistic, cultural, and situational specifics of communication, and we provide suggestions for procedures that can be implemented in future studies and facilitate psychological text analysis across languages and cultures.

Introduction

The use of computerized text analysis as a method for obtaining information about psychological processes is usually dated to the 1960s, when the General Inquirer program was introduced ( Stone et al., 1962 ). Since then, this field has advanced and flourished in ways that were difficult to foresee at the time. The original (word-count) approaches have been enhanced and optimized in terms of the scope and complexity of their dictionaries and methods ( Eichstaedt et al., 2020 ), and the capacity of computers has arrived at processing very large amounts of data in no time. At the same time, extensive digital documentation and sharing, related to the growth of the information society ( Duff, 2000 ; Fuller, 2005 ), have provided almost unlimited input for text analysis.

Over the last decade, Natural Language Processing (NLP) methods have effectively become an established and attractive go-to method for psychological science ( Althoff et al., 2016 ; Pradhan et al., 2020 ). At present, they are developed mainly as automated systems that can understand and process texts in natural language, e.g., for conversational agents, sentiment analysis, or machine translation ( Amini et al., 2019 ). The new techniques, employing methods of artificial intelligence, classical machine learning (ML), and deep learning methods ( Magnini et al., 2020 ) are gradually displacing original approaches, with their eventual dominance in the field being a safe prediction ( Johannßen and Biemann, 2018 ; Eichstaedt et al., 2020 ; Goldberg et al., 2020 ).

By implication, the field can currently be thought of as being in a transitional phase—although most cited studies in psychology are based on foundations laid with conventional computational techniques (e.g., word counting), their share is gradually decreasing in favor of more complex techniques (e.g., ML processing). This phase is crucial in many ways, not only for the (re)evaluation of existing research backgrounds and evidence but also for the development and optimization of next-generation psychological text analysis methods.

The goal of this article is to provide a critical review of the approaches, methodology, and interpretation of traditional closed-vocabulary text analysis from the specific perspective of multicultural and multilingual research. Attention is paid to three fundamental challenges: (1) the specifics of language and culture, (2) the levels of language analysis in question and the terminology used, and (3) the context of the use of specific tools and methods. The article ends with a discussion of possible adjustments and extensions to methods and outlines further perspectives and desiderata for conducting cross-language research in psychology.

Challenges in Cross-Language Psychological Text Analysis

Over the last two decades, research on psychological aspects of natural word use ( Pennebaker et al., 2003 ; Ramírez-Esparza et al., 2008 ; Harley, 2013 ) has provided an impressive bedrock of scientific findings. Most of this research has been carried out using closed-vocabulary approaches, methods based on assigning words within a target text document to categories of a predefined word dictionary ( Eichstaedt et al., 2020 ). Semantic and grammatical features of word use have been identified as psychological markers of personal speaker characteristics, for example, gender and age ( Biber, 1991 ; Mehl and Pennebaker, 2003 ; Newman et al., 2008 ), personality characteristics ( Tausczik and Pennebaker, 2010 ; Yarkoni, 2010 ; Gill and Oberlander, 2019 ), social characteristics ( Berry et al., 1997 ; Avolio and Gardner, 2005 ; Dino et al., 2009 ; Kacewicz et al., 2014 ), emotions ( Brewer and Gardner, 1996 ; Pennebaker and Lay, 2002 ; Newman et al., 2008 ), and health ( Ramírez-Esparza et al., 2008 ; Demjén, 2014 ). The research has so far mostly been conducted within an explanation framework, but is now also increasingly used for prediction purposes ( Yarkoni and Westfall, 2017 ; Johannßen and Biemann, 2018 ).

The large number of existing studies speaks to the high relevance of this research, both in terms of establishing consensus between studies and in revealing relationships with other variables as support for concurrent validity with the results of established measures. However, recent studies have also raised important questions about the generalizability of existing findings beyond the original context of investigation, which has highlighted potential constraints on their validity in different languages and cultures ( Garimella et al., 2016 ; Basnight-Brown and Altarriba, 2018 ; Jackson et al., 2019 ; Sánchez-Rada and Iglesias, 2019 ; Chen et al., 2020 ; Thompson et al., 2020 ; Dudãu and Sava, 2021 ). The results of the studies also indicate that the comparison and psychological interpretation of linguistic phenomena between different cultures and languages is subject to several fundamental challenges.

Language and Culture in Question

The first challenge concerns the choice of the language and culture in which the texts are analyzed and interpreted. Currently, the vast majority of psychological language research is based on English, which dominates contemporary science as a lingua franca ( Meneghini and Packer, 2007 ; Seidlhofer, 2011 ). The preference of research in English is understandable—English is a global language (e.g., the most used language of international communication, information technology, and on the Internet) ( Internet Users by Language, 2021 ), English is the consensual language of academic discourse and, as such, it has a broad research base ( Johnson, 2009 ). Nevertheless, the number of English native speakers (approx. 360–400 million) ( König and van der Auwera, 2002 ), is a small fraction of the world’s population. There are approximately 6,900 languages spoken today, of which 347 have more than 1 million speakers ( Bender, 2011 ).

Although it may seem that languages are rather similar to each other, in many cases they exhibit substantial phonological, morphosyntactic, and semantic structural differences. In other words, they operate with different linguistic building blocks, structures, and relations to communicate equivalent ideas ( Haspelmath, 2020 ). As an example, we can describe the variance that exists in even such a basic classification as content (lexical) vs. function (grammatical) words ( Corver and van Riemsdijk, 2001 ). Although most languages allow a relatively clear distinction between these two types, this is not the default for all languages ( Asher and van de Cruys, 2018 ). For example, in indigenous North American languages, the words “sit,” “stand,” and “lie,” considered content words in English, appear as both content and function words ( Hieber, 2020 ). Moreover, many word classes (parts of speech) are not present in some languages (e.g., adjectives are not present in Galela language) ( Rijkhoff, 2011 ). Such differences exist at all levels of language (i.e., language domains, parts of grammar) and further examples will be given below.

In addition to differences between individual languages, differences between cultures using the same language should also be mentioned. As an example, we can use English, which is currently the official language in at least 58 countries ( List of Countries Where English Is an Official Language – GLOBED, 2019 ). Not surprisingly, the use of English shows a number of variations across these cultures. The variations are most often manifested at the level of pragmatics (e.g., accentuated manifestations of egalitarianism in western Anglophone cultures compared to more pronounced patterns of respect in Asian and Polynesian Anglophone cultures) ( Thomas and Thomas, 1994 ), but also at the level of semantics—in understanding the meaning of words (e.g., the word “old” is usually more semantically related to “age” in Australian English and to the “past” in American English) ( Garimella et al., 2016 ). Other aspects also contribute to language variation, such as dialects or the specific use of English by non-native speakers ( Wolfram and Friday, 1997 ; Yano, 2006 ). Considering that languages show such variability at both intra-lingual and inter-lingual levels, and function differently in many aspects, this may raise the question of the adequacy of single-language results (or single-culture results) that are often implicitly assumed to be broadly applicable ( Wierzbicka, 2013 ).

Definition of Levels and Variables of Language Analysis

The second challenge consists of the definition of the level of language (language domain, area of linguistic analysis) we focus on, the terminology used, and the variables in question. In research on the psychology of word use, terminology is often not set in accordance with traditional taxonomy in linguistics and does not adequately reflect interlingual differences. Instead of distinguishing language levels (domains) in dimensions which are more universal and established among linguists, e.g., morphology, syntax, semantics, lexicology, etc. ( Hickey, n.d. ; Mereu, 1999 ; Kornfilt, 2020 ), the focus of the analysis is often described in eclectic ways, based on the specifics of the language in question. For example, English is a language that has a relatively poor morphology compared to other Indo-European languages ( Vannest et al., 2002 ; Milizia, 2020 ), and the level of morphology is therefore often integrated into a group of diverse variables or is replaced by other concepts. A common example is the sorting of language features into fuzzy categories such as “Linguistic Dimensions” (covering word classes and morphology), “Other Grammar” (covering word classes and both morphology and syntax), and “Psychological Processes” (covering semantics, morphology, syntax, and pragmatics together) in the LIWC2015 program ( Pennebaker et al., 2015 ) (note: this method is described in more detail below). In fact, each of these categories includes strictly linguistic dimensions (variables), only in different configurations.

Another example is the differentiation between ‘language content’ (content of communication, that is, what is communicated/told, that usually covers lexical and semantic level) and ‘language style’ (the way the content is conveyed, that is, how the author is communicating, theoretically covering all levels of analysis, including morphology) ( Ireland and Pennebaker, 2010 ). The assumption that language content and style can be unambiguously distinguished at the level of individual variables is questionable, since the definition of words as “content” (e.g., nouns, verbs) or “stylistic” (e.g., pronouns and prepositions) varies considerably between languages ( Corver and van Riemsdijk, 2001 ; Asher and van de Cruys, 2018 ; Hieber, 2020 ). Even the most general distinction between function words and content words in one language captures rather a continuum, where prototypical function words and content words appear at opposite ends ( Osborne and Gerdes, 2019 ). In summary, although these conceptual or effectively metaphorical distinctions have proven theoretically generative and practically useful, they can significantly limit the possibilities of cross-language comparison.

The unclear taxonomy and exclusive, domain-specific terminological definition bring with them complications both at the level of interdisciplinary cooperation (e.g., among psychologists and linguists) and at the level of intercultural research ( Sonneveld and Loening, 1993 ). For languages that are relatively close in their structure, the discrepancy in classification may not be pronounced, but when distant languages are studied and compared, substantial differences can arise. The taxonomy of words and their functions is non-trivially language-specific, with different languages providing different classifications of language content and style ( Nivre et al., 2016 ; Kirov et al., 2020 ). In some languages, the same grammatical relationship is expressed morphologically, in others through function words, while some languages do not mark this information at all (e.g., in grammatical tense or definiteness) ( Osborne and Gerdes, 2019 ; Universal Dependencies: Syntax, 2021 ).

For example, many locatives are marked by prepositions in English (e.g., “in,” “by,” “to,” “from”), while in Finnish they appear as morphological case-inflections (e.g., “-ssA,” “-llA,” “-lle,” “-stA,” “-ltA”). Furthermore, possessives and adverbials can be marked morphologically in Finnish (e.g., “-ni”—“my,” “-si”—“your”), but in English they appear as separate words, thus a word form like “auto-i/ssa/ni/kin” (“also in my cars”) with stem and four subsequent suffixes would need four separate words in English ( Vannest et al., 2002 ). The Czech language provides another example of the interconnection between language content and style. It also works with a wide range of grammatical suffixes that change paradigmatic and grammatical classification, e.g., the word “uč” (“teach!”) with suffixes “-it” (“to teach”) “-el” (“teacher”) “-ova/á” (“of teacher”) “-ní” (“teaching”) “-čko” (“little teaching”), where each of the suffixes can changes the inflection and/or semantic nature of the word ( Rusínová, 2020 ). Therefore, a text analysis approach that counts and processes such linguistic units as stand-alone words ( Pennebaker and King, 1999 ; Pennebaker et al., 2014 ) is inherently limited and potentially biased.

Approaches and Methods in Question

The third challenge concerns specifics around the commonly employed text analytic approaches and methods. Many methods were primarily designed for the processing of a specific language, or even a specific type of communication (i.e., genre or register), and their use in cross-language research can therefore result in methodological and interpretive difficulties. In this regard, the current approaches to quantitative text analysis, based on lexical and semantic levels of analysis (treating words/tokens as lexical units within a certain semantic field) ( Cruse et al., 1986 ), can be divided into two main groups—closed-vocabulary approaches and open-vocabulary approaches ( Schwartz et al., 2013b ). Closed-vocabulary approaches operate from “top down” and assign words from a target text to psychologic categories within a specific and fixed dictionary (e.g., a dictionary of emotional words that covers categories of positive and negative emotion categories). This procedure is also referred to as the word-count approach ( Schwartz et al., 2013a ; Iliev et al., 2015 ; Kennedy et al., 2021 ). The result of the analysis is usually the (normalized) frequency within which references to these categories occur in a given text ( Eichstaedt et al., 2020 ).

Compared to that, open-vocabulary approaches operate from “bottom-up” (data-driven), that is, based on language (text) as such. Algorithms identify related clusters of units (lexical units or elements, for example, punctuation) that naturally occur (and co-occur) within a large set of texts and find lexical and semantic patterns that appear (and appear together) in the data ( Park et al., 2015 ; McAuliffe et al., 2020 ). Both approaches have their pros and cons; as stated by Eichstaedt et al., “Closed-vocabulary approaches can be rigid, while open-vocabulary approaches can be sensitive to idiosyncrasies of the dataset and the modeler’s choices about parameters. Closed-vocabulary approaches are more reproducible but inflexible, where open approaches are more flexible but can vary across datasets” (p. 77) ( Eichstaedt et al., 2020 ). Given the historical dominance of word-count approaches, the following section focuses in detail on closed-vocabulary analysis.

Closed-Vocabulary Approaches in Cross-Cultural Research

In terms of the number of published studies, closed-vocabulary approaches still dominate by far the field of psychology of word use. There are many reasons for their preference, for example, their implementation exacts little technical demands (training of the AI, development of algorithms, etc.), they allow relatively uncomplicated interpretation of the results, and they also do not require large datasets to perform the analysis ( Eichstaedt et al., 2020 ; Sharir et al., 2020 ). Over the last six decades, a number of tools have been developed, e.g., General Inquirer ( Stone et al., 1962 ), DICTION ( Hart, 2001 ), Linguistic Inquiry and Word Count (LIWC) ( Pennebaker et al., 2015 ), Affective Norms for English Words (ANEW) ( Bradley and Lang, 1999 ), SentiStrength ( Thelwall et al., 2010 ), SentiWordNet ( Baccianella et al., 2010 ), OpinionFinder ( Wilson et al., 2005 ), Regressive Imagery Dictionary ( Martindale, 1973 ), TAS/C ( Mergenthaler and Bucci, 1999 ), Gottschalk-Gleser Scales ( Gottschalk et al., 1969 ), or Psychiatric Content Analysis and Diagnosis (PCAD) ( Gottschalk, 2000 ).

Most of these methods are primarily focused on the level of lexical semantics, that is, on searching for words with specific semantic loading. The analyzed text is usually compared with a predefined dictionary that contains words that represent a concept (e.g., religion words) or a psychological state (e.g., positive emotion words). For example, the concept of ‘satisfaction’ in DICTION is represented by words such as “cheerful,” “smile,” or “celebrating” ( Hart and Carroll, 2011 ). Leaving aside the question of the validity of the semantic categories in the dictionary itself (cf. Garten et al., 2018 ), there are several issues that closed vocabulary analysis has to deal with. A common problem is the interpretation of lexical ambiguity and the meaning of words in different contexts ( Hogenraad, 2018 ). A typical example in English are contronyms or polysemous words such as “fine” (signifying both pleasant and a penalty), “mean” (signifying both bad and average), and “crazy” (signifying both excitement and mental illness). The risk of misinterpretation (misclassification) can be reduced by, e.g., removing or replacing ambiguous words from the dictionary ( Schwartz et al., 2013a ). However, such a procedure almost necessarily also reduces the sensitivity of the semantic category, and thus the precision of the analysis.

Level of Lexical Semantics in Cross-Language Adaptation

If we focus on cross-language adaptation of closed-vocabulary methods, it should be emphasized that these tools are naturally based on the specifics of the source (original) language for which they were developed, most often English [see Mehl (2006) ]. Therefore, adapting such dictionaries to other languages is often a complicated and time-consuming process that faces a series of additional challenges ( Bjekić et al., 2014 ; Dudãu and Sava, 2020 ; Boot, 2021 ). First, the methods are most often based on the original cultural and linguistic structure rather than the target culture or language, that is on the imposed-etic approach ( Berry et al., 1997 ). This strategy can lead, among others, to the risk of reductionism or misinterpretation of results, for example, when constructs (variables/categories) do not exist, are not equivalent, or function differently in the original and target language ( Church and Katigbak, 1989 ). Languages often have unique words that are difficult to express in other languages (e.g., words like “toska” in Russian, “jamani” in Swahili or “saudade” in Portuguese). Furthermore, even for words that seem easy to translate, their meaning may shift, e.g., in English, the word “anger” is mainly related to wrath, irateness or rage, while in the Nakh-Daghestanian languages, it is closer to envy and in the Austronesian languages more closely associated with pride ( Jackson et al., 2019 ).

Let us add that semantic changes are not a matter of cross-language comparison only, but they can also occur naturally within one language, such as in different historical stages of a language ( Vanhove, 2008 ; Riemer, 2016 ; Garten et al., 2018 ).

Second, the possibility of estimating possible shortcomings of dictionary adaptation can be problematic, since the degree of equivalence varies not only across language features (some words are more cross-linguistically and cross-culturally comparable than others) ( Biber, 2014 ), but also across different communication contexts ( Daems et al., 2013 ; Biber and Conrad, 2019 ; Dudãu and Sava, 2020 ). For example, the meaning and use of the English word “hump” vary both between English speaking cultures and between situational contexts (e.g., in British English it can refer to an emotional state, in American English it can refer to a vigorous effort, depending on the context in which it can be perceived as vulgar). In some languages, the influence of the context is crucial for the word interpretation and classification, such as in Czech, where sociolinguistic situation (inter-lingual variation) borders on diglossia ( Bermel, 2014 ). Thus, we can assume that dictionaries validated only in a certain communication context (e.g., academic essays) will not be sufficiently effective in another context (e.g., informal conversations).

The topic of comparability of language variables (words, units, features) across languages is discussed in a number of studies. Although many of them have revealed a high degree of similarity in the results of cross-language analysis ( Ramírez-Esparza et al., 2008 ; Windsor et al., 2019 ; Vivas et al., 2020 ), there is increasing evidence pointing to significant differences in lexical and semantic functioning across more distant languages. In the study by Thompson et al. (2020) , published in Nature Human Behavior , the authors analyzed semantic alignment (neighborhood) for 1,010 meanings in 41 languages using distributed semantic vectors derived from multilingual natural language corpora. While some words within semantic domains with a high internal structure were more closely aligned across languages—especially quantity, time, and kinship (e.g., “four,” “day,” and “son”), words denoting basic actions, motion, emotions and values (e.g., “blow,” “move,” and “praise”) aligned much less closely. In terms of semantic alignment by parts of speech (word classes), the highest alignment was found in numerals, while other parts of speech were much less aligned (e.g., prepositions were the least aligned). Thus, this study critically questions the idea of widely comparable word meanings across languages, at least from a cross-cultural universalist perspective ( Kim et al., 2000 ).

Another study, published in Science , examined nearly 2,500 languages to determine the degree of similarity in linguistic networks of 24 emotion terms ( Jackson et al., 2019 ). The study also revealed a large variability in the meaning of emotion words across cultures. For example, some Austronesian languages colexifies the concepts of “pity” and “love,” which may index a more positive conceptualization of “pity” compared to other languages. Another example concerns the connotation of “fear,” which is more associated with “grief” and “regret” in Tai-Kadai compared to other languages. As the authors show, the similarity of emotion terms could be predicted based on the geographic proximity of the languages, their hedonic valence, and the physiological arousal they evoke. Given the central role of emotion words, and more broadly sentiment analysis, in the field of language analysis, this study has clear implications for cross-language analysis, particularly when comparing distant cultures and languages.

Finally, cultural differences in language use were also documented in a study that focused only on English. Garimella et al. (2016) described the differences between Australia and the United States based on the words they used frequently in their online writings. The results indicated that there are significant differences in the way these words are used in the two cultures, reflecting cultural idiosyncrasies in word use. For example, the adjective “human” is more related to human rights in the Australian context, but more to life and love in the United States context ( Garimella et al., 2016 ). From our point of view, these studies provide important insights: although languages are similar in many ways and they certainly share universal bases, the degree of similarity varies depending on cultural and geographical specifics.

The Linguistic Inquiry and Word Count Program as an Example

So far, we have focused on the analysis on the lexical semantics level only—this level is also common to all closed vocabulary approaches mentioned above. However, one of the methods, the LIWC program, is exceptional in this respect—besides traditional semantic categories (social words, emotion words, etc.), it provides an additional analysis of morphology and syntax features. Therefore, LIWC therefore serves well to illustrate the potentials and pitfalls of cross-linguistic adaptation of the closed vocabulary method in the context of multiple language levels (domains).

Linguistic inquiry and word count ( Pennebaker et al., 2015 ) is currently the most widely used text analysis method in the social sciences. At the time of writing this article, 781 records were available on the Web of Science that contained “LIWC” or “Linguistic Inquiry and Word Count” as the topic, and more than twenty thousand records are listed on Google Scholar. In its current version, LIWC2015, the program offers an intuitive user interface and provides a simple and clear output of the results ( Pennebaker et al., 2015 ), including a range of comparison possibilities ( Chen et al., 2020 ). LIWC dictionaries have been translated and adapted into multiple languages, including Spanish ( Ramírez-Esparza et al., 2007 ), French ( Piolat et al., 2011 ), German ( Wolf et al., 2008 ; Meier et al., 2019 ), Dutch ( Boot et al., 2017 ; Van Wissen and Boot, 2017 ), Brazilian-Portuguese ( Balage Filho et al., 2013 ; Carvalho et al., 2019 ), Chinese ( Huang et al., 2012 ), Serbian ( Bjekić et al., 2014 ), Italian ( Agosti and Rellini, 2007 ), Russian ( Kailer and Chung, 2007 ), Arabic ( Hayeri, 2014 ), Japanese ( Shibata et al., 2016 ), and Romanian ( Dudãu and Sava, 2020 ).

English LIWC2015 works with approximately 90 features grouped into 4 domains: “Summary Language Variables” (general text descriptors and lexical variables, including one syntactic variable “words per sentence”), “Linguistic Dimensions” (containing summary variables, word classes variables, and morphological variables, e.g., “total function words “, “articles,” “1st person singular,” and “negations”), “Other Grammar” (containing word classes variables, and both morphological and syntactic variables, “numbers,” “comparisons,” and “interrogatives”), and “Psychological Processes” (containing semantic variables and other variables, e.g., “sadness,” “non-fluencies,” and “causation”) ( Pennebaker et al., 2015 ). In terms of the analytic procedure, LIWC operates on relatively simple principles. LIWC uses its own dictionary to simply identify and label the corresponding words in the analyzed text— via word-count. Pre-processing in LIWC includes only basic segmentation and requires additional manual tagging (e.g., for specific ambiguous filler words, e.g., “well,” “like,” or non-fluencies, e.g., “you know”). More advanced NLP procedures, on the other hand, use pre-trained models and perform a sequence of “cleaning” processes in such tasks (e.g., Rayson, 2009 ; Manning et al., 2014 ), e.g., part of speech disambiguation and tagging, lemmatization, or parsing ( Straka and Straková, 2017 ).

Several strategies have been used to adapt the LIWC dictionary to other languages ( Boot, 2021 ). These include the supervised translation of the English dictionary word by word ( Bjekić et al., 2014 ; Dudãu and Sava, 2020 ), the use of the existing word corpora and their assignment to corresponding LIWC categories ( Andrei, 2014 ) or as an enrichment of LIWC categories ( Gao et al., 2013 ; Meier et al., 2019 ), the use of dictionaries in closely related languages ( Massó et al., 2013 ), the modification of the older version of the dictionary ( Zijlstra et al., 2004 ), or adapting the original dictionary via machine translation ( Van Wissen and Boot, 2017 ). The various LIWC languages differ significantly in the number of words contained in the dictionary. For example, the Romanian LIWC dictionary (Ro-LIWC2015) contains 47,825 entries compared to the English LIWC2015 dictionary with 6,549 entries (including words, word stems, and emoticons; cf. LIWC2007 contains 4,500 words, and LIWC2001 contains 2,300 words). The average proportion of words identified (labeled) by LIWC also varies considerably across the different LIWC language dictionaries, for example 87% in English (LIWC2015; cf. 82% in LIWC2007), 88% in German (DE-LIWC2015; cf. 70% in LIWC2001), 70% in Dutch, 54% in French, 66% in Spanish, 70% in Serbian, and 67% in Romanian ( Bjekić et al., 2014 ; Dudãu and Sava, 2020 ), speaking to the fact that the LIWC approach likely yields differential sensitivity across different languages.

Analysis of Non-semantic Levels of Language

The translation and adaptation process faces most of the issues described above. Here, however, the analysis deals also with additional challenges, connected to level of morphology and syntax of the target languages, for example the pronoun-drop phenomenon (in some languages, users very frequently omit pronouns, particularly in their subject positions; e.g., “tengo hambre” in Spanish dropping the first-person singular pronoun “yo”) ( Świątek, 2012 ), grammatical classification (e.g., pronominal adverbs in Dutch, that combine pronouns/adverbs with prepositions—“we doken erin” which replaces “we doken in het”—“we dived into it”), grammatical restrictions (some linguistic features are restricted to particular languages, see below), with case sensitivity problems (LIWC is not case-sensitive which makes it difficult to process certain words, e.g., the German word “Sie” which, if capitalized, serves as formal second person singular or plural pronoun and, when not capitalized, serves as third person plural pronoun), and the above mentioned ambiguity (including, if the capitalized word appears at the beginning of a sentence) ( Boot, 2021 ).

Although some shortcomings of the dictionary translation approach can be partially overcome (e.g., by removing words from the dictionary, adding new words and phrases, or with data pre-processing), they still increase the risk of reduced sensitivity and validity, especially in its reliability and comparability to the original method. As already mentioned, this applies particularly to languages with a grammatical structure more distant from English. For example, due to the grammatical structure of Serbian (a Slavic language), the category of verbs had to be substantially modified, and the category of articles had to be removed completely ( Bjekić et al., 2014 ). Many adjustments were also made in the Romanian adaptation, for example in verb tense, grammatical gender, or diacritics processing ( Dudãu and Sava, 2020 ). To sum up, every translation of the LIWC dictionary involves many decisions about which entries (words or categories) should be kept, dropped, or added, and each decision is necessarily a trade-off between computational feasibility and linguistic accuracy ( Dudãu and Sava, 2021 ).

Cross-Language Evaluation of Linguistic Inquiry and Word Count

The extent to which language specifics and LIWC adjustments affect the quality of adaptation is difficult to evaluate, as the studies differ in many aspects. Some studies do not report psychometric validation information for their dictionaries (e.g., Arabic, Turkish, or Russian), while others provide only indirect evidence ( Balage Filho et al., 2013 ). In several studies, equivalence estimates are presented as a general indicator of the quality of adaptation. Equivalence is usually estimated via correlation coefficients between the adapted version of LIWC and the English original. If we focus on four major studies, the authors report an average correlation of adapted LIWC and English LIWC as r = 0.67 for German based on N = 5,544/6,463 texts in German/English (Europarl corpora and transcriptions of TED Talks transcriptions), r = 0.65 for Spanish ( N = 83 texts in Spanish/English; various Internet sources), r = 0.65 for Serbian ( N = 141 texts in Serbian/English; scientific abstracts, newspapers and movie subtitles), and r = 0.52 for Romanian ( N = 35 books of contemporary literature in Romanian/English) ( Ramírez-Esparza et al., 2007 ; Bjekić et al., 2014 ; Meier et al., 2019 ; Dudãu and Sava, 2020 ).

Although the average values of the correlations can be considered satisfactory, upon closer inspection, they vary widely between categories and levels of analysis, especially in morphology and semantics. For example, in the Romanian LIWC, most correlations of non-semantic categories are non-significant (11 of 18 categories). Significant results were found in the category “Pronouns” in the first person (singular 0.93, plural 0.92) and in the third person singular (0.66, plural non-significant), in the category “Other Function Words” in conjunctions (0.37) and negations (0.53) and in the category “Other Grammar” in interrogatives (0.58) and quantifiers (0.66) ( Dudãu and Sava, 2020 ). Considering these results and the average proportion of total words identified in the Romanian LIWC (only 67% words were labeled), we must conclude that the Romanian LIWC appears not effective enough for the comparable analysis of non-semantic (grammatic) categories, even though its dictionary is seven times bigger than the English original (Romanian: 47,825 entries; English: 6,549 entries; Dudãu and Sava, 2020 ).

Another issue concerns the specificity of text samples on which validity and equivalence tests were performed. In this sense, the communication context (text type, genre, register) is an important factor that can produce substantial variation both in the frequency of language features and in the associations with other variables, especially psychological ones ( Pennebaker et al., 2007 ; Daems et al., 2013 ; Haider and Palmer, 2017 ; Biber and Conrad, 2019 ; Kučera et al., 2020 ; Dudãu and Sava, 2021 ). Differences in the sensitivity of LIWC for detecting psychological markers in different types of text (English only), were shown in the meta-analysis of Chen et al. (2020) , in which, for example, the strength of the relationship between extraversion and positive emotion words varied significantly and substantially across communication contexts (e.g., asynchronous/synchronous and public/private communication). Thus, if only one type of communication is used (e.g., only written language), it is difficult to estimate to what extent the translated dictionary has comparable validity for, for example, spoken communication. Moreover, it is possible to assume that the language variation is related to multiple factors, not only to the type of text, but also to, for example, sociodemographic characteristics of speakers ( Stuart-Smith and Timmins, 2010 ), as well as to discourse domain and language itself ( Biber, 2014 ).

The above-mentioned challenges have implications not only for the adaptation of closed-vocabulary methods to other languages, but for the field of psychology of word use more broadly. Due to the predominant interest of research in the English language, psychological language markers are often implicitly presented in studies as relatively universal, generalizable at least to English-speaking cultures ( Chung and Pennebaker, 2018 ). In many classical studies, for example, frequent use of first-person singular pronouns has emerged as a marker of negative emotionality ( Pennebaker and King, 1999 ; Pennebaker et al., 2003 ; Oberlander and Gill, 2006 ; Gill et al., 2009 ; Yarkoni, 2010 ; Qiu et al., 2012 ). However, subsequent research in other languages and on other samples relativizes this relationship ( Mehl et al., 2012 ; Bjekić et al., 2014 ; Holtzman et al., 2019 ; Kučera et al., 2020 , 2021 ). Given the lack of cross-language and cross-cultural studies, the original assumption of generalizability is understandable. However, considering recent studies, the previous conjectures need to be corrected for regarding the culture, language, and communication contexts and samples in which the relationships emerged. If the different functioning of words in other languages and cultures is not sufficiently described, many generalizations may be biased or misrepresented as a result.

Dealing With Closed-Vocabulary Cross-Language Analysis

Although the issues raised above may raise pessimism regarding the possibilities of closed-vocabulary approaches in cross-language research, we believe that most challenges can (and need to be) overcome, at least to some extent. Closed-vocabulary approaches offer, in contrast to open-vocabulary approaches, several advantages that are important for psychological research. The categories they work with can be intuitively labeled and (and facilitate interpretation, explanation, testing, and accumulation and transfer of results (e.g., into other languages and contexts) ( Kennedy et al., 2021 ). Even if traditional methods are replaced by new technologies (e.g., AI), the demand for interpretations of phenomena based on intuitive categories (e.g., representing variables using established psychological concepts) is bound to survive. In the rest of the article, we therefore focus on suggestions that support the effective use of closed-vocabulary approaches in multilingual and multicultural setting.

Dealing With Language and Culture

The first challenge we discussed was the language and culture on which the analysis is based and the degree of its similarity to other languages and cultures. To build on the previous arguments, text analysis methods likely provide more different results the further apart studied languages and cultures are, not only because of the methodological differences in analysis, but also because of the specifics of the languages and cultures themselves. As a parallel, we reference the issues concerning the use of Big Five personality questionnaires across cultures (the most widely used method for assessing personality characteristics), which outside of western, educated, industrialized, rich and democratic (WEIRD) populations shows serious limitations and low validity for measuring the domain of basic personality traits ( Laajaj et al., 2019 ). In the same way, striving for better explanations of cross-linguistic variation requires employing the power of cross-cultural comparisons to describe the variation and similarity ( Barrett, 2020 )—the methodology must be linked to more principled sampling, both at the level of speakers (e.g., representative sample of speakers in a given culture or at least a sample corrected for imbalances) and texts (e.g., to acquire the texts with regard to their ability to be representative for selected communication contexts).

Since the cross-language comparison based on texts from the entire communication spectrum would be difficult to implement, it is necessary to choose specific types of communication (i.e., registers, and genres) to be analyzed. Leaving aside their ease of availability to the researcher, the focus should be on types of text that show a certain degree of cross-language universality. In this regard, existing cross-linguistic studies on register variation can provide important information in this regard. For example, Biber’s research finds two language dimensions (i.e., constellations of linguistic features that typically co-occur in texts) that could be considered relatively (although not absolutely) universal: (1) “clausal/oral” discourse vs. “phrasal/literate” discourse, and (2) “narrative” vs. “non-narrative” discourse ( Biber, 2014 ). The first dimension linguistically comprises typical grammatical features (e.g., verb and pronoun classes) and is based functionally on a distinction between a personal/involved focus and informational focus (e.g., private speech vs. academic writing as prototypic genres). The second, narrative dimension, consists of different sets of features (e.g., human nouns and past tense verbs), and typically appears in fictional stories, personal narratives, or folk tales. These general patterns have emerged from different studies of languages other than English, for example, Spanish, Brazilian Portuguese, Nukulaelae Tuvaluan, Korean, Somali, Taiwanese, Czech, and Dagbani ( Biber, 2014 ).

From the point of view of cross-language comparison, it is therefore recommended to choose text types that are at least somewhat comparable on these two dimensions to ensure maximum (in the sense of as much as reasonably possible) comparability. If the selection of texts cannot be made by dimensions defined ex ante (e.g., if the texts have already been collected), it is also possible to subject the texts to ex post dimensional analysis via multi-dimensional analysis (MDA), an approach that identifies co-occurrence patterns of linguistic features based on the factor analysis ( Biber, 1991 ). Through MDA, it is possible to describe different texts in terms of their similarity in dimensional structure. However, MDA is currently only available for a limited number of languages (in addition to the languages listed above for Scottish Gaelic and written Chinese) ( Sardinha and Pinto, 2019 ).

Dealing With Levels of Analysis and Language Variables

The second challenge concerns the terminology and language level (domain) that is the subject of the analysis. Since the definition of language variables based on the specifics of one language only is problematic, it is necessary to work with variables that have common characteristics and to categorize them in a more clearly defined system. The issue of universal classification has been addressed in a number of studies, both theoretically and practically ( Hasselgård, 2013 ). If we are to build on newer approaches, two of the available linguistic frameworks can serve as an example to follow, the Universal Dependencies (UD) and the Universal Morphology (UniMorph) projects ( Nivre et al., 2016 ; McCarthy et al., 2020 ). Both frameworks focus on the annotation of human language and connect many fields of contemporary linguistics ( Osborne and Gerdes, 2019 ; de Marneffe et al., 2021 ). In both frameworks, morphology (including part of speech) and syntax are considered the most principal non-semantic levels of language analysis in the taxonomies.

Universal Dependencies 1 is a framework for annotation of grammar across different human languages, currently available for 122 languages with 33 more in preparation ( Universal Dependencies, 2021 ). Morphological variables of UD include, for example, the categories of part of speech and lexical and inflectional features (e.g., pronominal type and degree of comparison), and syntactic variables include cover dependency relations between words (relations between a syntactic head and a subordinate element, e.g., multiple determiners attached to the head noun).

The UniMorph project 2 has similar goals as UD and provides normalized morphological paradigms for diverse world languages, especially low-resource languages with inflectional morphology. The schema of UniMorph comprises 23 dimensions of meaning (e.g., person, number, tense, and case) and over 212 features (for the dimension of case, e.g., ablative, absolutive, accusative, etc.) ( Sylak-Glassman, 2016 ; McCarthy et al., 2020 ).

If we consider Universal Dependencies and the Universal Morphology frameworks from the perspective of cross-language research, i.e., when comparing multiple languages analyses, a comment needs to be added to the number and applicability of linguistic variables. Since the set of linguistic features (categories, dimensions) we can work with is entirely dependent on properties of languages in question, it is necessary to identify features that are shared between these languages—i.e., identically labeled in UD or UniMorph. For example, if we compare the results of UD text analysis in English and Spanish, we can only work with 13 English features, which are shared with Spanish (e.g., degree, gender, person, polarity; see English ParTUT and Spanish AnCora treebanks; Universal Dependencies, 2021 ). However, UD in Spanish offers more linguistic features (23 features in total), and we can use these “non-English” variables, e.g., in a further comparison with another language.

To sum up, the frameworks provide useful tools, and they can serve as a starting point for better classification and (re-)definition of language variables for the purposes of cross-language psychological analyses. In addition, Universal Dependencies Tools are open-source software, so they are available for free.

Dealing With Cross-Language Adaptation of Methods

The third challenge is related to current approaches to text analysis and their methods. In terms of cross-language use of semantically based closed-vocabulary approaches, research should focus primarily on identifying and covering the semantic specifics and functioning of words in different languages, not just on translating the text into the language of analysis. Studies that describe the semantic alignment of words across different languages and contexts could help here ( Garimella et al., 2016 ; Jackson et al., 2019 ; Thompson et al., 2020 ). For both semantic and morphological analysis, several procedures can be used to increase the comparability of the analyses. For example, it is possible to use statistical adjustments proposed by Dudãu and Sava—to employ multilevel analysis with language as the level 2 covariate (especially when text input is available in relatively different languages) or to perform within-language standardization to attenuate the language particularities that could affect the investigation in the multilingual setting.

For example, Brazilian Portuguese probably has linguistic particularities in the use of third-person singular (e.g., in personal pronouns and possessives with a higher degree of inflection), which can cause inconsistencies in cross-language comparisons ( Carvalho et al., 2019 ). To avoid the lack of equivalence between results of analyses in different languages, it is possible to perform within-language standardization, i.e., use the mean and standard deviation of the third person singular variable as the reference parameters for rescaling the values. As the authors state, when comparing the four LIWC language adaptations (English, Dutch, Brazilian Portuguese, and Romanian), the unadjusted calculations show little sign of cross-language equivalence compared to the situation where language specificities are considered, that is, via within-language standardization ( Dudãu and Sava, 2021 ).

Another way to reduce the difficulties of adapting closed-vocabulary methods and subsequent cross-language comparison is to use machine translation. Two basic approaches are the “translated dictionary” approach, and the “translated text” approach. The first one consists of automatic translation of entries (usually word by word) from the original dictionary (e.g., English) into the target language. This creates a new dictionary in the target language, which is used to perform analyses in this particular language (e.g., the Danish version of LIWC) ( Boot et al., 2017 ; Van Wissen and Boot, 2017 ). The second approach consists of translating the analyzed text into the language in which the original method works (e.g., English) and then in performing the analysis with the original method. This approach seems to be effective and straightforward in many ways—it makes the analysis tool accessible to languages for which it has not yet been adapted, and reduces errors associated with the translation process and adaptation of the dictionary into another language. The efficiency of MT systems (e.g., Google Translate) is proving to be very high also in terms of syntax and stylistics and recent studies show that this “translated text” approach outperforms the traditional word-by-word “translated dictionary” approach ( Windsor et al., 2019 ; Araújo et al., 2020 ; Boot, 2021 ), for example, in measures of equivalence of Dutch, German, and Spanish language analyses ( Boot, 2021 ).

Dealing With Methods Based on Machine Learning

Finally, acknowledging where the field is heading, we would like to comment on questions around new technologies in psychological text analysis more generally. The use of artificial intelligence (AI), machine learning (ML), and machine translation (MT) is already closely related to many aspects of text analysis, for example, within open-vocabulary approaches ( Eichstaedt et al., 2020 ). Undoubtedly, modern technologies offer enormous potential based on the performance and sophistication of up-to-date computational systems, but also raise fundamental questions about methods of data processing, their supervision, and interpretation of results ( Mønsted et al., 2018 ; Stachl et al., 2020 ).

The ML and MT methods allow us to expand the spectrum of observed variables and at the same time effectively predict their relationships. However, from the perspective of our paper, their disadvantage is the problematic interpretation of the analytical processes itself, i.e., the so-called black box problem ( Castelvecchi, 2016 ). For example, it is possible to train AI on a large number of texts to effectively recognize the specific characteristics of speakers (and then, e.g., allow the AI to predict them), but it is difficult to get clearer information on what procedures and variables (features) are involved in the process ( Zednik, 2019 ). AI is thus more of a promising method for predicting relationships, rather than a method that provides their explanation and deeper insight ( Yarkoni and Westfall, 2017 ).

It is not within the scope of this article to discuss all aspects of ML/MT utilization; however, we would like to focus on one issue that we consider particularly important in relation to cross-language research and the use of closed-vocabulary analysis in psychology. These are the quality and complexity of the training data, especially in the context of different languages and different types of communication.

Successful use of ML depends to a large extent on the data on which the system is trained, both in terms of quantity and quality ( Ehrlinger et al., 2019 ). Regarding the number of training texts, a general rule of thumb is that more data usually means higher effectiveness of the system ( Baeza-Yates and Liaghat, 2017 ). In terms of data quality, the situation is much less clear. In addition to routine data quality controls (e.g., cleaning dataset from irrelevant texts), the nature of texts should also be considered, especially at the level of the type of communication that is the subject of the ML training ( Smith et al., 2013 ; Modaresi et al., 2016 ; Medvedeva et al., 2017 ; Ott et al., 2018 ). For example, several studies have shown that current electronic communication is dominated by the so-called “electronic/internet discourse” (e-discourse), which takes the form of semi-speech (between speaking and writing) ( Abusa’aleek, 2015 ). This e-discourse has its own features such as unconventional spelling and combinations of visual and textual elements ( Lyddy et al., 2014 ; Pam, 2020 ).

Following this concept, we can assume that if ML is, say, trained primarily on parallel corpora of formal written communication (e.g., press releases or parliament transcripts in two or more languages), its effectiveness for processing (translating) the e-discourse or other more specific communication might be noticeably reduced, and vice versa ( Koehn and Knowles, 2017 ; Søgaard et al., 2018 ). Increased error rates for certain types of text (styles, genres, registers) have been described for systems as complex as Google Translate ( Putri and Havid, 2015 ; Afshin and Alaeddini, 2016 ; Prates et al., 2018 ). These errors mainly concern lexical/discourse errors and style errors (note: lexical errors occur when MT translates words wrongly or does not translate them, discourse errors occur when MT could not recognize the meaning of the word in its context, and style errors occur when the word is inappropriate in a given context). In the 2016 research, error rates (based on comparison with human translation) were quantified at 5.9% for lexical/discourse errors and 8% for style errors ( Afshin and Alaeddini, 2016 ). Higher sensitivity to errors was found in the translation of function words, especially adjectives and adverbs ( Putri and Havid, 2015 ). In addition to these errors, problems referred to as “machine-bias” can arise. A classic example is the case of gender preference in Google Translate, that is, when Google MT exhibited a strong tendency toward male defaults ( Prates et al., 2018 ). Although the issue was quickly handled by Google through (forced) equal representation of gender categories in translation, the underlying problem itself is not resolved that easily, since MT was probably trained on (historical) data in which the male gender is more common, which resulted in the preferred in translation. In these situations, it is therefore necessary to apply methods such as “post-editing,” i.e., the process of making corrections or amendments to automatically generated text (machine translation output) ( Temizöz, 2016 ; Gutiérrez-Artacho et al., 2019 ).

The quality of MT is constantly changing with the ever-increasing training data and the participation of new technologies (e.g., automatic transcription of oral communication). At the same time, the accumulation of data facilitates the representation of more diverse types of communication and language varieties (dialects, sociolects, etc.), which contributes to solving number of problems of traditional closed-vocabulary approaches (MT is based on authentic varieties of language, not on a priori assumptions about their functioning). However, the increase in the amount of training data is not proportional between languages—languages that are used more often in electronic communication (especially English) provide automated systems with much more data than the so-called “low-resource/resource-poor languages” ( Thuy et al., 2018 ). Although it is possible to apply procedures that link datasets of resource-sufficient and resource-poor languages ( Impana and Kallimani, 2017 ), the issue of reduced comparability cannot be overlooked ( Seki, 2021 ). The described situation is a parallel to the previously mentioned problem of disproportionate representation of certain types of communication in the ML dataset. In the application of MT in psychological research, it is therefore necessary to emphasize the need for control and documentation of the ML training process, especially when working with languages that generate fewer texts compared to the world’s most used languages, and when working with types of text that are more distant to original training data.

At the beginning of our article, we stated that we are currently in a “transitional phase of research” within the field of text analysis. After more than 60 years of research on psychological aspects of word use, new technologies and methods are entering this discipline at a rapid rate. Original programs based on simple word counting are being challenged by automated machine learning systems and large-scale “big data” analyses ( Gandomi and Haider, 2015 ) that allow for extensive cross-cultural comparisons. New technologies offer great potential, but the question is when (or whether) they will completely replace traditional techniques. It will also be important to consider to what extent the original methods can support more advanced analyses in terms of their focus, interpretation, and explanation of linguistic phenomena. In this regard, current research raises a number of questions related to the relevance of older studies, considering different language structures in different cultures and contexts of human communication ( Kim et al., 2000 ; Jackson et al., 2019 ; Thompson et al., 2020 ).

In our critical analysis here, we focused on closed-vocabulary approaches, a relatively old method of text analysis. Nevertheless, even today, its contribution needs to be appreciated and its strengths highlighted. We would like to celebrate the ground-breaking research and many quality papers that have been published in this field over the last two decades (for all, see, e.g., Pennebaker et al., 2003 ). Research in Anglophone cultures has provided many excellent tools for text analysis in English, but it has also amplified universalist tendencies to adapt target languages to default methods, instead of adapting these methods to target languages and their specifics (e.g., Bjekić et al., 2014 ; Dudãu and Sava, 2020 ). Given the richness and variety among different languages, many relationships between language and psychological variables are undoubtedly reduced this way ( Kim et al., 2000 ; Wierzbicka, 2013 ; Kučera, 2020 ).

In summary, we can state three basic considerations: (1) To further the science of the psychology of word use, it is necessary to promote close interdisciplinary cooperation, especially with the fields of linguistics, computer science, and cultural psychology. Within that, linguistics can provide a clear taxonomy of language, a background in cross-linguistic research, and useful analytic tools (e.g., MDA for dimensional text description or UD for their morpho-syntactic annotation) ( Biber, 2014 ; de Marneffe et al., 2021 ). (2) If we are looking for relationships between mind, behavior, and language use, it is not possible to overlook the specifics of different languages and cultures. Although studies conducted in English are usually more accessible to both researchers and the public (e.g., given the tools available and the amount of data), it is critical to compare the results with studies in other languages and cultures in order to evaluate the generalizability of relationships and to understand their meaning more deeply ( Kim et al., 2000 ; Wierzbicka, 2013 ). (3) In cross-language psychological research, all present-day methods can be used. However, it is necessary to consider their functionality in different contexts (e.g., define more universal variables and comprehend situational/cultural aspects of communication) ( Biber and Conrad, 2019 ; Cvrček et al., 2020 ), and critically assess their development and use. This consideration also applies to current machine learning systems, in which the possibility of methodological supervision is usually limited (in terms of control of the analysis process) and in which the fundamental condition for their effectiveness is the quality of training data ( Koehn and Knowles, 2017 ; Ott et al., 2018 ). These three points can be related to both new studies and studies already conducted, for which a review of their results could be expected.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Author Contributions

DK: conceptualization, investigation, writing—original draft, and writing—review and editing. MM: conceptualization, supervision, writing—original draft, and writing—review and editing. Both authors contributed to the article and approved the submitted version.

This study was supported by the Fulbright Scholarship Program, Fulbright-Masaryk Scholarship no. 2020-28-11.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : natural language processing, cross-language, culture, closed-vocabulary approaches, LIWC

Citation: Kučera D and Mehl MR (2022) Beyond English: Considering Language and Culture in Psychological Text Analysis. Front. Psychol. 13:819543. doi: 10.3389/fpsyg.2022.819543

Received: 21 November 2021; Accepted: 14 February 2022; Published: 04 March 2022.

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*Correspondence: Dalibor Kučera, [email protected]

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Language and Culture

Language and culture are essential components of human societies and influence the way individuals interact with each other. Language is used to express a person's thoughts, feelings, and attitudes, while culture helps to shape an individual's identity and to build bridges between communities of different backgrounds. Language and culture can have a powerful impact on how people perceive the world and how they interact with one another. Language and culture can also be used as tools for education, communication, and social change. Learning about different languages and cultures can help to foster understanding and respect for diversity, and can bring people from different backgrounds together.

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The Journal of Language and Culture , a biannual publication in the fields of Humanities and Social Sciences, is issued in June and December by the Research Institute for Languages and Cultures of Asia at Mahidol University. Established in 1981, the journal serves as a platform for disseminating scholarly works on language and culture, with a focus on contributing to national development and fostering international collaboration. Additionally, it aims to champion the preservation, development, and revitalization of language and culture.

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Flexibility Stigma Across Europe: How National Contexts can Shift the Extent to which Flexible Workers are Stigmatised

• Original Research
• Open access
• Published: 27 August 2024

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• Heejung Chung   ORCID: orcid.org/0000-0002-6422-6119 1 &
• Hyojin Seo   ORCID: orcid.org/0000-0002-1021-5588 2  

Although flexible working has expanded rapidly, especially during the pandemic, biased views against flexible workers – namely, flexibility stigma - are still prevalent and returning. Flexibility stigma hinders worker’s take up of flexible working arrangements and can make flexible working arrangements result in negative outcomes for worker’s well-being and productivity. This study examines how national cultural and policy contexts shape flexibility stigma levels within a country. We use a multilevel approach using the Eurobarometer dataset of 2018, covering 28 European countries, matched with national level aggregate data on policy and culture. Results show that in countries with a more work-life balance work culture and egalitarian gender norms, we see less prevalence of flexibility stigma. Similarly, in countries with generous family-friendly policies, workers are less likely to have negative perception towards flexible working. Finally, stronger bargaining positions of workers, may it be through stronger union power or through better labour market conditions, helps remove stigmatised views around workers who use flexible working arrangements. This study evidences the importance of contexts that shape views around flexible working, to help us better understand policy changes needed to ensure better flexible working practices.

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1 Introduction

Alongside the increase in workers’ demand for flexible working arrangement (FWA)s that allow workers more control over when and where they work such as flexitime and teleworking, we have seen progress in the legislative developments in the provision of FWAs over the years (Alexander et al., 2021 ; Deloitte, 2018 ). With the technological advancements that allow work to be carried out in a more flexible manner with regards to the location and time, we could have expected a much steeper rise in the use of such FWAs across Europe. However, examining data from the past two decades before the COVID-19 pandemic, we do not see a notable increase in workers access to and use of FWAs (Chung, 2022 ). Scholars have noted that this may be due to the prevailing negative perception against workers who use FWAs, namely, flexibility stigma (Munsch, 2016 ; Williams et al., 2013 ). Flexibility stigma is the idea that workers who use FWAs are less productive, motivated, and committed to their workplace compared to workers who do not work flexibly. Flexible workers subsequently experience negative career outcomes. When such views exist, workers are less likely to (request to) work flexibly regardless of their policy entitlements, as there may be potential negative consequences on their careers and promotion chances (see for evidence, Fernández-Cornejo et al., 2019 ; Kasperska et al., 2024 ; Petts et al., 2022 ; Tanquerel & Santistevan, 2022 ; Thébaud & Pedulla, 2022 ). What is more, biased views against workers using FWAs are a major reason why workers end up working harder and longer when using FWAs, with work encroaching on the private lives of workers (Chung & Van der Horst, 2020 ; Glass & Noonan, 2016 ; Kelliher & Anderson, 2010 ; Lott, 2020 ). This results in negative outcomes for workers’ well-being and gender equality, and in negative consequences for productivity especially in the longer run (Gajendran & Harrison, 2007 ).

Although the rise in homeworking practices during the early phase of the pandemic has reduced biased views against flexible workers to a certain extent (Chung et al., 2020 ), we see that such views still exist and are returning (Li, 2022 ). Evidence gathered in recent years show that flexibility stigma still acts as a barrier for workers in accessing FWAs, furthering inequality patterns in the labour market (Crush, 2022 ; Wyatt et al., 2022 ). In sum, for workers to make better use of FWAs in the post-pandemic labour markets, without incurring negative consequences, we need to find ways to tackle the flexibility stigma.

Stigma against individuals, rather than coming from factual based information, are driven by societal conditions, cultural norms, and institutional policies (Goffman, 1990 ). Similarly, when people hold bias against flexible workers, they are not evidence based. Rather, such views arise due to the normative views around the image of a good or productive worker (Williams et al., 2013 ). As such views are not only shaped by norms around work and gender roles, but also by national family policies and workers’ negotiation power, flexibility stigma is likely to vary across the diverse national context across Europe. This is tested using a multilevel approach and the 2018 Eurobarometer data covering 28 European countries (the then EU member states) which is the most recent data set including measures of flexibility stigma that is cross-nationally comparable. This paper provides not only a better understanding of the potential causes of flexibility stigma, but also evidence for policy actions to be taken when introducing flexible working policies to ensure that flexible working can support both workers and companies.

2 Theoretical Background

2.1 defining flexibility stigma.

Flexibility stigma is defined as the discrimination workers face when using various types of FWAs for family responsibilities (Williams et al., 2013 ). One core reason behind this stigma or discrimination comes from the prevailing ‘standard’ or ‘ideal worker’ norm within a society. In many of our societies, the ideal worker is viewed as a worker who works long hours in the office, prioritises work above everything else in life, without any other obligations outside of work (Acker, 1990 ; Williams, 1999 ). Proximity bias, namely the preferential treatment managers show towards workers that are more visible to managers, also explain why homeworkers can be stigmatised (Bloom et al., 2015 ; Cristea & Leonardi, 2019 ). Thus, not working long hours in the office and not sticking to fixed working hours regime, especially to address caring responsibilities, stigmatises the worker as someone who are not devoted, committed, or productive as other workers (Berdahl et al., 2018 ; Cech & Blair-Loy, 2014 ; Fernández-Cornejo et al., 2019 ). This is despite the evidence that shows that flexible workers are often more productive (for example, Bloom et al., 2015 ; Boltz et al., 2022 ) and more motivated, loyal, and committed than other workers (Gajendran & Harrison, 2007 ; Kelliher & de Menezes, 2019 ).

There are different ways in which the literature operationalises flexibility stigma (Chung, 2020 ). The poor worker stigma entails the negative assumptions workers have towards flexible workers’ work capacity (e.g., Munsch, 2016 ). The negative career consequences dimension of flexibility stigma measures the impact of flexible working on promotions, career prospects, and income trajectories (e.g., Leslie et al., 2012 ; Lott & Chung, 2016 ). In this study, we explore both types of stigma, namely what respondents believe is the general (negative) perception (not only the respondents’ own) towards flexible workers, and the perceived negative career consequences of flexible working (again perceived by the general population, not only that experienced by the worker).

2.2 National Contexts and Stigma

Stigma is shaped by social interactions and structures rather than being embedded in biological characteristics (Goffman, 1990 ), or in our case, objective truths around flexible workers’ true work capacity or motivation. Such views are shaped by social norms around what a good performing, ‘ideal’ worker looks like (Berdahl et al., 2018 ), which is shaped by national institutions. This paper specifically examines the role of national norms around work and gender roles, and national level family policies, labour market institutions, and labour market conditions. It is important to note that these factors have been identified as some of the key factors explaining access and use of flexible working arrangements in previous studies (Chung, 2019 ; den Dulk et al., 2013 ; Wiß, 2017 ).

2.2.1 Cultural Contexts and Stigma

In contexts where the perception of ‘the ideal worker’ is someone who can devote themself to work without other responsibilities outside of work, bias against flexible workers are more likely to occur (Chung & Van der Lippe, 2020 ; Williams et al., 2013 ). The stereotyping of the flexible worker stems from these workers’ deviation from this particular ideal or standard worker norm. Not surprisingly, many of the studies (e.g., Cech & Blair-Loy, 2014 ; Chung, 2020 ; Munsch, 2016 ) that evidence flexibility stigma are from countries (e.g. US or UK) and occupations (e.g. STEM) where such work cultures prevail. However, we know that such cultures do not necessarily exist across all countries, and there are variations. In countries where there is a more balanced notion of work and private life and where workers expect and are expected to have a good work-life balance, having responsibilities outside of work is likely to be seen as the standard (Been et al., 2017 ). In such contexts, using flexible working to meet family and other life demands is less likely to be seen as deviating from the ideal or standard work type, which makes flexible workers less likely to incur any negative career outcomes (see also, Petts et al., 2022 ; van der Lippe & Lippényi, 2020 ). Work centric cultures are therefore expected to increase negative connotations towards flexible workers, which will increase their likelihood of experiencing negative career outcomes.

Workers in work-centric cultures are more likely to perceive/experience flexibility stigma.

Similarly, gender norms also influence how and for whom flexible working is stigmatised and leads to negative career outcomes. Gender norms can shift employers’ and co-workers’ assumptions around men and women’s flexible working. Biased views around women’s flexible working are largely based on the idea that women will prioritise family roles when working flexibly, while men prioritise work (Chung, 2022 ; Chung & Van der Lippe, 2020 ). However, such gendered patterns of flexibility working is more evident in countries where gender roles are more traditional, especially in relation to men’s breadwinning roles and women’s caregiving responsibilities (Kley & Reimer, 2023 ; Kurowska, 2020 ).

In addition, egalitarian gender norms can also help shape the general work cultures of society, shaping the general prevalence of flexibility stigma. Long-hours based ideal worker culture is inevitably linked to masculine work cultures (Acker, 1990 ; Berdahl et al., 2018 ), based on the male-breadwinner female-caregiver model. This is where the male worker can devote themselves only to work without any other responsibilities outside of work, because of all the reproductive work is carried out by the female partner in heterosexual relationships. This is why it is especially in male-dominated occupations long-hours work devotions are expected, and biased views against flexible workers are more prominent (Cech & Blair-Loy, 2014 ; Williams et al., 2013 ). In egalitarian cultures, men and women are expected to take on similar roles in the household – e.g. men are expected to take on as much childcare and housework as women, and women are expected take on as much paid work as men – and all workers, not only women, are expected to (have to) balance work with responsibilities outside of work (Knight & Brinton, 2017 ). In such cultures, we expect the notions of what constitutes as an ‘ideal worker’ to change, to be someone who has demands coming both from work and family (Chung, 2024a ). Accordingly, not only are FWAs more widely available in such countries (Kley & Reimer, 2023 ), biased views against flexible workers are likely to be reduced.

Workers in countries with traditional gender norms are more likely to perceive flexibility stigma.

2.2.2 Institutions and Stigma

Institutional theory argues that institutions, laws, and policies shift the norms and culture in society and change the way individuals and organisations behave (DiMaggio & Powell, 1983 ). In countries with generous family policies, the access to and the use of family-friendly FWAs are likely to be seen as part of the general terms of employment rather than ‘a gift’ that needs to be reciprocated (Been et al., 2017 ; van der Lippe & Lippényi, 2020 ). Capabilities theory also argues that national policies can change the prevalent norms in societies in terms of what are acceptable work-family reconciliation practices for individuals (Hobson & Fahlén, 2009 ). For example, when there are generous ear-marked parental leaves for fathers, fathers are able to take a larger role in childcare and housework without being stigmatised for deviating away from the ‘masculine’ image (Petts et al., 2022 ). Similarly, generous family policies at the national-level – such as childcare policies or leaves – can shape cultural norms around work-life balance and shift the notion of the ‘ideal worker’ to assume a good work-life balance as the norm for both men and women (see also, Bünning & Hipp, 2022 ; Chung, 2024a ). This can help reduce negative views against those who use flexible working for care purposes and reduce the likelihood they experience negative career outcomes.

What is more, generous family policies can shape employer’s perception of how workers will use flexible working for care purposes. When work facilitating policies (Misra et al., 2011 ) such as childcare provision are not available, parents may have no other option but to use flexible working arrangements to meet family demands whilst working (Chung & Van der Horst, 2018 ). In such contexts, employers may be more suspicious about workers’ flexible working – expecting a blurring of or encroachment of family life into working time/space when workers work flexibly (e.g. caring for children when working from home). On the other hand, when generous policies exists, for example cheap accessible public childcare, workers may be better able to manage their work-family boundaries better when working flexibly (Kossek et al., 2006 ). This will allow workers to better focus on work even when working flexibly (e.g. children in childcare when worker works from home). This may change the perceptions around flexible workers and their work capacities when working flexibly reducing bias against them, and subsequently reducing the likelihood of experiencing negative career outcomes.

Workers in countries with generous family policies are less likely to perceive flexibility stigma.

2.2.3 Workers’ Bargaining Power and Stigma

Worker’s bargaining power can be an important factor explaining the extent to which FWAs lead to negative career outcomes. According to the power resource theory, strong trade unions can protect not only the workers in their own trade union or company, but also ensure the strong protection of workers in general by providing “contagion from the left“(Korpi, 1989 ). This includes supporting workers taking up FWAs and enabling them to be better protected from any potential discrimination, which further supports policy take up (Budd & Mumford, 2004 ). Similarly, we expect that in countries where stronger unions are present, negative views against flexible workers to be less present, largely by normalising the use of FWAs or other types of family-friendly arrangements (Lyness et al., 2012 ). Studies have shown that unions influence worker’s bargaining power by shaping national-level policies and levelling-up the general working conditions of workers in general, ensuring the development of family-friendly working condition (Berg et al., 2004 ), or stopping the retrenchment of FWAs (Jacobi, 2023 ) at both company and national levels. This explains why stigma against flexible working is expected to be weaker in such countries. However, in this case, we expect that union power would be more relevant in protecting workers from negative career outcomes rather than reducing the bias against flexible workers more directly.

Workers in countries with strong unions are less likely to perceive flexibility stigma.

One last yet important context factor for consideration is the labour market conditions of the country. Attitudes around work and work-life balance changes due to labour market and economic conditions, largely due to the changes in workers’ individual and collective bargaining power and along with it different levels of competition amongst workers for jobs (Lyness et al., 2012 ). When there is greater supply of labour than demand, namely high unemployment, workers will have weaker negotiation power over employers, and higher competitions among workers for jobs. Under such conditions, it is more likely that workers are asked to put work first, and prioritise work above all else (see also, Schor, 2008 ) leaving little space for the use of FWAs especially for care purposes. Under these circumstances, biased views against workers who use FWAs for work-life balance purposes will be more commonplace. On the other hand, when demand for workers outstrips supply, i.e., low unemployment rates, workers may have more power to demand better work-life balance from their employers (den Dulk et al., 2013 ). What is more, when there is greater demand than supply of workers, employers may use family-friendly flexible working arrangements as incentives to help recruit and retain workers (Batt & Valcour, 2003 ). Flexible working, even for care purposes, is less likely to be viewed with negative connotations under such contexts. Similarly, flexible working is less likely to lead to negative career outcomes, as employers are more likely to support worker’s work-life balance demands when there is a labour shortage.

Workers in countries with high unemployment rates are more likely to perceive flexibility stigma.

2.3 Variation Across Gender

Women’s views around the prevalence of flexibility stigma may be influenced more by national contexts than that of men. Some scholars argue that women are more likely to be stigmatised when taking up flexible working arrangements (Chung, 2020 ; Munsch, 2016 ). This is partly due to the gendered outcomes of FWAs where women end up doing more domestic work when working flexibly whereas men do more paid work (Kim, 2020 ; Wang & Cheng, 2023 ). What is more, women’s relative bargaining position is weaker both at home and in the labour market, and usually are penalised more in the labour market (Jones et al., 2023 ). Thus, women may be more sensitive to contextual changes when it comes to flexibility stigma perception. For example, previous studies have evidenced how women’s employment patterns are shaped by national institutions such as family policies more than that of men’s (Korpi et al., 2013 ) and company contexts influence women’s flexible working outcomes than that of men’s (e.g., van der Lippe & Lippényi, 2020 ).

Other scholars argue that men are more likely to be the bearers of biased views against flexible working (Chung, 2020 ; Munsch, 2016 ; Thébaud & Pedulla, 2022 ), because they are more likely to (be able to) adhere to the work devotion culture of a company (Berdahl et al., 2018 ; Blair-Loy, 2009 ). However, when men take up FWAs they may experience stronger stigma, as men’s, especially father’s FWA use for family purposes, makes them deviate away from both the male-breadwinner image and the ideal worker image (Rudman & Mescher, 2013 ). This is why we can also expect that men’s perception around flexibility stigma may be influenced more by its embedded contexts.

Summing up, we do not set concrete hypotheses on the direction of the association but expect that there will be gender variations in the way contexts influence worker’s perception.

3 Data/Methods

This paper uses the data from the Eurobarometer survey on work-life balance (European Commission, 2018 ), which was conducted in June-July 2018 by TNS Political & Social (at the request of European Commission) via telephone. This dataset was chosen as it is one of the few if not the only available dataset that captures workers’ attitudes towards flexible working that is comparable across a wide range of countries. It covers 28 European countries, including EU member states and the UK. The total sample size is 26,582, but we restrict the analysis to those who are currently employed and working in a company that uses any type of FWAs Footnote 1 . Here FWAs include part-time, flexitime (adapted beginning and finishing working times), working from home (telework) or being able to take some time off for private emergencies (medical issues, a sick child, etc.). This includes a total of 69% of all employed workers. Having checked for cross-national variance in the proportion of workers that are excluded, we did not find a large variance (Appendix C). However, we understand that biased views against flexible workers may be underrepresented in countries with lower proportion of workers included in the analysis. This is because previous studies (Kasperska et al., 2024 ; Munsch et al., 2014 ; van der Lippe & Lippényi, 2020 ) indicate that the more experience people have towards flexible working, and the more flexible working is widespread, it is less likely to be met with stigma. In this sense we may be under-estimating the stigma levels in countries where fewer respondents are working in environments where flexible working is present, and not present in the data set. Given that many of the context variables that explain the levels of flexibility stigma across countries also explain workers’ access to flexible working, what we can expect is that importance of context may be even greater than what we find in this paper. We further remove all cases where there were any missing responses in the variable used for this study, leaving us with a total of 6,319 cases across the 28 countries. For more details about the sample reduction, see Appendix B. For more information about the data see: https://europa.eu/eurobarometer/surveys/detail/2185 .

3.2 Dependent Variable: Flexibility Stigma

The Eurobarometer includes two variables that measure flexibility stigma, specifically measuring how respondents think flexible workers are negatively viewed (by others) and the subsequent career consequence. Note that the question does not measure the respondents’ own negative stereotypes against flexible workers. Respondents were asked “regardless of if you personally used, or not, these flexible work arrangements in the company or organisation where you currently work (or last worked), please tell me to what extent you agree or disagree with the following statements about the way these arrangements are perceived.” “(Flexible working) is/was badly perceived by colleagues” and “(flexible working) has/had a negative impact on one’s career (i.e., promotion, bonus, type of work allocated etc.)”. Respondents can choose between totally disagree, tend to disagree, tend to agree, or totally agree. All variables are coded so higher score entails stronger stigma against flexible workers. As the correlation between the two variables is only at 0.4 (significant at 0.001 level), we look at the two variables separately, and as dichotomous variables due to the skewness of the response. Those who totally agree and tend to agree are coded as 1, the rest as 0. However, as a robustness check we also examine the variables as ordinal variables (see Appendix Table G).

3.3 Independent Variables: National Contexts

There are various ways in which we can measure the extent to which a society is an ideal worker/long-hours work culture. One way is to look at the average working hours of full-time workers (Schor, 2008 ) which can indicate the extent to which long-hours work is expected in the country. This is derived from the EUROSTAT 2018 data. Other studies use work-centrality attitudes of the country (den Dulk et al., 2013 ). Work centrality is the national average factor score based on five variables measuring how central work is to individuals’ lives measured through questions such as “Work should always come first, even if it means less spare time”. Gender norms are measured by the national average of factor scores of one factor consisting of four items measuring gender role attitudes of individuals, including questions such as “When a mother works for pay, the children suffer”. We use the 2017 European Value Study survey to capture work-centrality and gender norms of the country. Although a year lagged, this was the closest year data available that covered majority of the countries included in our data. For detailed list of variables used and the factor analysis results please see Appendix A.

This paper focuses on three different aspects of family policies to examine how they impact perceptions toward flexible working. Firstly, general generosity of family policies is measured through public expenditure on family policies as a % of GDP. Secondly, we include a measure indicating the generosity of work-facilitating policies (Misra et al., 2011 ), as it was found to be key in explaining access to (family-friendly) flexible working policies (see also, Chung, 2019 ; den Dulk et al., 2013 ; Lyness et al., 2012 ). More specifically, we use the proportion of children using formal childcare for age group 0–2 years. Both data comes from Eurostat and is from 2015, as we can expect a lagged effect of policy on individual’s attitudes. Thirdly, we include paternity leave as a separate family policy variable as previous studies have shown how such policies can change the gender norms around whose responsibility it is to care (Hobson & Fahlén, 2009 ) and with it, stigmatisation of policy use (Petts et al., 2022 ). Paternity leave is measured as the length of paid paternity, parental and home care leave available to fathers for the year 2015 and is derived from the OECD Family Database. Note that models including paternity leave do not include all countries due to the availability of data. Union density and collective bargaining coverage rates (as a percentage of wage earners) are used to measure workers’ bargaining power. Both variables are from the ICTWSS data set 5.1 for the year 2018 or the closest year available. Finally, labour market condition is measured through the unemployment rates for the year 2018 derived from EUROSTAT. All context variables have been centred and standardised in the model, allowing us to compare the coefficient sizes. For more details on the operationalisation and descriptive analysis of the data please see the Appendix A and B.

3.4 Control Variables/Individual Level

Based on previous studies (e.g., Cech & Blair-Loy, 2014 ; Chung, 2020 ), we include the following variables as control variables: age is used as a categorical variable 15–24 (reference group), 25–34, 35–44, 45–54, 55–64, 65 + as we expect a non-linear relationship; gender (female reference); education is included as binary variable with 0 referring to “upper secondary or below” and 1 “tertiary or above”; care responsibility is measured into four categories, namely, no caring responsibility (reference) caring for children under 3, children between the ages 3–6, children between the ages 7–14, and other caring responsibilities (e.g., elderly or disabled household members); and a binary variable indicating whether the respondents’ place of residence, where they live in a city (reference) or a rural area. For work characteristics we include working hours of workers distinguishing between full-time (reference) and part-time workers (self-defined) and include occupation as categorical variables using the Eurobarometer definition. More detailed notes on the construction of variables along with the descriptive statistics of the variables used in this paper can be found in Appendix A and B. Although there may be other factors that can contribute to explaining our dependent variables, we have restricted the number of controls due to availability of appropriate variables in the dataset (e.g. sector) and the sample size of the data.

Two-level random intercept multilevel multivariate regression models are conducted to examine how national contexts are associated with flexibility stigma (see Hox, 2002 ). Multilevel modelling assumes that the lower-level sample (i.e. individuals in this paper) is subject to the influences of groupings (i.e. countries). Thus, it is useful to examine how the national contexts influence the perception of individual workers on flexible working. We first examine the cross-national variations in the flexibility stigma, including all individual-level variables. We include each national context variables one at a time in each model to examine how different national contexts derived from the theories discussed in Sect.  3 can explain such variations. We also test context factors against each other by including two national-level variables at a time, which is the maximum number we can include in our model given the small number of country cases we have in the data set (Stegmueller, 2013 ). As we expected that national contexts may shape workers’ perceptions for men and women differently, we run the analysis separately for men and women to examine gender differences. As a robustness check, an interaction term with gender and country context variables with gender random slopes are used to statistically test for the gender variation in the association between country contexts and flexibility stigma levels. As a final robustness check we examine the variable as ordinal rather than dichotomous variables. We use the meqrlogit, meologit function of STATA 15.1 for all models.

4.1 Descriptive Results

Firstly, as we can see in the Figs.  1 and 2 , about 1/3 of European individuals in the survey in 2018 thought that flexible working was viewed negatively or that it leads to negative career outcomes. There are large cross-national variations. In the Nordic welfare states, such as Sweden, Finland, Denmark and Estonia, not many hold stigmatised views against flexible workers and respondents are less likely to feel that FWAs lead to negative career outcomes. On the other hand, in many Southern European countries, like Greece, Cyprus, Romania, and Spain, and liberal countries like Ireland and the UK, stigma against flexible workers are more prevalent. There are some differences depending on the type of stigma we explored again showing the need to examine these two separately.

Flexibility Stigma 1 (flexible working is badly perceived by colleagues) across Europe (% of workers who totally agree or tend to agree)

Flexibility Stigma 2 (flexible working has/had a negative impact on one’s career) across Europe (% of workers who totally agree or tend to agree)

4.2 Multivariate Results

Examining the empty model (available upon request), the interclass correlation for the perception that colleagues view flexible working negatively (Stigma1) has 5.7% of its variance at the country level (men 6.0%, women 5.7%), and for the perception that flexible working results in negative career outcomes (Stigma 2), it is 8.1% (men 7.9% and women 7.7%). Although this is not a large variance attributed at the country level, this is not uncommon in multilevel models where countries are set as 2nd levels (Bryan & Jenkins, 2016 ). What is more, as we will see in the later section, country contexts significantly explain large parts of the variance allowing us to better understand how best to tackle such biases against flexible workers.

Table  1 explores the individual level characteristics that can explain the variance across European individuals in their perceptions that flexibility stigma exists in their societies. Women are more likely to think that flexible workers are viewed negatively, both in terms of colleagues’ perception and expected career outcomes. This mirrors previous studies (e.g., Cech & Blair-Loy, 2014 ; Chung, 2020 ; Munsch, 2016 ) that have shown that although men may be more likely to hold negative biases against flexible workers, women are more likely to fear (or have directly experienced) negative career outcomes. Variation across age groups is found in people’s perception of how flexible working can be perceived negatively by colleagues, but not of flexible working leading to negative career outcomes. Younger workers (15–24 and 25–34) are less likely to think flexible working is negatively viewed. In closer inspection (3rd column), we find that among women, young workers (15–24) are less likely than all other age groups to think this way. Somewhat opposite tendency was found among men where younger workers (15–24) are more likely than some older age groups (25–34, 35–44, 45–54) to think that flexible working will negatively impact their career outcomes. Those who have higher education are less likely to perceive flexibility stigma, whereas manual workers are more likely to perceive it. Those with caring responsibility for young children (under the age of 3) are more likely to say that flexibility stigma exists. This result is largely driven by the mothers in our study. Mothers of very young children (< 3) and women with other care responsibilities are more likely to believe that colleagues hold negative views against flexible workers, compared to women without children or other care responsibilities. Mothers with children between ages 7–14 and women with other care responsibilities are more likely to say that careers can be negatively impacted by flexible working than women without care responsibilities. For men, fathers with children age under 3 are somewhat more likely ( p  < 0.1) to think flexibility stigma exists in terms of negative career outcomes, than those without care responsibilities, but the opposite was found for fathers with children between ages 7–14 ( p  < 0.1). This confirms the idea that those who may have responsibilities outside of work, who may have already experienced negative bias against their own work capacity and motivation, can be more cautious about the potential impact of working flexibly (Chung, 2020 ; Munsch, 2016 ). Somewhat opposite results were found between the two flexibility stigma perceptions when comparing those who work part-time and full-time. Part-time workers are less likely to think that colleagues perceive flexible working negatively, while they are more likely to think that their career outcomes would be negatively impacted. These perceptions can be based on their actual experience of working part-time, which is considered working flexibly in the survey. These patterns are largely driven by women.

4.3 Explaining Cross-National Variance

Table  2 presents the results of the assotiation between national-level context variables and respondents’ perceptions of flexibility stigma. Note that each context variables are included one at a time in the model. We find that many factors explored in this paper help to explain the cross-national variance in how respondents feel that flexible working is negatively viewed by colleagues. Whereas these contexts do little to explain the cross-national variation in the perception around how flexible working can result in negative career outcomes. More specifically, in countries with ideal/long-hours work cultures – as measured by the average hours worked by full-time workers and work centrality norms – workers are more likely to say that flexible working is badly perceived by colleagues. On the other hand, countries with egalitarian gender norms, and where national family policies are more generous and childcare coverage is wide, workers are less likely to think the same way. Similarly, in countries where unions are strong – higher union density and collective bargaining coverage, and workers have more bargaining power – low unemployment rate – workers are less likely to say that flexible working is badly perceived by colleagues. These associations are true for both men and women.However, for women, the significant levels of some these variables (childcare, family policy expenditure and collective bargaining coverage) are at the  p  < 0.10 levels or lower.

We’ve also examined how the significance of the variables changes when context variables are included two at a time (Appendix Table E-1). We found that compared to some policy and institutional variables (childcare coverage, union density, collective bargaining coverage) and even unemployment rate, gender and work cultural norms seem to be more robust in explaining the level of stigma, pertaining to how colleagues perceive flexible working negatively. This can be due to, on the one hand, because stigma is influenced more by norms and cultures than institutions. However, on the other hand, as we’ve mentioned in the theoretical section, it may be because policies and institutions influence flexibility stigma more indirectly via changing cultural norms (see also, Chung, 2024b ). In fact, we see how cultural norms and some of our institutional variables have high correlations (Appendix H). In other words, our cultural norms variables may be mediating the influence of the institutional variables on flexibility stigma.

When explaining the cross-national variance of the perception on flexible working leading to negative career outcomes, we find that in countries where there are generous family policies (as measured here as expenditure data), men are less likely to believe this to be the case but only at a p  < 0.10 level. It is insignificant for the female sample. The unemployment rate is the only significant factor explaining the cross-national variance in the perception of flexible working leading to negative career outcomes – namely in countries with high unemployment rates, respondents are more likely to say that flexible working leads to negative career outcomes. In Appendix Table E-2, we also examined what happens when two context variables are included in the model at the same time. What we found was that family policy becomes more significant in its association once work and gender norm, childcare coverage, or collective bargaining coverage is controlled for. This indicates that there may be potential influence of institutions but only in certain contexts. Further investigation is needed to confirm this.

As a robustness check, we examine the models using a cross-level interaction term between gender and the context variable to see how the contexts have significantly different impact for men and women (Appendix F). The results show that the negative association between family policy expenditure and flexibility stigma levels is stronger for men (interaction coefficient − 0.144 p  < 0.05). This entails that it is especially men’s views around flexibility stigma that may be influenced more by generous family policy contexts. There were no clear gender variations in the association between other context variables and flexibility stigma, indicating policies and norms may influence both men and women’s perceptions equally. Finally, we conducted ordinal analyses to check if results vary when we consider our dependent variable as an ordinal rather than a dichotomous variable (see Appendix G). Results are consistent for the main models with Table  2 in terms of the significance and the direction of relationships, but with few models showing stronger associations (see highlighted results in Appendix G). In other words, the choice of operationalisation of flexibility stigma did not have influence our general conclusions.

5 Discussion and Conclusion

Flexibility stigma prohibits workers from making use of existing policies (Petts et al., 2022 ; Williams et al., 2013 ), this may especially be true for certain groups of workers, such as fathers (Fernández-Cornejo et al., 2019 ; Kelland et al., 2022 ). This in turn can further exacerbate gender inequality patterns in the labour market as flexible working becomes a ‘women’s arrangement’ (Chung, 2024a ), resulting in negative career outcomes for workers -  both men and women (Chung et al., 2021 , 2022 ; Chung & Van der Lippe, 2020 ). Flexibility stigma is also a major factor explaining why flexible working sometimes results in unintended negative outcomes such as overwork, blurring of boundaries, and work encroaching on private life (Chung, 2022 ; Kelliher & Anderson, 2010 ). This leads to bad well-being and work-life balance outcomes for workers, negative outcomes for companies with regards to productivity, and can even be costly for society especially in the longer-run (Gajendran & Harrison, 2007 ; Kelliher & Anderson, 2010 ; Thébaud & Pedulla, 2022 ). The goal of this paper was to better understand the cultural and institutional contexts that enable such biased views to exist, which help us find policy solutions to tackle these issues.

The results of the paper evidence that cultural norms matter and are perhaps some of the most important factors explaining the levels of flexibility stigma perceived in a country. Long-hours work centric cultures and traditional gender norms may be a good breeding ground for biased views against FWAs use. However, we also found that well planned out national-level interventions can tackle this. Ensuring a more family-friendly policy environment through the introduction of more generous family policies such as public childcare services can help tackle flexibility stigma (Petts et al., 2022 ). Providing generous family policies at the national-level can help change norms around work-life balance, where rather than being a work-centric society, a good work-life balance becomes a norm for all workers, and make gender norms become more egalitarian (Been et al., 2017 ; den Dulk et al., 2013 ). In such scenarios, biased views against flexible working are likely to be reduced. Similarly, providing workers with more bargaining power, whether it be through stronger union bargaining power or due to shifts in labour market conditions being preferable, could potentially shift work and gender norms, which helps workers feel less stigmatised when taking up FWAs.

Although our analysis was conducted at the national-level, we can expect similar conclusions at the company-level. In other words, companies that want to encourage the take-up of FWAs and ensure that workers do not fear the negative consequences from it, may want to or need to introduce a wider range of other policy interventions concurrently (Kelly et al., 2014 ). This includes policies that encourage the development of a more family-friendly culture, or providing workers with better protection when taking up flexible working arrangements, or changing the notion of flexible working not only as a work-life balance measure but also as a performance enhancing arrangement (Wood & De Menezes, 2010 ). Deliberate change in work cultures to eliminate the long-hours ideal worker culture is also needed, may it be through setting new indices to measure productivity and commitment, or new key performance indicators and targets for individuals, groups, and the company so to move away from the long-hours, always-on culture (Perlow, 2012 ). Changes in gender norms through policies such as ear-marked parental leave for fathers could be of benefit as well. Such policies can also be useful in changing the notion of the standard worker, so all workers are expected to have work-life integration demands. 

There are some limitations to this study. The results of this study show that the contexts observed in this paper better explain the cross-national variance of workers’ views on how colleagues perceive flexible working negatively rather than views around how flexible working results in negative career outcomes. With regards to the latter perception, there may be other contexts that are more useful in explaining the variations. Future studies should examine this in greater detail. Given the cross-sectional nature of our data, we cannot guarantee the direction of the relationships. For example, although the associations exist, changing national contexts may not necessarily mean that there will be a change in the stigma perceptions of workers. More data needs to be collected measuring flexibility stigma cross-nationally, or across different contexts, possibly through longitudinal surveys or field/survey experiments to help us untangle the causality of the directions. Some studies already exist (Kasperska et al., 2024 ; Kelly et al., 2014 ) providing some supporting evidence. As the data used for this paper was collected before the pandemic, the question arises whether results of the findings are applicable in the ‘post-pandemic’ labour markets. Although we did see a decrease in the biased views against flexible workers during the peak of the pandemic (e.g.Forbes et al., 2020 ), we are increasingly seeing biased views around flexible working re-emerge. What is more, evidence gathered during the pandemic (e.g., Chung et al., 2022 ; Dunatchik et al., 2021 ; Lyttelton et al., 2022 ) shows that many of the negative outcomes of flexible working observed during the pre-pandemic times largely remained the same. This was because the important contextual factors, such as work and gender culture, national institutions, have not changed much during this period. Based on this, we expect that much of what we find in this paper, even though we use data from pre-pandemic times, is likely to be applicable to the ‘post-pandemic’ labour markets into the future.

Despite abundance of evidence from both before (Bloom et al., 2015 ; Boltz et al., 2022 ) and during the pandemic (Awada et al., 2021 ; CIPD, 2021 ; Etheridge et al., 2020 ; Farooq & Sultana, 2022 ; Forbes et al., 2020 ; Nikita et al., 2024 ) showing how flexible working can enhance rather than reduce productivity, biased views against flexible workers’ work capacities are still prevalent. This explains why many managers are increasingly asking workers to return back into office (Sasso, 2023 ). This paper provides evidence to show that although these biased views against flexible working exist, they are not inevitable, and we can actively work to change the context in which flexible working is used to challenge these views. More specifically, we can do this by removing long-hours work culture, ensuring work-life balance and gender egalitarianism as the norm, providing more generous family policies, and providing more workers more security and protecting their bargaining power. By doing so, we can enable a better use of flexible working practices that can benefit both workers and companies, and consequently society as a whole.

Data Availability

The data used for this paper is available to the public via GESIS data archive. See: https://www.gesis.org/en/eurobarometer-data-service/search-data-access/data-access .

The survey assumes that you needed to have some exposure to flexible working/workers to be able to answer these questions, even if you yourself do not have access to it directly. Employees includes those who answered to be employees or manual workers, therefore excluding the self-employed and those without professional status (namely, inactive).

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This project was made possible partly due to the ESRC Future Research Leaders funding (Grant ES/K009699/1), the European Commission H2020 initiative funding (HORIZON-CL2-2021-TRANSFORMATIONS-01-02) for the project TransEuroWorks, and the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2023S1A5A2A03083567)”.

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Chung, H., Seo, H. Flexibility Stigma Across Europe: How National Contexts can Shift the Extent to which Flexible Workers are Stigmatised. Soc Indic Res (2024). https://doi.org/10.1007/s11205-024-03420-w

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The venda-speaking people.

• Jannie Loubser Jannie Loubser Stratum Unlimited
• https://doi.org/10.1093/acrefore/9780190277734.013.1215
• Published online: 21 August 2024

Although not a culturally homogeneous or politically united nation, Venda-speaking communities across the Soutpansberg share certain traits that set them apart from neighboring Bantu-speaking groups. These include their distinctive language, the sacred status of their ruling families, bilateral kin groups among the elite, prominent females in the society, widely respected rainmakers, and varying burial modes. The development of these traits can be traced back to the emergence of a class-based social formation at Mapungubwe Hill, overlooking a fertile alluvial setting south of the Shashi–Limpopo confluence. During a relatively brief period, 1220–1310 ce , Mapungubwe’s control over the production and export of gold and ivory with the Indian Ocean coast in exchange for glass beads and cloth from Asia facilitated an unprecedented accumulation of economic wealth in the form of cattle, political power in the form of bilateral marriage practices, and privileged access to potent ancestral spirits by an elite residing behind stone walls on the hill. Knowing that Mapungubwe ceramics are ancestral Shona, the persistence of smaller Mapungubwe sites farther to the east and south along the Soutpansberg range until around the mid-14th century is indicative of a Soutpansberg stratum of Shona speakers surviving the collapse of the polity at Mapungubwe Hill.

Moloko ceramics associated with Sotho speakers started appearing south and west of the mountains at the tail end of the Mapungubwe period. A century later, around 1450 ce , Khami-period ceramics associated with Shona dynasties from Zimbabwe appeared along with elite coursed stone-walled settlements north of the Soutpansberg. A few Khami sherds also occur on sites with central cattle pens that are dominated by Moloko ceramics south of the mountains. The movement of Moloko ceramics to elite Khami sites is indicative of Sotho women marrying into elite Shona families.

Intermarriage between Sotho and Shona speakers across the mountains resulted in the merger of Moloko and Khami ceramic styles around 1500 ce . This interaction created a new, widespread, but short-lived ceramic style known as Tavhatshena. By 1550 ce , Tavhatshena had evolved into Letaba ceramics, a style still made by Venda-speaking potters in the early 21st century. Certain Singo oral traditions mention that the Venda language was already spoken when they first arrived in the Soutpansberg.

By the time the Singo arrived in the central Soutpansberg from Zimbabwe in the late 17th century, Venda had already been spoken for at least a century. Also, long-distance trade in prestige goods with the east coast continued to be conducted from the elite Khami period centers north of the mountains prior to the Singo’s arrival. The Singo managed to subjugate various Venda and Sotho polities in the Soutpansberg and beyond, creating a more or less unified trading state that fragmented into three major divisions in the late 18th century.

The western Ramabulana Singo division under Makhado resisted Boer attempts to wrest ivory trade and tribute payments away from its traditional control, marked by a series of conflicts, terminating in Boers abandoning Schoemansdal in 1867. The remainder of the 19th century witnessed conflicts between various Venda dynasties. Following the Boer defeat of the western Singo by the end of the 19th century, the western Singo moved to the central Soutpansberg in the early 20th century. Because the western Singo remained the dominant political group among the various Venda mitupo during the 20th century, their history eclipsed the histories of earlier Venda groups.

• Soutpansberg
• agropastoralists
• long-distance trade
• political-economy
• ethnic interaction

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‘Bengaluru is more accepting of varied food cultures’ Premium

Kalyan nagar, a relatively new neighbourhood, is home to not only people from the northeast, but also nepal, nigeria and bhutan, says prithiraj borah, who studies food culture and identity.

Updated - August 28, 2024 10:11 am IST

Published - August 28, 2024 09:00 am IST - Bengaluru

Bhut jolokia chili and dried fish. | Photo Credit: Prithiraj Borah

Prithiraj Borah remembers experiencing food-based discrimination firsthand in the summer of 2018 while working on his Ph.D. Borah, who was studying at the Indian Institute of Technology (IIT) Bombay back then, had travelled to Delhi for research and was invited to the home of some friends who lived in Munirka, South Delhi, near the Jawaharlal Nehru University campus.

“We were making something with akhuni (a fermented soybean product commonly used in Naga cuisine) when a neighbour knocked at the door and said that you cannot cook this here,” says the Vellore-based researcher and scholar. 

Prithiraj Borah | Photo Credit: SPECIAL ARRANGEMENT

It got him thinking about how people of “mainstream” India often had prejudices against food consumption, particularly from the Northeast, leading him to start reading and reflecting on the issue. But then the pressing demands of his Ph.D. took over, and he could not take the idea further, he says. Then, in February 2023, he moved to Vellore, Tamil Nadu, to teach at the Department of Social Sciences and Languages at the Vellore Institute of Technology. Since he had a friend in Bengaluru, 200-odd-km away, he decided to visit the city two months after shifting to Vellore. 

That was when he first encountered Kalyan Nagar, where his friend was staying, and discovered the many shops and restaurants selling food catering specifically to the Northeastern community. “Kalyan Nagar is a relatively new neighbourhood, and many migrants stay here,” says Borah, pointing out that the area is home to not only people from the Northeast but also Nepal, Nigeria and Bhutan. “Some of them are working as chowkidars or delivering food for Zomato, Swiggy or Dunzo. There are also people working in corporations, teaching at the university, even students,” he says. 

The neighbourhood’s incredible diversity, which, in turn, had led to the mushrooming of businesses catering to this massive influx of people from the Seven Sisters, got him thinking again about food and identity. “I wanted to look at this aspect of food and belonging in Kalyan Nagar,” he says.

Food and identity

In August last year, Borah applied to the India Foundation for the Arts (IFA) Project 560, an initiative that supports projects that engage with Bengaluru in different ways. He submitted his proposal to “examine notions of ‘belongingness’ and ‘neighbourhood’ through an understanding of food habits of the ‘indigenous’ and ‘tribal’ communities from the northeast in Kalyan Nagar,” as the IFA website puts it, and was eventually selected. 

According to the IFA website, the project fits the mandate of the Project 560 programme since it interrogates ideas around migration, labour, identity and belongingness in the microcosm of a neighbourhood, thereby enabling a layered understanding of the city. “Food becomes an important reason for people from various communities across the northeast to come together and feel a sense of camaraderie and belonging while they stay in Bangalore, far away from their homes,” it states.

“There is no single northeast culture and much food diversity,” says Borah. | Photo Credit: Prithiraj Borah

Borah began his fieldwork in February this year, travelling to Bengaluru from Vellore every weekend to explore the food culture of Kalyan Nagar. As someone with a sociology background, he took an ethnographic approach towards the project, something he has been doing since his master’s, which he completed at IIT Guwahati. He began identifying and visiting shops run for and by the northeastern community that supplied food and ingredients specific to the community’s culture.

He adds, however, that he was mindful of the many differences between the various tribes who inhabit the northeastern part of India. “As I wrote in my proposal, I did not want to homogenise any culture, identity or religion,” he says. “There is no single northeast culture and much food diversity.” 

Photo stories

A map of Kalyan Nagar is splayed across a soft board in Bangalore’s Creative Space, an art and performance venue located in Kalyan Nagar’s HRBR Layout. Several photographs depicting the signboards of these various shops, such as Victoria’s Kitchen, North East Shop and Seven Sisters, are tacked onto this map, while long lines of other photographs, offering viewers a glimpse of these stores’ offerings, cascade over the mirrored walls of the space. In another corner of the room are a couple of stores selling goods from the Northeast: packaged snacks, dried fish, coffee and more. 

We are at Food, Belongingness and Neighbourhood , a photo exhibition capturing narratives around northeast food in Kalyan Nagar, one of the key outcomes of this project. He says some of the other outcomes are likely to become part of a short video documenting northeast food stalls in that neighbourhood, a few oped articles about the experience, and a final report about this project. 

Borah, who is not a trained photographer, taught himself to handle a camera specifically for the project, spending hours lingering around the stores trying to document them visually.  At first, he visited these shops — buying various items and striking conversations with the people who ran them. “I would click random pictures of them cooking, showing only their hands and feet, avoiding their face,” he says. “Slowly, I built a rapport with them,” he says.

Once the people Borah was interviewing became comfortable with him, they began allowing him to roam around their kitchen to take photographs and gave him more detailed interviews; one even invited me to her church one day, he says. These spaces often became a place for conversation, whether about discussing personal problems or exchanging opinions on history, politics or philosophy. “It is also an open discussion space for the community,” he says. 

Insights and observations

Borah, an Assamese, also talks about being made fun of by the people he interviewed. “People often don’t like Assam because it is a caste-Hindu society that often discriminates against tribal people,” he says, recalling how when he went to buy Singju (a spicy Northeastern snack with Manipuri origins), people would say, “Oh, you Assamese people eat Singju too,” he says. 

As both an insider and an outsider to the larger northeast community, he approached it as such, questioning the fixed binaries between the two while doing his ethnographic research. “This insider-outsider debate always exists in ethnography,” he says. While his caste and community affiliations did make him an outsider, things evolved over the course of his research, he says. “Maybe I was different from what they were expecting,” he believes. “I am not going to say that I became an insider, but I managed to work as both,” says Borah, who attempted to question the fixed binaries of ‘insider’ and ‘outsider’ through this project. 

He shares some of the other insights he gleaned from his ethnographic research. For instance, he noticed that the Tangkhul Naga community was the most dominant community here, much like in Mumbai or Delhi. ‘They have a stronghold in any city,”  he believes. Another thing he observed was that women ran the majority of these shops. Since many of these tribes were matriarchal or matrilineal, women of the northeast were often more autonomous and independent, he says. And yet, “it is a two-sided coin, though, since it also means the burden on them increases.”

From his conversations with proprietors, Borah also discovered that running a business in Bengaluru is challenging since the northeast is not so well connected to this city. Unlike in Delhi, where there are direct flights from Dimapur, Kohima or Imphal, people often need to take a connecting flight to get to Bengaluru, he says. “The airport is also so far away. You need to struggle so much to get those foods,” he says.

On the positive side, however, he believes Bengaluru, unlike Delhi, is more accepting of varied food cultures. “Even if you are cooking pork, dry fish or bamboo shoots, people will not come and disturb you,” he says. “In fact, when I was doing my fieldwork, I even noticed many Kannada-speaking people coming and eating at these restaurants, excited to taste the food there.” 

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