research paper on gender neutral society

Gender-Neutral Language and Gender Disparities

This study investigates empirically whether and how the use of gender-neutral language affects the performance of women and men in real high-stakes exams. We make use of a natural experiment in which the institute administering Israel’s standardized college admission tests amended the language used in its exams, making test language more gender neutral. We find that the change to a more gender-neutral language was associated with a significant improvement in the performance of women on quantitative questions, which meaningfully reduced the gender gap between male and female performance on these questions. However, the change did not affect female performance on verbal questions nor male performance on either quantitative or verbal questions. Our findings are consistent with the hypothesis that gendered language may introduce a "stereotype threat" that adversely affects women’s performance in tasks in which they are stereotypically perceived to underperform. Our findings have significant implications for the ongoing academic and policy discussions regarding the use and effects of gender-neutral language.

We thank Ian Ayers, Lucian Bebchuk, Daniel Bird, Raquel Fernandez, Steven Lehrer, Adriana Robinson, Noray Savannah and Analia Schlosser, for valuable comments and discussion. We also want to thank all the participants of the reason and decision retreat at Tel-Aviv University and all the participants at the ISPA (Israeli Psychometric Association) conference. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Can Gender-Fair Language Reduce Gender Stereotyping and Discrimination?

Gender-fair language (GFL) aims at reducing gender stereotyping and discrimination. Two principle strategies have been employed to make languages gender-fair and to treat women and men symmetrically: neutralization and feminization. Neutralization is achieved, for example, by replacing male-masculine forms ( policeman ) with gender-unmarked forms ( police officer ), whereas feminization relies on the use of feminine forms to make female referents visible (i.e., the applicant… he or she instead of the applicant… he ). By integrating research on (1) language structures, (2) language policies, and (3) individual language behavior, we provide a critical review of how GFL contributes to the reduction of gender stereotyping and discrimination. Our review provides a basis for future research and for scientifically based policy-making.

Linguistic gender asymmetries are ubiquitous, as documented in the contributions in Hellinger and Bußmann (2001 2002, 2003 ), which analyze 30 languages (e.g., Arabic, Chinese, English, Finnish, Hindi, Turkish, Swahili) from various language families. An almost universal and fundamental asymmetry lies in the use of masculine generics . In English, for example, generic he can be used when gender is irrelevant (e.g., the user… he ) and in German, masculine role nouns serve as labels for mixed gender groups (e.g., einige Lehrer , masc.pl ‘several teachers’ for a group of male and female teachers). Thus, masculine forms not only designate men but also mixed-gender groups or referents whose gender is unknown or unspecified (see Stahlberg et al., 2007 ). Feminine forms, on the other hand, do not function generically but refer to women only ( Hellinger and Bußmann, 2001 ).

That masculine forms are used to represent all human beings is in accord with the traditional gender hierarchy, which grants men more power and higher social status than women ( Ridgeway and Correll, 2004 ). A large-scale content analysis of 800,000 Reuters news messages (published in English between 1996 and 1997) found that the pronoun he was more frequent than she in the news and also appeared in more positive contexts ( Gustafsson Sendén et al., 2014 ). The interrelation of language and the gender hierarchy has also been documented in a study which analyzed the ratio of male to female pronouns (e.g., he/she , his/hers ) in written texts (full texts of about 1.2 million U.S. books, years 1900–2008; from the Google Books database; Twenge et al., 2012 ). This ratio was found to reflect the status of women in the United States during the 20th century. When women’s status was high (as indicated by educational attainment, labor force participation, etc.), the proportion of female pronouns was higher; when women’s status was low, female pronouns were less frequent.

Gender-fair language (GFL) 1 was introduced as a response to this structural asymmetry and as part of a broader attempt to reduce stereotyping and discrimination in language (see Fairclough, 2003 ; Maass et al., 2013 , for the political correctness debate). GFL aims to abolish asymmetries in referring to and addressing women and men, for example, by replacing masculine forms ( policeman ) with gender-unmarked forms ( police officer ), or by using both masculine and feminine forms (i.e., the applicant… he or she instead of the applicant… he ).

In this paper, we review theoretical and empirical work on the role of GFL in sustaining or reducing gender stereotyping and social discrimination, as a follow-up on a comprehensive research program (the Marie Curie Initial Training Network - Language, Cognition, and Gender, ITN LCG , http://www.itn-lcg.psy.unibe.ch/content/index_eng.html ). In this framework, we survey research on (1) language structures, (2) language policies, and (3) individual language behavior in order to draw conclusions on the effectiveness of GFL and to identify boundary conditions and obstacles for its implementation. Our aim is to critically discuss and integrate research findings to answer the question of whether and under what circumstances GFL contributes to the reduction of gender stereotyping and discrimination. Hopefully, this review will provide a useful basis for future research and for scientifically based policy-making.

Language Structures

Although gender asymmetries exist in most, if not all, languages, they may be more or less conspicuous, depending on the structure of the language. Three types of languages can be distinguished: grammatical gender languages, natural gender languages, and genderless languages (see Stahlberg et al., 2007 ). Table ​ Table1 1 gives an overview of this typology, describing the main characteristics of the different types with regard to gender and gender asymmetries as well as preferred strategies of linguistic gender-fairness. German, French, and Czech, for example, are grammatical gender languages . In these languages, every noun has a grammatical gender and the gender of personal nouns tends to express the gender of the referent. In natural gender languages (English or Swedish) 2 personal nouns tend to be gender-neutral (e.g., neighbor ) and referential gender is expressed pronominally (e.g., he/she ). In genderless languages such as Finnish or Turkish neither personal nouns nor pronouns signal gender. Here, gender is only expressed through attributes such as ‘male/female [teacher]’ or in lexical gender words such as ‘woman’ or ‘father.’ Consequently, gender and linguistic gender asymmetries are much more visible in grammatical gender languages than in natural gender languages or genderless languages ( Hellinger and Bußmann, 2001 ).

Overview of language types regarding expression of gender and gender asymmetries.

The way gender is encoded in a language may be associated with societal gender equality ( Stahlberg et al., 2007 ). This assumption was tested empirically for 111 countries with different language systems, controlling for geographic, religious, political, and developmental differences ( Prewitt-Freilino et al., 2012 ). In this research, the Global Gender Gap Index of the World Economic Forum was used to determine gender equality (GGI; Hausmann et al., 2009 ). Countries with grammatical gender languages were found to reach lower levels of social gender equality than countries with natural gender languages or genderless languages. This suggests that a higher visibility of gender asymmetries is accompanied by societal gender inequalities. A survey on sexist attitudes yielded additional evidence for this relationship ( Wasserman and Weseley, 2009 ): respondents (native speakers of English as well as bilinguals) exhibited more sexist attitudes when the survey was conducted in a grammatical gender language (Spanish or French) than in a natural gender language (English). These findings document that, from the perspective of gender-fairness or gender equality, grammatical gender languages present a particularly complex and difficult case.

Research has consistently revealed that masculine generics evoke a male bias in mental representations and make readers or listeners think more of male than female exemplars of a person category ( Stahlberg et al., 2007 ). Effects of linguistic forms on mental representations were measured with the help of various experimental methodologies, for instance, (1) completing sentences with different pronouns and nouns (e.g., he , she , he/she , the lawyer , the client ; Jacobson and Insko, 1985 ), (2) writing stories about fictitious people following an introductory sentence in the masculine or in gender-fair wording ( Heise, 2000 ), (3) naming female or male representatives (e.g., favorite musician) in response to either masculine nouns or combinations of feminine and masculine forms ( Stahlberg et al., 2001 ), (4) estimating the proportion of women and men in certain roles (e.g., participants at a congress of nutritionists versus geophysicists; Braun et al., 1998 ), (5) measuring reading time as an indicator of fit between sentences about social groups denoted by nouns with different grammatical gender and sentences that contained a reference to the social group that qualified the group members as female, male, or neither one ( Irmen and Roßberg, 2004 ), or (6) measuring reaction times when classifying gender-related (e.g., she , he ) or neutral pronouns (e.g., it , me ) as female or male after perceiving gender-related (e.g., mother , father , nurse , doctor ) or gender-neutral primes (e.g., parent , student ; Banaji and Hardin, 1996 ). The masculine bias in language has been observed in English (e.g., Crawford and English, 1984 ; Hamilton, 1988 ; Gastil, 1990 ; Ng, 1990 ), French (e.g., Chatard et al., 2005 ; Gabriel et al., 2008 ), German (e.g., Heise, 2000 ; Stahlberg et al., 2001 ; Braun et al., 2005 ; Irmen, 2007 ), Italian (e.g., Cacciari and Padovani, 2007 ), Polish (e.g., Bojarska, 2011 ), and Spanish ( Carreiras et al., 1996 ). In a study with German and Belgian school children, the grammatical form of job titles was found to influence the children’s perceptions of typically male jobs: when occupations were presented in the masculine (e.g., German Ingenieure , masc.pl ‘engineers’) the mental accessibility of female jobholders was lower than with feminine-masculine word pairs (e.g., Ingenieurinnen und Ingenieure , fem.pl and masc.pl ‘[female and male] engineers’; Vervecken et al., 2013 ). In another study, adult speakers as well envisaged more men in an occupation when job advertisements included more masculine than feminine forms ( Gaucher et al., 2011 ). In all, both the range of methods as well as the number of languages for which the male bias of masculine generics has been documented attests to the validity of the finding.

In general, different strategies can be used to make language gender-fair and avoid detrimental effects of masculine generics: neutralization, feminization and a combination of the two. Which strategy is the appropriate one depends on the type of language concerned (grammatical gender language, natural gender language, or genderless language, Bußmann and Hellinger, 2003 ).

In the framework of neutralization gender-marked terms are replaced by gender-indefinite nouns (English policeman by police officer ). In grammatical gender languages, gender-differentiated forms are replaced, for instance, by epicenes (i.e., forms with invariant grammatical gender which refer to female as well as male persons; e.g., German Staatsoberhaupt , neut. ‘head of state’ or Fachkraft , fem. ‘expert’ in German). Neutralization has been recommended especially for natural gender languages (e.g., Hellinger and Bußmann, 2003 ; for English; Norwegian; Danish) and genderless languages (e.g., Engelberg, 2002 , for Finnish), as it is fairly easy to avoid gender markings in these languages. Thus, neither generic he nor the combination he/she , but “singular they is the dominant epicene pronoun in modern written British English. However, despite its use, singular they has never been endorsed by institutions of the English language, such as major dictionaries and style guides (although many style guides now reject generic he… )” ( Paterson, 2014 , p. 2). Recently, a gender-neutral third person pronoun was invented in Swedish: hen. This neologism first appeared in 2012 in a children’s book where it served as an alternative to the gender-marked pronouns ‘she’ (hon) and ‘he’ (han; Gustafsson Sendén et al., 2015 ).

In contrast, feminization is based on the explicit inclusion of women. Thus, masculine generics are replaced by feminine-masculine word pairs (e.g., German Elektrikerinnen und Elektriker ‘[female and male] electricians’; Polish nauczycielki i nauczyciele ‘[female and male] teachers’) or abbreviated forms with slashes (e.g., German Elektriker/in ; Polish nauczyciel/ka ) or brackets (e.g., Elektriker[in] ; nauczyciel[ka] ). Feminization has been recommended for grammatical gender languages such as German, Spanish, Czech, and Italian ( Hellinger and Bußmann, 2003 ; Moser et al., 2011 ), usually in combination with neutralizing in order to avoid overly complex sentence structures.

However, feminization is not always advantageous for women. The Italian feminine suffix - essa , for example, has a slightly derogatory connotation (e.g., Marcato and Thüne, 2002 ). Accordingly, a woman introduced as professoressa ‘female professor’ was perceived as less persuasive than a man or than a woman referred to with the masculine form professore ( Mucchi-Faina, 2005 ). Masculine terms used in reference to a female jobholder were associated with higher status than feminine job titles with - essa ( Merkel et al., 2012 ). Another example is the German (originally French) suffix- euse or - öse. Feminine terms such as Masseuse ‘(female) masseur’ and Frisöse ‘(female) hair dresser’ evoke sexual or frivolous associations, so that the neutral suffix -in is usually preferred, as in Ingenieur-in ‘female engineer,’ or Spediteur-in ‘female forwarding agent.’ Especially in Slavic languages feminine job titles tend to be associated with lesser status, with rural speech, or with the meaning ‘wife of…’ rather than ‘female job holder’ (for Russian: Doleschal and Schmid, 2001 ; for Serbian: Hentschel, 2003 ; for Polish: Koniuszaniec and Blaszkowa, 2003 ). There are also asymmetries in meaning between feminine and masculine forms, as with Polish sekretarka ‘female secretary,’ which designates a personal assistant, whereas the masculine sekretarz refers also to a high governmental function. In Polish, the feminine suffix - ka not only derives feminine occupational terms (such as nauczyciel-ka ‘female teacher’ from masculine nauczyciel ‘teacher’) but also words for inanimate objects such as marynar-ka ‘jacket’ from masculine marynarz ‘sailor.’ Problems of this kind can limit the possibilities of feminization in some languages. Where feminization faces such structural problems, its use is less widespread and may have negative effects (Italian: Mucchi-Faina, 2005 ; Polish: Formanowicz et al., 2013 , 2015 ). But where feminine suffixes are productive feminization can became a linguistic norm and can be evaluated positively (German: Vervecken and Hannover, 2012 ).

The focus of early research on GFL was mostly on the masculine bias associated with masculine generics. But although these findings suggest that linguistic asymmetries may have farther-reaching consequences, this line of research has made no further progress until recently. The latest findings are more comprehensive and indicate how linguistic asymmetries may facilitate (unintended) forms of social discrimination ( Mucchi-Faina, 2005 ; Stahlberg et al., 2007 ). For example, adult women were reluctant to apply to gender-biased job advertisements (e.g., English job titles ending in - man ) and were more interested in the same job when the advertisement had an unbiased form ( Bem and Bem, 1973 ). Also, the likelihood of naming women as possible candidates for the office of chancellor in Germany was found to depend on the grammatical gender of the word ‘chancellor’ in the question ( Stahlberg and Sczesny, 2001 ). When the masculine generic ( Kanzler ) was used, fewer respondents suggested female politicians compared to a combination of masculine and feminine form ( Kanzler oder Kanzlerin ‘[male or female] chancellor’). Moreover, self-evaluation and evaluations by others were found to be influenced by linguistic forms. Thus, girls assumed women to be less successful in typically male occupations when the jobs were described with masculine rather than gender-fair forms, and they were also less interested in these occupations (see also Chatard et al., 2005 ; Vervecken et al., 2013 ). Using feminine-masculine word pairs rather than masculine forms for traditionally male occupations boosted children’s self-efficacy ( Vervecken and Hannover, 2015 ). Furthermore, occupations described in pair forms mitigated the difference between ascribed success to female and male jobholders in gendered occupations ( Vervecken et al., 2015 ). Also, women’s perceptions of belonging were found to mediate the effect that women found jobs advertised in the masculine less appealing ( Gaucher et al., 2011 ). Accordingly, women experienced the use of gender-exclusive language during a mock job interview as ostracism ( Stout and Dasgupta, 2011 ). They reported a lower sense of belonging when gender-exclusive language ( he ) was used compared to gender-inclusive ( he or she ) or gender-neutral ( one ) forms. In a study on Austrian German, the wording of job advertisements influenced the evaluation of candidates for leadership positions ( Horvath and Sczesny, 2015 ): men were perceived as fitting a high-status leadership position better than women when a masculine job title was used ( Geschäftsführer , masc. ‘chief executive officer, CEO’). But when the job ad was gender-fair ( Geschäftsführerin/Geschäftsführer , fem./masc. ‘[female/male] CEO’), women and men were judged as equally suited. In the context of a lower-status position (project leader) no differences of this kind occurred.

Language Policies

Many countries have pledged themselves to an equal treatment of women and men (e.g., the member states of the European Union and associated states in the Treaty of Lisbon- European Commission, 2007 ), and the use of GFL is widely recommended ( Schweizerische Bundeskanzlei, 1996 , revised in 2009; UNESCO, 1999 ; National Council of Teachers of English, 2002 ; European Commission, 2008 ; American Psychological Association, 2009 ). But the implementation of GFL has reached different stages in different countries and speech communities.

In the 1970s, guidelines for GFL were introduced in particular professional domains across national and linguistic boundaries, for example, by the American Psychological Association (1975) , by the McGraw-Hill Book Company (1974 ; see also Britton and Lumpkin, 1977 ; Sunderland, 2011 ) and the Macmillan Publishing Company (1975) . These guidelines demand that authors of (psychological) articles, books, teaching materials, or fiction treat women and men equally, including the language they use (see also Sadker et al., 1991 ). Publication guidelines of this kind have been effective, because authors need to follow the rules if they want to see their manuscripts published. In texts written by Australian academics ( Pauwels, 2003 ), for example, masculine generic pronouns were infrequent. Similarly, an analysis of American Psychological Association journal articles from the years 1965–2004 revealed a complete absence of generic he from 1985 onward, even if the articles still contained other, more subtle gender biases such as androcentric reporting in tables and graphs ( Hegarty and Buechel, 2006 ).

In 1987 representatives of Canada and the Nordic countries argued for an adoption of GFL by the United Nations Educational, Scientific and Cultural Organization . This resulted in the creation of guidelines in UNESCO (1999) . UNESCO’s position in favor of GFL is described in their gender equality guidelines: “This development indicated a growing awareness that language does not merely reflect the way we think: it also shapes our thinking. If words and expressions that imply that women are inferior to men are constantly used, that assumption of inferiority tends to become part of our mindset; hence the need to adjust our language when our ideas evolve” ( UNESCO, 2011 , p. 4). The document not only became the most widely recognized international standard for GFL, it also regulates language use in internal documents and publications of UNESCO. Similar guidelines for publications were issued by the European Commission (2008) , referring to all working languages of the European Union (EU). Yet, the standards promoted by UNESCO and the EU do not regulate language use in the different countries and are not considered mandatory within their member states.

The availability of GFL policies and the extent of their implementation, that is, their dissemination and execution, also vary considerably between countries ( Moser et al., 2011 ). In Italy, for instance, guidelines for GFL were issued in Sabatini (1987) , in the German-speaking area most guidelines appeared in the 1990s (e.g., Hellinger and Bierbach, 1993 ; Schweizerische Bundeskanzlei, 1996 ; revised in 2009), and in the Czech Republic guidelines were published only in Valdrová et al. (2010) . In other countries such as Poland there are as yet no official guidelines at all. While in some states GFL policies are mentioned only on the website of a ministry (e.g., Czech Republic; Valdrová et al., 2010 ), use of GFL is mandatory in job ads and public administration in Austria. Since the 1990s the German Duden dictionaries, for example, have included not only the masculine form of personal nouns and job titles but routinely cite the corresponding feminine forms ( Kunkel-Razum, 2004 ). The dictionary lists even feminine forms that are infrequent in texts. An example is the word Päpstin ‘female pope,’ which has been listed in the Grosses Wörterbuch der deutschen Sprache (Large dictionary of the German language) from the year 1999 onward, even though obviously there never was a female pope in the history of the Catholic Church ( Kunkel-Razum, 2004 ). Moreover, the Duden editors decided to include a chapter on the “equal treatment of women and men in language” in the ninth volume of the series Richtiges und gutes Deutsch (Correct and good German). The chapter describes the linguistic potential which the German language offers for speaking or writing in a gender-fair way.

In the German-speaking countries, language policies have become part of the organizational culture of various institutions such as universities and administrations (e.g., Schweizerische Bundeskanzlei, 1996 , revised in 2009; Merkel, 2011 ; Swiss Federal Institute of Technology Zurich, 2011 ; Gendup – Zentrum für Gender Studies und Frauenförderung, 2012 ). Even so, Austria is the only country where the use of GFL in job advertisements is strictly prescribed and companies are fined for failing to address both genders in their job ads ( Bundesministerium für Frauen und Öffentlichen Dienst, 2009 ). This may be the reason why the proportion of job ads worded in GFL differs between Austria and German-speaking Switzerland: only 9% of Austrian job advertisements contain masculine generics, whereas it is 27% in Switzerland ( Hodel et al., 2013 ).

School and education are of particular importance for the implementation of GFL. In most countries there are few official GFL guidelines for authors of educational materials ( Eurydice, 2009 ) and regulations concerning schoolbooks exist only in certain countries (e.g., Germany, Ireland, or Iceland). Similarly, only a few countries require schoolbooks to be officially evaluated or approved. In the UK, for example, educational authorities do not monitor teaching materials and schools choose them autonomously. Today German schoolbooks for mathematics and German mostly use gender-neutral forms, followed by masculine generics and feminine-masculine word pairs, ( Moser and Hannover, 2014 ). The two gender-fair options together (word pairs and neutralizing) outweighed the masculine in the schoolbook sample that was analyzed. Since earlier studies on German schoolbooks (e.g., Lindner and Lukesch, 1994 ; Preinsberger and Weisskircher, 1997 ) reported a predominance of masculine generics, this finding indicates an increase of GFL in schoolbooks. In some of the texts, however, feminine-masculine word pairs were mixed with masculine generics (see also Markom and Weinhäupl, 2007 ). This inconsistency is problematic because in the presence of word pairs masculine forms may be understood as referring to male persons only (e.g., Gabriel et al., 2008 ).

Individual Language Behavior

Apart from language structures and country-specific aspects, there are a number of factors that make individuals use or reject GFL. One major factor is the novelty of gender-fair forms, which conflicts with speakers’ linguistic habits ( Blaubergs, 1980 ). As long as this is the case, people may experience GFL as irritating, and consequentially may refrain from using it. This could explain why negative effects of GFL have been found especially in the initial phases of language reform such as, for instance, in English in the 1990s ( McConnell and Fazio, 1996 ), and in Italian and Polish in the beginning of the 21st century ( Mucchi-Faina, 2005 ; Merkel et al., 2012 ; Formanowicz et al., 2013 ).

Moreover, initiatives for GFL were first instigated by activist movements (e.g., Silveira, 1980 ; Pusch, 1984 ) and for that reason often met with negative reactions ( Blaubergs, 1980 ; Parks and Roberton, 1998 ; Formanowicz et al., 2013 ). It is conceivable that individual reactions toward GFL are not only caused by its novelty, but also depend on attitudes toward gender arrangements ( Jost and Kay, 2005 ; Carney et al., 2008 ), for conservative political attitudes are associated both with lesser openness for novelty ( Carney et al., 2008 ) and with stronger support for traditional gender arrangements ( Jost et al., 2003 , 2008 ; Hoyt, 2012 ). Thus, speakers of Polish with more conservative attitudes devaluated female job applicants referring to themselves with a feminine job title compared to female and male applicants using a masculine job title ( Formanowicz et al., 2013 ).

Another factor for individual speakers’ use of GFL might be speakers’ gender: women could be expected to hold more favorable attitudes toward GFL than men and they might be more inclined to use it in their own speech. However, research findings on this point are mixed. While in some studies men rejected GFL more than women did (e.g., Parks and Roberton, 2004 ; Douglas and Sutton, 2014 ), other studies found no gender difference in attitudes toward GFL (e.g., Sczesny et al., 2015 ). Gender differences were mediated by participants’ attitudes toward women, which were, in turn, driven by more comprehensive ideologies that justified the social gender hierarchy (i.e., gender-specific system justification and social dominance orientation; Douglas and Sutton, 2014 ).

Language use has been viewed as associated with speakers’ sexist attitudes , so much so that the use of sexist language has been regarded as an example of subtle sexism ( Swim et al., 2004 ). Modern sexism, for instance, is a view that denies that women are still discriminated against and disapproves of policies promoting gender equality ( Swim et al., 1995 ). In fact, participants with modern sexist beliefs were found to use more traditional, gender-unfair language ( Swim et al., 2004 ). Correspondingly, speakers with stronger sexist attitudes toward women used gender-fair pronouns less frequently than speakers with less sexist attitudes ( Jacobson and Insko, 1985 ). Speakers with progressive gender role perceptions, on the other hand, exhibited a tendency to avoid sexist language when writing an essay ( McMinn et al., 1991 ).

This raises the question how sexist or non-sexist ideologies translate into actual language behavior. Spontaneous use of GFL was found to be guided by explicit intentions to use GFL as well as more implicit processes involving use of GFL in the past ( Sczesny et al., 2015 ). GFL use was not predicted directly by sexist beliefs but by intentions and habits. In other words, sexist speakers do not avoid GFL just because they are reluctant to change their linguistic habits, they deliberately employ a form of language that treats males as the norm and makes women less visible. Habits guide speakers’ linguistic behavior without their being aware of it ( Sczesny et al., 2015 ), and learning processes play a role for GFL to become a habit. S peakers who grew up with schoolbooks using predominantly masculine generics (e.g., English: Hellinger, 1980 ; Campbell and Schram, 1995 ; Lee and Collins, 2008 ; German: Lindner and Lukesch, 1994 ; Preinsberger and Weisskircher, 1997 ) tend not to question this usage. But once speakers have acquired the habit of using GFL they will rely on this language form. Establishing GFL habits via teaching and practicing current linguistic standards (e.g., Duden; Kunkel-Razum, 2004 ) is a promising approach which should follow the initial phase of GFL implementation and may reduce political controversies. In this sense, a prevalence of GFL in the media could also promote the use of GFL by individual speakers.

So far, few studies have investigated how speakers can be made to use and approve of GFL. After training interventions, speakers of English used slightly more gender-fair pronouns in completing sentences than non-attendants ( McMinn and Foster, 1991 ; McMinn et al., 1991 ; Prentice, 1994 ). Their attitudes, however, did not change ( Prentice, 1994 ). German speakers as well used more GFL after being exposed to arguments for GFL than in a control condition ( Koeser and Sczesny, 2014 ), but this did not affect their attitudes toward GFL. Interestingly, merely reading texts in gender-fair wording can also increase speakers’ own use of GFL: female speakers of German employed more gender-fair forms after reading a gender-fair text than after other texts, but there was no such effect for men ( Koeser et al., 2015 ). Male speakers increased their use of gender-fair forms only when their attention was drawn to GFL forms. These findings indicate that it is more difficult to change attitudes than to promote speakers’ actual use of GFL.

Overcoming Gender Stereotyping And Discrimination With Gender-Fair Language?

Over the past decades, a large body of research—based on various experimental methodologies, from storytelling to measuring reaction times—has confirmed the influence of linguistic forms on the accessibility of mental representations of women and men (see Stahlberg et al., 2007 ). Regardless of language structure and of the ease of implementing GFL ( Bußmann and Hellinger, 2003 ), a consistent finding is that speakers do not understand masculine forms as referring to both genders equally but that they interpret them in a male-biased way. This underscores the importance of implementing GFL in everyday language and of using it consistently, so that speakers take up this usage in their own texts and utterances.

How successful have the respective language policies been so far? In natural gender languages , neutralization has been fairly easy to adopt and implement (e.g., English, Danish). But even in these language communities people are guided by their knowledge about typical gender distributions in social roles. Thus, English readers tend to associate different occupations or role nouns with men or women, since gender stereotypes are incorporated in their mental representations ( Oakhill et al., 2005 ); and even though there are fewer gender-marked forms in natural gender languages, masculine generics exist and their use can result in social discrimination ( Stout and Dasgupta, 2011 ). In grammatical gender languages , feminization as the main strategy of GFL still poses challenges. This is especially true for some languages, e.g., Italian ( Merkel et al., 2012 ) and Slavic languages ( Koniuszaniec and Blaszkowa, 2003 ), where the creation of feminine forms can be problematic, as outlined above. Refusal of GFL can still be observed ( Formanowicz and Sczesny, 2014 ). Such disadvantages are likely to occur while the change is in progress ( Formanowicz et al., 2015 ).

Moreover, our review suggests that—independent of language structure—GFL is more frequent and more accepted when it is backed by official regulations and when the use of biased language is sanctioned in some way (e.g., in official publications or texts; American Psychological Association, 1975 , 2009 ; Bundesministerium für Frauen und Öffentlichen Dienst, 2009 ; see Hodel et al., 2013 ). The relationship between policy-making and social change is surely bidirectional. On the one hand, gender equality movements and their demands find their way into legislation. On the other hand, official regulations may stipulate social change by facilitating the internalization of new norms and enforcing their execution. Public discussions over policies also enhance public awareness for GFL (see above the singular pronouns they in English and hen in Swedish). The contribution of language reforms to gender equality in a society/speech community can best be assessed with investigations that compare countries sharing the same language (e.g., French in Canada and in France) as well as countries with different languages (e.g., Polish and German, two grammatical languages at different stages of implementing GFL). Although there have been some attempts at this type of research ( Formanowicz et al., 2015 ; Gustafsson Sendén et al., 2015 ) more research is needed to evaluate the effectiveness of language-related policies and provide an evidence-based rationale for policy-making.

As mentioned above, speakers’ use of GFL results from deliberate processes, involving attitudes and intentions, and habitual processes, involving repetition of past behavior ( Sczesny et al., 2015 ). Both types of processes are relevant for the successful implementation of GFL. Despite the various guidelines and legal regulations for GFL that exist on global and national levels, spontaneous use of GFL by individual speakers still seems to be infrequent. For instance, use of GFL in a gap-filling task was quite low among speakers of German from Germany and Switzerland, although GFL policies are fairly advanced in both countries. Most of the participants used more masculine generics than gender-fair forms. As language use is an action performed in a wide range of circumstances, future research should also assess the contiguity between behavior and context. Speakers may employ GFL when writing official texts, for instance, but not when talking or writing to friends. Moreover, attitudes, norms, and intentions concerning GFL in general seem to be only moderately favorable. Even though positive arguments for GFL can help to promote a change in language behavior ( Koeser and Sczesny, 2014 ), future research should attempt to identify factors that are crucial for a deliberate use of GFL. For instance, it might be worthwhile to determine the content and strength of attitudes in different groups of speakers, namely speakers who use GFL regularly compared to speakers who use GFL only occasionally and others who do not use it at all. To gain a more comprehensive understanding of the processes underlying a rejection of GFL, future research could also take a closer look at people’s political attitudes ( Formanowicz et al., 2013 ), their preference for status quo, and their acceptance of traditional gender arrangements ( Jost et al., 2008 ).

In any case, attitudes toward GFL may become more favorable the more frequently and longer GFL has been used (in addition to a mere exposure effect, Zajonc, 1968 , see also the existence bias: people treat the existence of something as evidence of its goodness; Eidelman et al., 2009 ). The role of familiarity for an active use of GFL can best addressed with longitudinal studies. In Sweden, for example, speakers’ attitudes toward the gender-neutral pronoun hen have become more positive over time ( Gustafsson Sendén et al., 2015 ). A meta-analytical approach would constitute another way of capturing the dynamics of GFL implementation, taking into account the time when the studies were conducted but also the availability of policies and the structure of the languages concerned. This approach might help to determine whether a language has left the phase where GFL evokes negative associations as well as the role of other factors (such as language policies).

Interventions aiming to increase the use of GFL could focus on a simple repetition of non-sexist expressions, so that these become established habits ( Koeser et al., 2015 ; Wood and Rünger, 2016 ). This would be a very subtle and implicit way of promoting use of GFL. The development and evaluation of GFL interventions/trainings has not yet been investigated systematically. Future research should take both deliberate and habitual processes of GFL use into consideration, for instance, by analyzing whether children—exposed to and trained in GFL at school (with the help of current schoolbooks)—will later use GFL habitually and consequently hold less gender-stereotypic beliefs.

Finally, there are still obstacles that prevent GFL from becoming a linguistic norm/standard and prevent the change toward an equal treatment of women and men. First, the male bias of linguistic asymmetries in mental representations is backed by a higher prevalence of men in certain social roles (e.g., heroes, politicians), which facilitates their cognitive accessibility ( Stahlberg and Sczesny, 2001 ). Once women and men occupy all social roles to a similar extent (see social role theory, which poses that gender stereotype content results from observing women and men in certain societal roles; Eagly, 1987 ; Bosak et al., 2012 ), this difference in accessibility should decrease and more gender-balanced mental representations should emerge. Ironically, recent research has documented that linguistic asymmetries prevent girls and women from aspiring to male-dominated roles (see Chatard et al., 2005 ; Gaucher et al., 2011 ; Stout and Dasgupta, 2011 ; Vervecken et al., 2013 ; Vervecken and Hannover, 2015 ) and thereby perpetuate the higher accessibility of men in these roles.

Second, the use of gender-unfair language, especially of masculine generics, restricts the visibility of women and the cognitive availability of female exemplars ( Stahlberg et al., 2007 ), which may be disadvantageous for women (e.g., in personnel selection; Stout and Dasgupta, 2011 ; Horvath and Sczesny, 2015 ). However, increasing the visibility of women with the help of novel feminine forms may also have negative consequences and may therefore be avoided, for instance, in women’s professional self-reference ( Merkel et al., 2012 ; Formanowicz et al., 2013 ). Thus, the avoidance of GFL by women (e.g., avoidance of feminine job titles in grammatical gender languages), in order to protect themselves from ascriptions of incompetence or lower status, also perpetuates the reduction of gender stereotyping and social discrimination.

Third, arguments against GFL have routinely included the presumed difficulty of understanding GFL texts ( Parks and Roberton, 1998 ). Empirical investigations have refuted this argument and have shown that text quality ( Rothmund and Christmann, 2002 ) and cognitive processing were not damaged ( Braun et al., 2007 ). When GFL texts were compared to (generic) masculine texts, there were no differences in readability and esthetic appeal ( Blake and Klimmt, 2010 ). In all, the empirical evidence does not confirm the alleged disadvantage of GFL. Yet, these findings and the scientific evidence for serious disadvantages of masculine generics (see above) have largely been ignored in political controversies and public discussions about GFL. In all, there is a lack of transfer of scientific knowledge which prevents the understanding of linguistic asymmetries as part of a broader gender imbalance and hinders social change. Education and policy-making therefore need to increase the efforts of circulating new scientific insights about GFL to break the vicious circle of ill-informed controversies and discussions about GFL.

At first glance linguistic gender asymmetries seem to affect mostly women. When masculine forms are used it is women who are seen as less prototypical category exemplars, it is women who feel less adequate or are less preferred as job candidates, and it is women who profit from GFL. Therefore, the question arises whether GFL benefits men as well. First, the introduction of GFL might represent a particular challenge for men. In a study by Crawford and English (1984) both male and female participants read a text whose title contained either masculine generics ( Psychologist and his work? ) or GFL ( Psychologist and their work? ) and were to recall the text after 2 days. As the results showed, men’s recall was better in the masculine and women’s recall in the GFL condition. This finding indicates that learning to use GFL involves more than overcoming linguistic novelty. For men, GFL means an unwelcome loss of their privileged position in language. Only in few situations have they something to gain through GFL. If all job advertisements would contain GFL, for instance, men might be more included in traditionally female jobs which used to be referred to in the feminine. Future research should also consider the perspective of men and examine how GFL can turn into a win–win situation for women and men in modern societies.

To conclude, past research has revealed that GFL has the potential to make significant contributions to the reduction of gender stereotyping and discrimination. But as the body of existing evidence is based mainly on experimental paradigms with different kinds of measures, future research should take a closer look on people’s actual language use in everyday life (e.g., in conversations, in the classroom, in social media or organizational communication). Moreover, it will be fruitful to further investigate the dynamics of GFL usage and its effects from cross-linguistic and cross-cultural perspectives (see above the Marie Curie Initial Training Network - Language, Cognition, and Gender, ITN LCG , which can be regarded as a first step in this direction). Speakers’ willingness to use GFL in everyday life is crucial in order to profit from the impact of GFL on the (linguistic and social) treatment of women and men in society. But a deliberate effort is required before the use of GFL can become habitual. Education and policy-making can facilitate these processes. When employed consistently over a longer period, and especially when supported by well-informed controversies and discussions, GFL will contribute even more to the reduction of gender stereotyping and discrimination and may thus function as another barometer for change (like the decrease in gender-stereotypical social perception of leadership, Schein, 2001 ).

Conflict of Interest Statement

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. The reviewer Simona Mancini and handling Editor Manuel Carreiras declared their shared affiliation, and the handling Editor states that the process nevertheless met the standards of a fair and objective review.

Funding. This research was conducted within the Marie Curie Initial Training Network: Language, Cognition, and Gender , ITN LCG, funded by the European Commission’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n°237907 ( www.itn-lcg.eu ). We thank Friederike Braun for her valuable comments on an earlier version of this manuscript.

1 In the literature, GFL is also referred to with other terms, e.g., gender-neutral language : Sarrasin et al. (2012) ; gender-inclusive language : Stout and Dasgupta (2011) ; non-sexist language : Douglas and Sutton (2014) .

2 According to McConnell-Ginet (2013) , however, the concept of natural gender language is a myth, and she suggests calling the respective languages “notional” gender languages, since, for example in English, “concepts and ideas about biological sex matter at least as much as sex itself to the choice of English third-person pronouns.” (p. 3).

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International Journal of Interdisciplinary Research

• Open access
• Published: 05 March 2022

Analyzing genderless fashion trends of consumers’ perceptions on social media: using unstructured big data analysis through Latent Dirichlet Allocation-based topic modeling

• Hyojung Kim   ORCID: orcid.org/0000-0001-9422-1944 1 ,
• Inho Cho 1 &
• Minjung Park   ORCID: orcid.org/0000-0003-3040-2759 1  

Fashion and Textiles volume  9 , Article number:  6 ( 2022 ) Cite this article

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After the development of Web 2.0 and social networks, analyzing consumers’ responses and opinions in real-time became profoundly important to gain business insights. This study aims to identify consumers’ preferences and perceptions of genderless fashion trends by text-mining, Latent Dirichlet Allocation-based topic modeling, and time-series linear regression analysis. Unstructured text data from consumer-posted sources, such as blogs and online communities, were collected from January 1, 2018 to December 31, 2020. We examined 9722 posts that included the keyword “genderless fashion” with Python 3.7 software. Results showed that consumers were interested in fragrances, fashion, and beauty brands and products. In particular, 18 topics were extracted: 13 were classified as fashion categories and 5 were derived from beauty and fragrance sectors. Examining the genderless fashion trend development among consumers from 2018 to 2020, “perfume and scent” was revealed as the hot topic, whereas “bags,” “all-in-one skin care,” and “set-up suit” were cold topics, declining in popularity among consumers. The findings contribute to contemporary fashion trends and provide in-depth knowledge about consumers’ perceptions using big data analysis methods and offer insights into product development strategies.

Introduction

Consumers’ blogs and social network opinions have become a valuable resource for gaining marketing insights and relationship management (Zhang et al., 2009 ). As social media has profoundly changed our lives, the widespread adoption of social media sources has generated a vast amount of textual data. Knowledge acquired from social networks interacts with consumers and affects many companies to find their competitive advantage in improving brand products or services (Governatori & Iannella, 2011 ; He et al., 2013 ). Consumer-driven fashion trends and continuous social media monitoring has created new paradigms of trend emergence, which lead to the discovery of key values for brands. For example, the traditional runway collections’ design aspects indicated the upcoming fashion trends; however, a social media platform with real-time content posted by consumers, influencers, and brands became streamlined fashion trends (Yotka, 2020 ).

Trend analysis is a technique that attempts to collect information and discover patterns and estimate future predictions (Immerwahr, 2004 ). The fashion industry adapts the trend analysis using the text-mining technique to predict consumer nature, which is associated with business success. The growth of Web 2.0 and social networks has increased the demand for unstructured data such as news, images, and videos online. According to IBM’s report, unstructured data accounted for 93% of the total data in 2020, and it is estimated that 1.7 MB of data are generated every second (Trice, 2015 ). Liu et al. ( 2011 ) found that 80% of an organization’s information consists of text documents, and that using automated computer techniques is essential to exploit the knowledge from the vast amount of text. However, investing consumers’ preferences and adaptation behaviors toward fashion trends is difficult because social media text-based communication analysis is costly and complicated in processing natural language.

The fashion trend implies various societal types and numerous clothing style choices according to different types of societies. Liberal society members tend to be more accepting of radical changes and innovation, while the conservative society community prefers to maintain its conventional costume (Kawamura, 2018 ). South Korea is famous for its highly fashion-conscious consumers who rapidly adjust to emerging trends (Hounslea, 2019 ), as they are willing to engage in digital technology development (Chakravorti et al., 2020 ). At 87%, South Korea’s social media rate is the third highest in the world, enabling consumers to easily follow current widespread trends and to generate new information (Shim, 2020 ). Given that gender fluidity in fashion has seen a recent boom globally since 2018 (Menkes, 2018 ), the genderless concept began to expand as the trend of emphasizing gender diversity expanded in South Korea. Szmydke ( 2015 ) explained that the traditional fashion industry has been providing design and service based on gender identity; however, masculinity and femininity have diversified with the advent of genderless fashion trends. In addition to the importance of the individual’s unique taste on style, current consumers independently define and express their gender identity (Kopf, 2019 ). Clothing is not only a simple method to express one’s lifestyle, but also a strong tool to represent one’s characteristics. Fifty-six percent of Gen-Z consumers who have a spending power of over 140 billion dollars shop outside of their designated gendered area (Marci, 2020 ), and searches for the term “genderless fashion” increased by 52% (Lyst, 2019 ). Moreover, 51% of gender-neutral global fragrance items were launched in 2018 (Murtell, 2019 ), and many fashion brands promoted a campaign of diversity and inclusivity in terms of gender, ethnicity, and body image. The men’s cosmetic market has grown 1.4 times in 5 years—reaching 1.4 trillion KRW (Lee, 2019 ) in South Korea in response to preferences for genderless items.

Therefore, the demand for adapting the genderless fashion trend has risen among general consumers and gender-neutral apparel has strode into retail prominence. Although very few studies have analyzed fashion trends in consumer behavior using the text-mining technique (Blasi et al., 2020 ; Rickman & Cosenza, 2007 ), no previous studies have focused solely on consumers’ perceptions of genderless fashion trends. Moreover, many researchers have explored genderless fashion in terms of design style elements, collection image characteristics, and sociocultural impact (Jordan, 2017 ; Rocha et al., 2005 ; Shin & Koh, 2020 ; Xu & Li, 2012 ) through qualitative research methods. The prominent genderless fashion trend is increasing, and the massive amount of big data has made it possible to understand consumers’ requirements and demands. To the best of our knowledge, this is the first study to evaluate consumers’ awareness of the current genderless fashion trend using the text-mining method. Therefore, this study demonstrates the genderless fashion trend perception among consumers on social media by applying textual data. More specifically, this research aims to answer the following questions.

What major keywords do consumers use when commenting on genderless fashion?

What are the main topics of genderless fashion and how do consumers perceive it?

How have the genderless fashion trends changed over time?

To investigate the research questions, we utilized a probabilistic topic modeling approach known as Latent Dirichlet Allocation (LDA; Blei et al., 2003 ; Griffiths & Steyvers, 2004 ; Newman & Blocks, 2006 ) for consumers’ narrative postings on community sites such as blogs and online communities. LDA-based topic modeling is a supervised machine learning algorithm used to extract latent topics from the thematic structure of large volumes of texts (Elgesem et al., 2015 ). The computational content-analysis of LDA-based topics enables the classification of large amounts of unstructured text documents. Consequently, LDA-based topic models are efficient in discovering and describing hidden semantic structures in a collection of texts (Koltsova & Shcherbak, 2015 ). In particular, we analyzed the search keyword “genderless fashion” on the portal site NAVER ( http://www.naver.com )—the largest web search engine in South Korea. We then examined consumers’ perceptions of genderless fashion over the past 3 years by collecting their texts from blogs and online communities. After the data cleansing and preprocessing procedures, we specified the top keywords to extract the topics. Then, an n-gram analysis (Wallach, 2006 ) was applied to categorize the continuous sequence of high-order phrases from the morphologically analyzed texts. To define the number of topics, perplexity and coherence tests were examined for interpretability verification. The intertopic distance map (IDM; Blei et al., 2003 ) was used to determine the similarity of the chosen topics using a graphic plot showing the specific gravity of the topic and the distance among the topics. Finally, the selected topics were labeled and compared with the representative documents, and a time-series analysis was performed to measure the topic trend change.

This study advances our in-depth understanding of genderless fashion trends and contains diverse perspectives on consumers’ behaviors and interests. This study explains how fashion trends are perceived and commercialized, related to consumers’ use of social media. Further, we extend our research on fashion trend analysis by applying text-mining algorithms to extract the most relevant topics, which goes beyond the findings in the existing literature. Despite the high level of demand among consumers in the pursuit of acceptance of various gender identities in the fashion industry, relevant studies are scarce. In this context, research on genderless fashion trend analysis based on a consumer-driven text-mining analysis is essential, and the current findings will enable fashion brands to forecast customers’ preferences for purchasing gender-neutral products and develop marketing strategies through social media channels.

Literature review

• Genderless fashion trend

The genderless fashion phenomenon has recently emerged as a new standard and has been cited as a major trend among consumers (Bernard, 2018 ; Kerpen, 2019 ; Segalov, 2020 ). The term “genderless” is also referred to as “agender,” “gender fluidity,” “gender neutral,” “gender diversity,” and “gender-free”—all of which refer to the state of being without a clear gender identity (Robinson, 2019 ). It refers to using products and creating styles according to individual personality and taste from a neutral perspective, regardless of gender. Most societies define traits specific to a gender and orient their members in that direction (Risman & Davis, 2013 ); however, genderless is interpreted as a movement to remove the social division between women and men and regard them as neutral individuals. For example, the binarity of gender was classified into distinct male and female segmentations, producing various stereotypes and corresponding behaviors. Strict adherence to traits of masculinity and femininity were expected from each sex, and costumes reflected the resulting dichotomous social norms. The perception of gender was influenced by factors such as feminism and relevant social movements in the 1960s and the development of mass media and the change from biological sortation to social gender. This had an impact on “androgynous” styles in the 1970s and “glam” looks in the 1980s, which transformed into the “unisex” concept, described as suitable for both males and females (Bardey et al., 2020 ; Mills, 2015 ). Lee ( 2021 ) highlighted that unisex is different from genderless fashion in terms of distinguishing methods to differentiate gender; it is based on the gender distinction between men and women, and embraces the same design, whereas the genderless style does not dichotomize gender and encompasses a wide spectrum of gender identities.

Millennials and Generation Z have different values and lifestyles than the previous generations, particularly in relation to the traditional gender role distinction. As the leading groups of trends and consumption, they want to define and express their gender identity on their own because of their great desire to express their social influence and external images (Wertz, 2018 ). A recent survey indicated that 38% of Generation Z and 27% of Millennials, who will account for $143 billion purchasing power in the next 4 years (Anyanwu, 2020 ), agreed that an individual cannot be judged or determined by gender. With this in mind, high-end brands projected runway models indistinguishable in terms of gender, while masstige brands introduced retail strategies to eliminate the distinction between men’s and women’s products in stores or launched new public brands. In addition to women’s and men’s wear brands, one major children’s wear brand removed boys’ and girls’ labels from the store floor plan to reinforce the extensive product choice preferences (Newbold, 2017 ), eliminating gender stereotypes for their customers.

Text-mining analysis

Text-mining is an artificial intelligence technology that utilizes natural language processing to obtain meaningful information from vast unstructured textual data (Liu et al., 2011 ; Nishanth et al., 2012 ) or to estimate uncertain patterns (He et al., 2013 ). It includes the processes of editing and organizing several documents composed of words, characters, and terms (Nishanth et al., 2012 ). As a big data analytics extension technique, text-mining analysis examines large and varied data documents to uncover nontrivial information such as unknown correlations, customer preferences, and market trends that aid in the best decision making in the business (Hashimi et al., 2015 ). In particular, after the rapid increase in social network services, social media mining has been adopted to understand and interact with customers and gain a competitive advantage. According to Reports and Data ( 2020 ), the text-mining market will reach $16.85 billion by 2027 owing to the high rise in the adoption of social media platforms, and many business organizations have deployed text-mining analytics to transform data into competitive knowledge.

Many previous researchers have used text-mining techniques to analyze consumers’ brand sentiments (Mostafa, 2013 ), to measure consumer preferences (Rahman et al., 2014 ), and to survey the commerce trend on social media (Shen et al., 2019 ). Regarding fashion, Lang et al. ( 2020 ) evaluated consumers’ fashion-renting experiences through in-depth text analysis using LDA-based topic modeling, and Dang et al. ( 2016 ) classified fashion content texts from social networks using a support vector machine. Choi and Lee ( 2020 ) researched ethical fashion using text-mining with network analysis, and Lee et al. ( 2018 ) analyzed luxury fashion brands and mass brands’ evaluations of Twitter messages. Owing to the strong capabilities of text-mining techniques, many attempts have been made to analyze social media content to yield valuable findings on consumers’ behavior and sentimental values toward a brand. However, previous studies have dealt with relatively limited information, focusing solely on consumers’ perceptions of genderless fashion trends. Consequently, to analyze mainstream fashion trends and understand consumers’ interests, a text-mining method was employed for this study.

LDA-based topic modeling

In this study, LDA-based topic modeling (Blei et al., 2003 ) was utilized to extract customers’ perceptions of the genderless fashion trend on social media. Topic modeling allows the user to detect and summarize latent semantic structures, and LDA is the most common method for clustering abstract topics that occur in a collection of documents (Nabli et al., 2018 ). LDA assumes that documents consist of a mixture of topics, and that topics generate words based on probability distributions. As shown in Fig.  1 , Blei ( 2012 ) explained the LDA model algorithm as follows: the square boxes are called “plates” and “N” stands for a collection of words collected within a document, “D” for a collection of documents, and “K” for a set of topics. The circles represent probability parameters, and the node “ \({W}_{d,n}\) ” is observed as a word in the document; while topics, topic distributions, and topic assignments are not revealed. There are full words (“ \({W}_{d,n}\) ”) in the numerous documents (“D”) collected by the researchers, assuming that each word has a corresponding topic (“ \({Z}_{d,n}\) ”).

Graphics of document generation for LDA algorithm (Blei, 2012 , p. 81)

There are many different topics embedded in each document, and the distribution of topics differs. Therefore, LDA deduces the latent variables of the document through the words contained in the document and generates a specified number of topics from the document stack through the Dirichlet distribution. In this study, LDA-based topic modeling was adopted to understand the consumer-driven content of genderless trends in social media networks. Various researchers have explored LDA-based topic modeling to discover new knowledge about consumers’ communication. Bastani et al. ( 2019 ) analyzed the customer complaints of national financial agencies, and fashion design participants were analyzed to observe research trends (Jang & Kim, 2017 ). Gray et al. ( 2015 ) developed an LDA-based text-mining methodology to define fashion styles obtained from online apparel information with affiliate networks. In contrast to the approach of consumers’ research in the fashion industry conducted in the various studies discussed above, genderless fashion trend research is unknown. Therefore, we developed a primary approach to discover consumers’ preferences and interest in social media toward the genderless fashion trend with an LDA-based topic modeling proposal.

Data collection

We obtained data from the largest Korean search portal engine—NAVER—focusing on consumers’ online community and blog reviews for 3 years since the genderless fashion trend began (Menkes, 2018 ): from January 1, 2018 to December 31, 2020. To gain insights related to genderless fashion trends among consumers’ posts and communication, a search of the keyword “genderless fashion” was conducted, which produced 9722 posts. The web crawling program language Python 3.7 ( http://www.python.org ) was used to build the model. Consumers’ posting date, platform type, title, contents, and link information were gathered; the text-mining objects were title and content. Data were pre-processed to cleanse them of undesirable words, special characters, non-Korean words, and punctuation. Afterward, word tokenization was lemmatized and converted into the minimal unit of meaning formats such as nouns, adjectives, verbs, or adverbs in their dictionary forms. These words were accumulated in the bag-of-words model (Zhang et al., 2010 ), which represents a multiset of words regardless of word order. Words that occurred in 80% of the documents and in fewer than five documents were removed (Jauhari et al., 2020 ). Moreover, search keywords’ implied synonym words such as gender-neutral, gender fluid, gender diversity, and fashion that could have affected the results, were removed. Hence, only meaningful words relevant to the generation of the topics remained.

Measurement and research process

To perform the research data analysis, we used Python 3.7 to perform data processing and applied LDA-based topic modeling. The detailed research process flowchart, performed over four steps, is shown in Fig.  2 . First, the web crawling technique was performed using the keywords “genderless fashion” to collect consumers’ review posts on NAVER’s blogs and online communities. The number of keyword changes over 3 years was evaluated to estimate consumers’ preferences and interests. Second, data cleansing and preprocessing of unstructured text data were conducted to eliminate irrelevant or generic words. Consequently, the entire text document was into split into individual words, which is known as word tokenization. Then, stop-word removal and word lemmatization were applied to filter meaningful words on natural language data. For example, onomatopoeic words (“haha,” “nope,” etc.), emoticons, propositions (“the,” “a,” etc.), inappropriate words (“recently,” “more,” “really,” etc.) were removed. Then, the top 50 text frequency words and bigram rates were analyzed. Next, to analyze topic modeling based on the LDA algorithm, a topic model number was defined by applying the measure of perplexity and coherence parameters. Then, each topic model’s labeling was selected based on the observed keywords and representative documents associated with the high weight of the topic. In this step, an IDM was applied to determine the degree to which each topic was related to other topics and the degree of similarity between topics. Fourth, to measure the topic trend change over the past 3 years, we investigated the number of consumers’ posts containing each topic. Subsequently, a time-series linear regression analysis was performed to confirm the annual trends of the topic.

Research data processing flowchart

Status of consumers’ posts and media news about genderless fashion

We compared the number of posts over 3 years from 2018—when genderless fashion was cited as a major trend—to 2020 by crawling consumers’ blog and online community posts on NAVER and media news posts. In these 3 years, 9722 pieces of consumer-generated content about genderless fashion were uploaded, and the yearly trend showed that the number of online posts had steadily increased: 1435 postings in 2018, 2538 postings in 2019, and 5749 postings in 2020. Consistently, there were 104 online news articles in 2018, 524 in 2019, and 1008 in 2020. As shown in Fig.  3 , both consumers’ and media news outlets’ posts continued to increase, especially in 2020, when it doubled compared to 2019. Therefore, it was confirmed that consumers’ interest in genderless fashion has grown rapidly.

The number of consumers’ posts and media news for 3 years (2018–2020)

Text frequency

To analyze the key terms related to genderless fashion, we combined the titles and contents of consumers’ posts. Data cleansing and preprocessing were essential for generating meaningful topic modeling. We performed word tokenization to analyze the text dataset as a morpheme, turning it into the smallest unit of meaning through natural language processing (Bastani et al., 2019 ). To filter out unnecessary words, stop-word removal (Nabli et al., 2018 ) was conducted, eliminating undesirable fragments such as punctuation, single-letter words, grammatical errors, and numbers. The resulting set was extracted with only nouns and adjectives after word lemmatization, maintaining the basic dictionary form of a word after removing the inflectional endings. Accordingly, the frequency value of the occurrence of all extracted words was obtained, except for the words that appeared more than 80% of the time or in less than five documents. The top 45 keywords based on the extracted frequency are listed in Table 1 . The results of visualizing the top 50 of the highest frequency keywords from 4051 word lists is shown in Fig.  4 . Words with a high frequency of occurrence are expressed as bigger and bolder in the word cloud. To review the top-ranking frequency occurrence words, genderless fashion-related brands (e.g., Gucci, Olive Young) and merchandise (e.g., product, design, style, item, bag, pants, shirts, store, jacket, sunglasses, knit) were extracted in the fashion and beauty industry (e.g., clothes, cosmetics, hair, makeup, jewelry). Concerning color, black was the highest, followed by white, blue, gray, and green (in order).

Word cloud visualization results

N-gram analysis

We attempted to improve text classification by determining which words were connected in the unigram dataset. Bigram means that two-word phrases belong to the n-gram analysis method to generate contiguous word pairs in the corpus and gain the contextual word association (Crossley & Louwerse, 2007 ). It is also useful to compare bigrams in two different sentences because it allows us to identify the similarities and various types of words in context. The results of the top 35 bigrams from 6703 two-word lists are shown in Fig.  5 . Cosmetics (e.g., super hyalon, skincare, mask pack, moisture line, hand cream, basic cosmetics, skin moisturizer, BB cream), fragrance (e.g., perfume recommendation, body spray, Eau de perfume), fashion brands (Maison Martin Margiela, Thom Browne, Zadig & Voltaire, Push the Button, Bottega Veneta), and style-related items (oversize, wide pants, jogger pants, denim pants, wild slacks) appeared accordingly.

Results of the bigram analysis

Select the optimized number of topics

We analyzed the coherence score and perplexity score to evaluate the optimal number of topics as quantitative diagnostic metrics. The coherence score measures how frequently the top keywords of each topic co-occur to identify which of the top words contributes the most relevant information to the given topic (Blair et al., 2020 ). The perplexity score is an indicator of whether the topics are clearly classified, and it is assumed that the smaller the value, the better the actual literature results reflected by that topic (Inglis & Foster, 2018 ). Therefore, the smaller the perplexity value and the larger the coherence value, the more semantically consistent the topic model that is constructed. By calculating the perplexity and coherence values for all the words in the web-crawled document, we ensured that the LDA-based model achieved maximum coherence score and minimum perplexity score with the number of topics ( k  = 18; Fig.  6 ).

The interpretability of topic modeling

Topic selection and labeling

The IDM for topics extracted from topic modeling in this study is shown in Fig.  7 . IDM is a diagram that shows the weight of a topic and the distance between topics, and makes it possible to understand the degree of relevance of each topic to other topics (Sievert & Shirley, 2014 ). The topic view is on the left, and the term bar charts with 18 topics selected are on the right. Selections are linked so that the researcher can briefly demonstrate the aspects of the relationship of the topic terms. The distribution of topics related to the subject shows that the proportion of each topic is similar, which confirms that the deviation is non-significant. Furthermore, because the topics do not altogether overlap with each other, the association between the topics is low, which means that each topic is divided into a relatively clear research area.

Intertopic distance map (IDM) of genderless fashion LDA topic modeling

We classified consumers’ perceptions of genderless fashion for 3 years by identifying keywords derived using LDA-based topic modeling algorithms and documents with a high weight of the topic. Table 2 shows the topic number corresponding to the keywords of the topic, the weight of the topic in the document, the date of the posting, and the title as an example from topic number one to five.

The topic labeling process was discussed and confirmed by five experts in the fashion and textile industries. Table 3 represents 18 topics and top keywords for genderless fashion trend topic modeling in accordance with the analysis of major keywords and documents with high topic weight in previous works.

Time-series analysis

To understand the trend of each topic by year, the year was applied as the independent variable, the weighted average value of the topic by year was used as the dependent variable, and a series linear regression analysis was performed. In addition, the values of the regression coefficient and the significance probability of the linear regression analysis were verified as criteria for judging the rise and fall of trends by year. Only those topics with a significant p-value (< 0.05) and a Durbin–Watson value greater than 1.5 and less than 2.5, if the regression coefficient value was positive, were classified as a “hot topic”; while, if negative, they were classified as a “cold topic,” and topics for which no meaningful result could be derived were classified as a “neutral topic” (Griffiths & Steyvers, 2004 ).

The hot topic that has been rapidly growing among consumers in the genderless fashion trend for the last 3 years was “perfume and scent.” In contrast, “bags,” “all-in-one skin care,” and “set-up suit” (i.e., a casual outfit that can be used together or worn separately with a jacket and pants) were cold topics, indicating that consumers’ interest in these gradually declined. The remaining topics were classified as neutral topics because they were non-significant in the time-series analysis (see Table 4 ).

The concept of gender diversity has begun to expand with the trend of focusing on individuals’ unique taste importance. Consumers began to self-define and express their gender identity and discuss it through social media channels. With access to massive amounts of unstructured data from blog and online community reviews, the purpose of this study was to identify consumers’ perceptions and preferences regarding genderless fashion based on the text-mining analysis approach. In particular, we selected the LDA-based topic modeling method to examine a large amount of qualitative information obtained from consumers’ posts.

Text data were collected from the search keywords “genderless fashion” on the NAVER portal site from January 1, 2018 to December 31, 2020. A total of 9722 postings were collected, word tokenization was conducted after data preprocessing and cleansing, and word frequency and n-gram analysis were performed to remove stop words. To determine the optimal number of topics, perplexity and coherence scores were evaluated, and 18 topic keywords were finally selected through the LDA algorithm analysis. To select each topic, the contents of the representative documents with a high weight of the topic were reviewed. Finally, a time-series regression analysis was performed to understand the trend of topics by year, and the hot topic of the uptrend and the cold topics of the downtrend were selected.

First, to review the text frequency and n-gram analysis results, our study findings revealed that consumers are interested in external images as independent individuals rather than meeting other people’s standards, and often talk about fashion brands (“Gucci,” “Maison Martin Margiela,” “KIVULI,” “Zadig & Voltaire,” “Push the Button,” “Bottega Veneta”), items (“clothes,” “bag,” “pants,” “shirts,” “jacket,” “sunglasses,” “jewelry,” “style”), and cosmetic and perfume products (“skin,” “sheet mask,” “skin moisturizer,” “makeup,” “body spray,” “body mist,” “hand cream,” “Eau de perfume,” “Super hyalon,” “BB cream,” etc.) related to genderless fashion. This indicates that consumers’ recommended products and styles of genderless fashion are affected by the diverse fashion labels collection. Consumers are interested in the coordination and design details of certain brand items related to the gender-neutral concept. In particular, beauty cosmetics and fragrances, which are dominated by female-oriented stereotypes, are now being highlighted, regardless of gender division, owing to the influence of genderless fashion trends among consumers. Kim ( 2021 ) stated that many brands are launching gender-free cosmetics, which has become an opportunity for male consumers’ interest in skin care to become specialized. These results can be understood in the same context as those of previous studies (Newbold, 2017 ; Reis et al., 2018 )—that genderless fashion is a response to the needs of the fluid market niche increase aside from femininity and masculinity stereotypes. Wertz ( 2018 ) also indicated that Millennials and Generation Z’s consumption trends value individuality and practicality rather than gender. Concerning color, An ( 2018 ) as well as Hong and Joo ( 2020 ) mainly pointed out that “pink” was the trendy color on gender-neutral menswear collections; however, we discovered that achromatic colors such as “black,” “white,” “gray” mentioned mostly among the consumers. The results suggested that the men’s collection combines colorful colors into genderless fashion, but our study confirmed that consumers prefer dark colors.

Second, 18 topics were analyzed from LDA-based algorithms and 13 topics were classified as fashion categories (i.e., “summer jewelry,” “men’s fashion & grooming,” “hairstyle & color,” “high-end fashion’s basic item,” “bags,” “FW fashion,” “collaboration,” “genderless concept models,” “luxury brand sunglasses,” “pants style,” “set-up suit,” “domestic eyewear brand,” and “capsule collection”), while 5 topics were classified as beauty and fragrance categories (i.e., “moisturizing skin care,” “perfume and scent,” “cosmetic beauty brands,” “body spray,” and “all-in-one skin care”). The fashion industry has provided designs and services differently according to gender (Szmydke, 2015 ); however, new product development and rebranding strategies have emerged in accordance with the gender fluidity change followed by consumer-driven change. Previous studies (Hong & Joo, 2020 ; Shin & Koh, 2020 ) have investigated genderless fashion in terms of design and style based on the collection images. Kim ( 2020 ) and Yang ( 2020 ) researched genderless trends in cosmetic brands’ advertisements. Hence, our results indicated that the main interest in the genderless concept of current consumers lies in the fashion and beauty fields by expanding existing qualitative studies using big data. In particular, South Korea’s male cosmetics consumption is number one in the global market (Im, 2016 ), which is consistent with our results. The effect of the gender fluidity phenomenon on the beauty industry was also revealed in our results (e.g., “super hylaon,” “LAKA”) as the genderless-only cosmetic brands.

Third, our time-series linear regression analysis revealed a hot topic (“perfume and scent”) and three cold topics (“bags,” “all-in-one skin care,” and “set-up suit”), while the rest were presented as neutral topics. The topic that has continuously grown among consumers in relation to the genderless fashion trend in the last 3 years has been “perfume and scent.” Certain brands of seasonal perfumes (“Jo Malone,” “Diptyque”) and scents (“Eau de perfume,” “common”) were mentioned among the consumers. As “gift” suggests in the topic, genderless fragrances have a sensuous and soft scent, which are easy to give as a present regardless of gender. According to BBC’s report, gender fluid fragrances have surged in popularity, increasing to 51% as compared to 17% in 2010 (Bolongaro, 2019 ). In contrast, “all-in-one cosmetics” attracted high consumer interest in the beginning, but they gradually declined in popularity. The high demand for “moisturizing skin care” indicates that male consumers used all-in-one products because of their convenient usage in the past; however, now they can choose exclusive genderless products, allowing them to choose their own products by function and purpose (Hong, 2020 ).

Considering the changes in consumers’ perception of fashion products, interest in bags has been declining. “Tote bags” and “size” were considered because of users’ light-weight concerns, and they referred to the brand look-book (“Beanpole”) or fashion week collection (“Juun. J,” “Push the Button”). Yoo ( 2020 ) explained that handbag brands have expanded the range of tote bags, particularly because of their unique characteristics as well as the effect of genderless fashion trends. The “set-up suit” topic also showed a steady decline. Business casual suits are tailored (“custom”) or users prefer practical styling with a comfortable pattern (“comfort”) along with the demand for female consumers. Demand for women’s suits increased with the growth of genderless fashion, but it seems that the demand has decreased owing to the recent increase in telecommuting under the influence of the COVID-19 pandemic.

Conclusions

Existing research on genderless fashion trends has focused on the style characteristics shown in collections and advertisements (Hong & Joo, 2020 ; Kim & Lee, 2016 ; Yang, 2020 ). Therefore, there is a possibility that our subjectivity was involved and consumers’ perspectives were not included. Recently, the number of consumer-led products and brands has increased remarkably; therefore, consumers’ recognition of fashion trends is critical as they affect the industry enormously. A few studies have focused on consumer reviews on fashion subjects using the big data analysis method. Lang et al. ( 2020 ) investigated consumers’ fashion rental experiences, and Choi and Lee ( 2020 ) studied ethical fashion perception. However, this is one of the first studies that deals with consumers’ preferences for genderless fashion trends by applying text-mining and LDA-based topic modeling techniques. Through this computer-aid method, researchers can extract hidden implications or estimate patterns from a natural language dataset (Hashimi et al., 2015 ). To analyze and understand consumers’ behaviors in real-time is becoming essential; thus, we investigated consumers’ unstructured data in fashion trends analysis.

This study has managerial implications for product planners who develop merchandise based on recent trends. We found that consumers have a high interest in brands and products related to perfume, fashion, and cosmetics in terms of genderless fashion trends that can make their individuality stand out despite gender division. Therefore, when a product planner plans a merchandising product group targeting consumers, these product categories can be prioritized. In particular, given that the topic of “perfume and scent” has been on the rise among consumers, strategic promotions and collaboration with genderless fragrance brands can also be conceived.

The limitations of this study and suggestions for future research are as follows.

This study collected the text documents from consumers postings of blogs and online communities, therefore it is not focused solely on a specific generation. Because the genderless fashion is popularly accepted by Millennials and Generation Z (Anyanwu, 2020 ), it would be meaningful to closely consider the opinions of various generations in the future. Continuous research is expected to be conducted in the field of fashion and textiles, because text-mining research is still scarce and at its nascency. For future research projects, it is necessary to analyze not only consumer opinions related to genderless fashion trends, but also related articles introduced in the mass media. If in-depth analyses can be conducted in the aspects of social interest and the business industry, more insights can be gained to enhance the proposed model in this study.

Availability of data and materials

The datasets used and analyzed during the current study are available from the first author on reasonable request.

Abbreviations

Spring summer

Fall winter

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This work was supported by the Ewha Womans University Research Grant of 2020.

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HK originated the research idea and carried out the research. IC discussed the results with HK and MP helped with the improvement of the manuscript. All authors read and approved the final manuscript.

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Hyojung Kim: Ph.D. candidate, Department of Fashion Industry, Ewha Womans University, 52, Ewhayeodae‑gil, Seodaemun‑gu, Seoul 03760, South Korea.

Incho Cho: Visiting Professor, Department of Fashion Industry, Ewha Womans University, 52, Ewhayeodae‑gil, Seodaemun‑gu, Seoul 03760, South Korea.

Minjung Park: Professor, Department of Fashion Industry, Ewha Womans University, 52, Ewhayeodae‑gil, Seodaemun‑gu, Seoul 03760, South Korea.

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Kim, H., Cho, I. & Park, M. Analyzing genderless fashion trends of consumers’ perceptions on social media: using unstructured big data analysis through Latent Dirichlet Allocation-based topic modeling. Fash Text 9 , 6 (2022). https://doi.org/10.1186/s40691-021-00281-6

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• Latent Dirichlet Allocation-based topic modeling
• Text-mining
• Social network analysis
• Fashion big data analysis

ORIGINAL RESEARCH article

Introducing a gender-neutral pronoun in a natural gender language: the influence of time on attitudes and behavior.

• 1 Department of Psychology, Stockholm University, Stockholm, Sweden
• 2 Department of Psychology, Gothenburg University, Gothenburg, Sweden
• 3 Department of Psychology, Lund University, Lund, Sweden

The implementation of gender fair language is often associated with negative reactions and hostile attacks on people who propose a change. This was also the case in Sweden in 2012 when a third gender-neutral pronoun hen was proposed as an addition to the already existing Swedish pronouns for she (hon) and he (han) . The pronoun hen can be used both generically, when gender is unknown or irrelevant, and as a transgender pronoun for people who categorize themselves outside the gender dichotomy. In this article we review the process from 2012 to 2015. No other language has so far added a third gender-neutral pronoun, existing parallel with two gendered pronouns, that actually have reached the broader population of language users. This makes the situation in Sweden unique. We present data on attitudes toward hen during the past 4 years and analyze how time is associated with the attitudes in the process of introducing hen to the Swedish language. In 2012 the majority of the Swedish population was negative to the word, but already in 2014 there was a significant shift to more positive attitudes. Time was one of the strongest predictors for attitudes also when other relevant factors were controlled for. The actual use of the word also increased, although to a lesser extent than the attitudes shifted. We conclude that new words challenging the binary gender system evoke hostile and negative reactions, but also that attitudes can normalize rather quickly. We see this finding very positive and hope it could motivate language amendments and initiatives for gender-fair language, although the first responses may be negative.

Introduction

Language is seen as an important tool for determining gender, i.e., if something is being perceived as feminine or masculine ( Boroditsky et al., 2003 ; Stahlberg et al., 2007 ), where gender most often imposes a dichotomy ( Ansara and Hegarty, 2014 ). This implies that language also could be used as a tool for establishing gender-equality and to challenge gender perceptions. In Western culture and languages, actions toward gender-fair languages have primarily focused on making women more salient and reducing the so-called male bias (for a review, see: Stahlberg et al., 2007 ). For example, in the seventies, the feminist movement questioned the use of a generic masculine pronoun to refer to people in general ( Moulton et al., 1978 ; MacKay, 1980 ; Phillips, 1981 ; Murdock and Forsyth, 1985 ).

The literature describes two types of gender fair language: “balancing/feminization’ and ‘neutralization.’ Feminization implies the use of gender-appropriate forms, and is more often used in languages with grammatical gender (e.g., German, French), for example by adding feminine versions to masculine titles (e.g., Lehrer/Lehrerinnen for masculine and feminine teachers; Stahlberg et al., 2001 , 2007 ). Neutralization is more commonly employed in so called ‘natural gender languages’ (e.g., English, Swedish, Norwegian), and implies that gender-neutral forms are preferred over gendered forms. Examples are using the word parents instead of mum and dad , and humankind instead of mankind (at least in official records).

In Swedish, a recent action was to introduce the gender-neutral third person pronoun, hen , as a complement to the Swedish words for she (hon) and he (han) ( Ledin and Lyngfelt, 2013 ; Milles, 2013 ; Bäck et al., 2015 ). In current time the word first appeared in 2012, figuring in a children’s book. In July 2014, it was announced that hen should be included in 2015th edition of The Swedish Academy Glossary (SAOL) constituting the (unofficial) norm of the Swedish language ( Benaissa, 2014 ; Fahl, 2014 ), after what had been a long, sometimes offensive and heated debate in the media. No other language has so far added a third gender-neutral pronoun that actually has reached the broader population of language users, which makes the situation in Sweden unique. This article presents a review of the process on how hen became implemented, including the arguments that were put forward from opponents and proponents, respectively. We present data on attitudes toward hen during the recent 4 years and study how time is associated with the attitudes and actual use of the word.

The word hen is very similar to, and pronounced as, the Finnish gender-neutral pronoun hän with the same meaning, i.e., describing any person no matter their gender – although the language of Sweden’s cultural neighbor Finland belongs to the language group without gendered third-person pronouns ( Stahlberg et al., 2007 ; Prewitt-Freilino et al., 2012 ). Even though the debate about hen took off in 2012, the word was first mentioned as early as in the 1960’s ( Milles, 2013 ), when linguists proposed that a gender-neutral pronoun would be a more rational choice in comparison to a generic he or using double forms (i.e., he and/or she ). However, these discussions were more of an academic nature limited to small linguistic communities and did not reach a broader public ( Milles, 2013 ). In the beginning of the 21st century people in LGBT-communities (Lesbian-, Gay-, Bi-, Trans-) began to use hen , both for people outside the gender dichotomy and as a way of diminishing the salience of gender. A similar movement has been found in the English language, among linguists and among transgender communities, where more than 80 different forms of gender-neutral pronouns have been proposed. Today, one trend in English is to use gender-neutral pronouns such as zie and hir ( Baron, 1986 ; Ansara and Hegarty, 2014 ; Love, 2014 ), although these words have not been very widespread outside the LGBT-communities ( Crawford and Fox, 2007 ).

When the debate took off in 2012, the spark that started it was the publishing of a children’s book ( Lundquist, 2012 ) that used hen to denote the main character of the book, instead of using a gendered pronoun. The author and the publisher also wrote a debate article in one of the largest newspapers in Sweden together with Karin Milles, a linguist researcher and advisor of gender-fair language planning, arguing for the introduction of a gender-neutral pronoun ( Milles et al., 2012 ; Milles, 2013 ). Advocates of the word argued that children are too much influenced by gender categories, where non-gendered pronouns allow them to visualize and develop their stories much more freely ( Milles et al., 2012 ). Antagonists argued that children listening to such non-gendered stories would be disoriented not knowing their gender, and that having a (binary) gender (i.e., being a girl or a boy) is something to be proud of ( Lagerwall, 2012 ). At this point in 2012, the use of hen was highly controversial, which is illustrated by an incident when a columnist in one of the largest newspapers used hen. The reactions led the management of the paper to apply a policy against using hen in its news reporting ( Cederskog, 2012 ). In contrast, an entertainment magazine changed all third personal pronouns into hen in their second issue in 2012 ( Milles, 2013 ). Later in 2012, the Language Council of Sweden ( Språkrådet ) providing official recommendations about Swedish language, recommended that hen should not be used, since it could be irritating and conflict with the content in the text. This illustrates a common argument against gender-fair language reforms – where new forms are commonly described as awkward and potentially steeling attention from the message ( Blaubergs, 1980 ; Parks and Roberton, 1998 ). For example the publication manual by American Psychological Association (APA) includes guidelines against sexist language stating that ‘…combination forms such as he/she or (s)he are awkward and distracting and are not ideal’ ( APA, 2012 , p. 74). APA recommends the use of ‘neutral’ words such as the person , or they . However, both they and the person might be associated with gender bias (most often a male bias), which existing literature on gender-fair language has shown is a robust phenomenon (e.g., Hyde, 1984 ; Stahlberg et al., 2001 , 2007 ; Lenton et al., 2009 ; Garnham et al., 2012 ). According to the literature, a gender bias is described as the situation when care is taken to express gender-fairness in the language and people nevertheless seem to create biased perceptions where they associate the gender-neutral expressions with either a masculine or a feminine gender. For example in English, the word they could be used as an assumed generic form ( Gastil, 1990 ; Strahan, 2008 ), but in a study where the generic he was replaced by they , children still more often associated they with a man ( Hyde, 1984 ). Also, supposedly neutral words such as person, mankind , or even human have been associated with a male bias ( Stahlberg and Sczesny, 2001 ; Douglas and Sutton, 2014 ; Bäck et al., 2015 ). These results imply that the creation of new words may be needed to override gender and cisgender bias, although it might take some time for language users to get used to them. However, the implementation of newly formed words is not an easy and straightforward enterprise, maybe especially not for a pronoun. From a linguist perspective, it has been argued that pronouns changes more slowly than other words because they belong to the so called ‘function words’ or ‘closed words classes’ ( Milles, 2013 ; Paterson, 2014 ). Function words are used to organize the grammatical structure in a sentence and their meaning is only derived from how they are used in context ( Chung and Pennebaker, 2007 ; Milles, 2013 ). Pronouns are organized in a grammatical system, thus adding a new word challenges the whole system ( Paterson, 2014 ), which is not the case when nouns or verbs are added to a dictionary, or when feminine forms of professional roles are added to masculine forms.

Hen can be used in two different ways: either as a third-person pronoun in situations including general descriptions of an individual whose gender is unknown or is considered as irrelevant, or as a third-person pronoun in situations where the described person is not gender-neutral but describing someone identifying themselves outside the gender-dichotomy ( Milles, 2013 ; Bäck et al., 2015 ). For people with a non-binary gender identity, double forms of pronouns (i.e., he/she ) and guidelines for gender-fair language are excluding ( Ansara and Hegarty, 2014 ). For example ‘APA’s binary descriptions of gender reinforce ethnocentric gender ideology that assumes ‘woman’ and ‘man’ are the only possible genders’ ( Ansara and Hegarty, 2014 , p. 264).

The different uses of hen align with the arguments from its proponents and antagonists. Representatives from LGBT-communities propose a gender-neutral pronoun since it dissolves gender expectations and includes all individuals no matter their gender-identity ( Milles, 2013 ). These arguments have met the strongest reactions where the proponents have been targeted with offensive and hostile attacks. The antagonists have argued that queer people and feminists are trying to change biology, and that gender is one of the most natural categories. A maybe less controversial argument is that the gender-neutral pronoun hen is a shorter and more efficient way in comparison to double forms. Accordingly, hen could be used when gender is unknown, or as a generic pronoun. These arguments have been put forward by some feminists and linguists ( Milles, 2013 ). Yet, other groups of feminists have been negative toward a gender-neutral pronoun since, they claim, it could be a way of diminishing women. For example, a well-known Swedish feminist and professor in literature has argued that the feminine gender is obscured by the word hen ( Brattström, 2014 ). Hence, the use of hen and its consequences have not been agreed on, and disputes reside even within the feminist movement.

After 2012 followed a time with progress toward a more official implementation. In 2013, the Swedish Language Council (språkrådet) changed their recommendation and proposed that hen could be used as a gender-neutral pronoun, although with caution because it may distract attention from the message. The next year, in 2014, it was announced that the word should be included in the 2015th edition of the SAOL that constitutes the (unofficial) norm of the Swedish language ( Fahl, 2014 ). In this year, the language council also formally changed their guidelines for gender fair language in public authorities, and included hen as an alternative to other neutral or gender balanced forms. Using hen is still not mandatory in official publications; each authority decides themselves whether to use it in public documents or not, and so far very few do ( Ledin and Lyngfelt, 2013 ; Olsson, 2015 ).

In the Swedish media, the word has become more commonly used ( Ledin and Lyngfelt, 2013 ; Milles, 2013 ). For example, during the first 6 months of 2012 hen was mostly seen in a vivid debate about the word itself, while during the second half of 2012, the word was actually used in texts unrelated to the debate about the word, that is, as a gender-neutral pronoun. In one of the bigger newspapers in Sweden the occurrences of hen increased over a year, from 1 in 2010, to 9 in 2011 and to 113 in 2012 ( Ledin and Lyngfelt, 2013 ). This means that though hen still is rare, an increase is undisputable. The analyzed paper is among one of the conservative papers, thus it was presumed that occurrences in more progressive papers may be higher, however, a quantification of this hypothesis has not yet been done. In an effort to understand how the media used the word (generic or transgender), Ledin and Lyngfelt (2013) showed that 15% of the occurrences were related to transgender use, whereas 85% corresponded to a practice when gender was unknown, irrelevant or, as a generic form.

Since the pronoun is new, there is still limited research about how the word is perceived and what consequences it might have. A few studies have tested whether hen decreases a male- and cisgender bias. In one study ( Wojahn, 2013 ), 150 participants read a story about a cellphone user, referring to the person either as he, he/she, hen , or he or she . Results showed that hen evoked the least male bias and also less cisgender bias. In a previous study, we have shown that a person described as hen was more often remembered as a person of unknown gender, whereas a person described by a neutral word is more often remembered as having a masculine gender ( Bäck et al., 2015 ).

Gender-fair language is often implemented over several years. It commonly starts with activist movements who propose a change. Since people have a preference for status quo ( Jost et al., 2004 ; Samuelson and Zeckhauser, 2005 ; Crandall et al., 2009 ), and a preservation of traditional gender arrangements ( Jost et al., 2008 ), new linguistic gender word forms may be negatively reacted upon. Proponents of non-sexist language have been attacked, words have been defined as being linguistically wrong or awkward ( Blaubergs, 1980 ; Parks and Roberton, 1998 ), and feminine occupational titles have been evaluated more negatively than their masculine traditional form ( Formanowicz et al., 2013 ). However, familiarity and exposure breeds liking ( Zajonc, 1968 ), thus the attitudes may change the longer gender-fair language has been used ( Eidelman et al., 2009 ; Moreland and Topolinski, 2010 ). Whether such attitude change occurs also for gender-neutral pronouns within a country has not been studied before.

In studying the implementation process of gender-fair language reforms and the consequences on population attitudes and use, it is important to consider variables traditionally associated with negative attitudes toward gender fair language. If we are to make a claim that gender fair language reforms will be successful, an important task for the present research is to show that time in use is important to include when studying attitudes and frequency of use, together with other potential explanations. Previous research has identified a number of predictors of attitudes to gender-fair language and the following section will provide an overview of these.

Sexism in terms of attitudes toward gender equality has been identified as a predictor of negative attitudes toward gender-neutral language use (cf. Sarrasin et al., 2012 ), together with political orientation in terms of right-wing conservatism ( Formanowicz et al., 2013 ; Norton and Herek, 2013 ). Also in the ‘hen- debate,’ more left-wing than right-wing politicians used hen and promoted that hen should be included in the Swedish Dictionary ( Milles, 2013 ). In Sweden, there are feminist movements both on the left and right of the political map, and in the last election more politicians than ever before openly stated that they considered themselves to be feminists ( Öhberg and Wängnerud, 2014 ). Thus, feminist values would be associated with more positive attitudes, no matter of political orientation. Jacobson and Insko (1985) showed that feminist attitudes were associated with a higher use of gender fair language, such as using more double forms of pronouns. Feminist attitudes also mediated the effect between gender and attitudes toward gender fair language. Hence, even though the literature suggests that political right-orientation would predict negative attitudes, this is not entirely straight-forward, and we suggest that interest in gender issues may be a potent predictor as well.

Gender (as coded in a binary system feminine/masculine) as a predictor of attitudes to and use of gender-fair language has been inconclusive so far. Some studies have shown that women are more positive than men to gender-fair language (i.e., Prentice, 1994 ; Sarrasin et al., 2012 ) others have shown no differences (i.e., Koeser and Sczesny, 2014 ). Women tend to use gender-fair language more often than men ( Koeser and Sczesny, 2014 ), and are more easily influenced to adjust to gender-fair language ( Koeser et al., 2014 ). Notably, using a gender-neutral hen is not as clearly beneficial for women, as compared to other forms of gender-fair language (e.g., balancing masculine and feminine form, or avoiding masculine generics). Hence, it is not certain how, or even if, gender will affect attitudes to hen . Since hen challenges the binary gender system that is prevailing in most cultures, it could be argued that some individuals will show stronger resistance than others, depending on how important the gender system is to them. We argue that biological gender is not of greatest importance in this case, but rather the extent to which one identifies as a woman or a man, and how important this identification is. Indeed, arguments in the debate have touched upon such issues; for example, heterosexual people have argued that they are negative toward the word hen because it ‘restricts their right to express their gender identity,’ and that ‘romance between men and women will suffer’ ( Lagerwall, 2012 ). Very few studies have investigated strength of gender identity as being a woman or a man in relation to gender-fair language. These studies have used forms of BEM Sex Role Inventory (BMSRI; Bem, 1974 ). The studies showed that a masculine gender identity (no matter of biological gender) was associated with more negative attitudes ( Rubin and Greene, 1994 ), while androgynous gender identity has been associated with more positive attitudes, and higher use of gender-fair language ( McMinn et al., 1990 ; Rubin and Greene, 1991 ). Given that Sweden is an egalitarian society, where the distinction between femininity and masculinity is no longer as strongly rooted in traditional feminine and masculine roles, we believe that the strength of gender identity is a better measure than gender roles as measured by BMSRI ( Bem, 1974 ).

Finally, we believe that age will predict attitudes and the use, because younger people are more susceptible to new ideas and to challenge traditional roles, than older people are ( Visser and Krosnick, 1998 ; Eaton et al., 2009 ).

The main purpose with the present research is to study how time and other factors are associated with change in attitudes and use of hen . In the present research we investigate the effect of time on the outcome variables. However, we do not here study the mechanism (for instance habituation) by which elapsed time can explain such effects, but rather show that other potential explanatory factors are not sufficient to explain the outcome effects alone. To date, time has been proposed as a cause for difference in evaluations (see for example, Sarrasin et al., 2012 ). However, no studies have followed an implementation over time in one language, with one specific word. It is also known from previous research that time has a positive effect on attitudes such that the longer something has been in effect the better people will like it ( Zajonc, 1968 ; Moreland and Topolinski, 2010 ). We present data from 2012 to 2015, on the attitudes to hen and self-reported use of hen from 2013 to 2015. We make the following predictions:

H1. Attitudes towards hen will become more positive over time.

H2. Self-reported use of hen will increase over time.

H3. Sexism and right-wing political orientation will be associated with negative attitudes, as well a lower use of hen

H4. Age will be related to attitudes and use, such that younger people will be more positive, and indicate more use of the word, than older people. Gender is included as a control because some studies have shown that women are more positive to gender-fair language than men.

H5. A strong gender identity (as either a woman or a man) will be associated with more negative attitudes and less use. Interest in gender issues will be associated with more positive attitudes and higher use.

H6. Time will have a significant and independent effect on attitudes and use of hen , also when all other variables are controlled for.

Materials and Methods

Participants and procedure.

We have collected data on attitudes and use of hen at six points in time since 2012. Participants and the datasets are described in Table 1 . Dataset 1 and 2 consist of participants that were approached in the waiting hall at the Central station in Stockholm. Dataset 3 and 4 consist of students at Lund University. Dataset 5 consists of participants that were approached in the city of Lund. Participation was rewarded with a lottery ticket in all these data collections. All studies from 2012 to 2014 were completed through ‘paper-and-pencil’ questionnaires. The experimenter distributing the questionnaire was present during the participation, but on a distance to provide confidentiality. Dataset 6 consists of participants recruited through advertisement on different Internet forums. 243 started to fill in the questionnaire, 190 completed it. Participation was not compensated. This study was carried out in accordance with Swedish national ethical standards put forth by the Central Ethical Review board and the Swedish Research Council and with written informed consent from all participants.

TABLE 1. Overview of the studies: time, sample size, participants mean age, gender distribution, and type of sample.

The attitude to hen was assessed with one item ‘What is your opinion about the gender-neutral pronoun hen in the Swedish language?’ (Responses were given on a 7-point response scale ranging from ‘1 = very positive’ to ‘7 = very negative’). A short text introduced to the question and explained that hen was a gender-neutral word that can be used as a complement to the Swedish words representing she and he .

Behavior (use of hen ) was measured from 2013 and onward with one item ‘Do you use hen yourself?’ (Responses were given on a 7-point response scale ranging from ‘1 = No, never’ to ‘7 = Yes, always’).

From 2013, participants also indicated whether they previously were familiar with the word hen from before. Answers ranged on a 7-point scale from ‘1 = not al all’ to ‘7 = very much’. Because there were very small variations in the responses from 2013 to 2014, in 2015 we dichotomized this response option into ‘yes’ and ‘no.’

Sexism was measured with five items from the Swedish version of the Modern sexism scale ( Ekehammar et al., 2000 ; e.g., ‘Discrimination against women is no longer a problem in Sweden’; ‘Humiliating treatments of women in adverts is unusual’; Answers in terms of agreement or disagreement were given on a 7-point scale from ‘1 = Strongly disagree’ to ‘7 = Strongly agree). Sexism was included in all six datasets. Means and SD over time are included in Table 2 .

TABLE 2. Means and standard deviations for included variables for each year, respectively.

Political orientation was assessed with one item ‘On a political scale from left to right, where is your position?’ Answers were given on a 7-point scale from ‘1 = clearly to the left’ to ‘7 = clearly to the right’).

Gender identity was included from 2013 and onward. In 2013 and 2014 it was assessed with two items (e.g., ‘To be a woman/man is an important part of my identity,’ ‘To be a woman/man is important to me,’ measured on a 7-point scale from ‘1 = strongly disagree’ to ‘7 = strongly agree’). In 2015, we began measuring gender identity with a validated sub-scale from Luhtanen and Crocker (1992) collective identity scale (e.g., ‘My gender identity is an important reflection of who I am,’ ‘My gender identity is an important part of my self image,’ (measured on a 7-graded scale: ‘1 = strongly disagree’ to ‘7 = strongly agree’). We used the two positively framed items because these were most similar to the items we used in 2013 and 2014. The reason for this shift was to use a more well-established scale.

Interest in gender issues was indicated with one item ‘How interested are you in general in gender issues?’ The scale ranged from ‘1 = not at all’ to ‘7 = very much’. This variable was included from 2013 and onward.

Age and gender was given by participants in a free-text response in order to avoid cisgenderism ( Ansara and Hegarty, 2014 ). These variables were included in all datasets.

In order to run the analyses, we collapsed all datasets into one. In the regressions, Time was included as a continuous variable for the years 2012–2015. This means that dataset 2–4 was collapsed into 1 year, 2013. Because there were different sample types we controlled for that factor.

Attitudes to ‘hen’ and Changes Over Time

Virtually all participants responded that they were familiar with the word hen . In 2013 and 2014 more than 95% responded a 6 or 7 on the 7-point scale, while in 2015 99.5% responded ‘yes’ to the question if they were familiar with the word since before.

The attitudes shifted from negative to positive over time (see Table 3 ). A univariate ANCOVA with year (2012, 2013, 2014, 2015) as the independent variable, sample type (student/community) as covariate, and attitude as the dependent variable, showed that attitudes changed over time, F (3,679) = 59.22, p < 0.001, = 0.21. Post hoc comparisons (Bonferroni adjusted for multiple comparisons), showed that the means did not change significantly from 2012 to 2013, or from 2013 to 2014, but between all other years ( p ’s < 0.004). Furthermore, the attitudes were polarized, such that respondents were either very negative or very positive toward the word hen. Figure 1 shows that the very negative attitudes (i.e., 1 and 2 on the scale) decreased over time (2012 = 56.5%; 2013 = 26.1%; 2014 = 17.5%; 2015 = 9.6%); whereas the very positive attitudes increased (i.e., 6 or 7 on the scale; 2012 = 17.4%; 2013 = 40.4%; 2014 = 32.5%, 2015 = 68.9%).

TABLE 3. Means and SD for ‘attitude to hen ’ and ‘behavior to use hen ’ over 4 years (2012–2015).

FIGURE 1. Polarization of attitudes toward hen was reversed from 2012 to 2015. ‘Negative attitudes’ = 1 and 2 on the rating scale; ‘positive attitudes’ = 6 and 7 on the rating scale.

Use of ‘hen’ Over Time

From 2013 and onward respondents also indicated whether or not they used the gender-neutral pronoun hen themselves (see Table 3 ). A univariate ANCOVA with year (2013, 2014, 2015) as independent variable, sample type as covariate, and behavior as dependent variable, showed a significant shift in behavior over time, F (2,498) = 8.56, p < 0.001, η p 2 = 0.03. Post hoc pairwise comparisons (Bonferroni adjusted for multiple comparisons) showed that the difference was significant between 2013 and 2015, ( p < 0.001). The responses for behavior were also somewhat polarized but not as much as for the attitudes, and were not reversed over the years (see Figure 2 ). A majority in 2013 (50%) and 2014 (58%) indicated they never or almost never used the word hen (as indicated with a 1 or 2 on the rating scale). In 2015, this group had decreased to 25%. However, there was no change in those who very often or always used the word hen (as indicated with a 6 or 7 on the rating scale) over time. In 2013, 13% responded they used hen often; in 2014 and 2015, 10% indicated they often used hen. Thus, both H1 and H2 stating that attitudes will become more positive and the use will increase over time were supported, although the attitudes changed more than the behavior.

FIGURE 2. Change in usage of a gender-neutral pronoun from 2013 to 2015. ‘Never or very seldom’ = 1 and 2 on the rating scale; ‘Always, or often = 6 and 7 on the rating scale.

Predictors Associated with Attitudes and Use

Hypotheses 3 throughout 6 were related tttitude and use. To test the influence of time on the attitudes to hen , while also controlling for, and investigating effects of, the other predictors, a hierarchical regression with all the variables that were measured from 2012 to 2015 was computed. Table 4 contains the correlations of included variables, collapsed across all years. The regression was performed in three steps (see Table 5 ). Regressions were also computed with dummy coding for time and the results were similar; we chose to present time variable as a continuous variable. The first step included time (2012–2014) and explained 19% of the variance. The longer the word has been known, the more positive were the attitudes. Adding sample type, age, and gender explained further 6% of the variance, such that being a woman, young, and a student was associated with more positive attitudes. Finally, in step 3, modern sexism and political orientation explained an additional 19% of the variance. Those with a right-wing orientation and higher sexism scores were more negative than individuals with left-wing orientation and lower sexism scores. When these factors were included, gender became insignificant, while time was still an important predictor. The total model explained 43% of the variance in the attitude to hen. Hence, H3, stating that sexism and political right affiliation would be associated with negative attitudes, H4, stating that younger people would be more positive to hen , and H6 stating that time will have an independent and significant effect on attitudes even when controlling for the other predictors, were all supported.

TABLE 4. Correlations, means, and SDs for variables included in regression.

TABLE 5. Hierarchical multiple regression analyses predicting attitudes to hen .

From 2013 and onward three more variables were included in the questionnaires: behavior (use of hen), gender identity , and interest in gender issues . In order to test whether gender identity and interest in gender issues account for more variance over sexism and political orientation, we calculated two hierarchical multiple regressions for attitude and behavior separately. The correlations, means, and SD are described in Table 6 .

TABLE 6. Correlations, means, SDs for variables included in regressions.

The regressions were computed in four steps to control for the contribution of variance in each step (see Table 7 ). For the attitude to the gender-neutral pronoun hen , time explained 9% of the variance in the first step, such that the longer hen had been in use, the more positive were the attitudes. The second step, where sample, gender and age were included, explained another 6% of the variance. Again, student samples were more positive than community samples, women were more positive than men, and younger people were more positive than older. The third step included sexism and political orientation, and explained another 21% of the variance, such that modern sexism and being right-wing oriented was associated with more negative attitudes. When these variables were included, gender became insignificant. The third step including gender identity and interest in gender issues, explained another 8%. Having a strong gender identity was associated with negative attitudes, whereas being interested in gender issues was associated with a positive attitude. When interest in gender issues and gender identity was introduced, neither gender or sample type were significant predictors, and the beta-weights for modern sexism and political orientation also decreased but remained significant. Although the beta-weight for time decreased in step 4 it remained significant.

TABLE 7. Hierarchical multiple regression predicting attitude to and use (behavior) of a gender-neutral pronoun hen .

In the regression with behavior (use of hen) as the dependent variable, time itself explained 2% of the variance. When age, gender, and sample type were included in the second step, those variables accounted for another 9% of the variance. Being older and having a masculine gender was associated with less use than being younger and having a feminine gender. The third step included modern sexism and political orientation and explained another 15% of the behavior. Right-wing orientation and sexism was associated with lower use of a gender-neutral pronoun. The fourth step, with gender identity and interest in gender issues explained another 9%, such that a strong gender identity was associated with lower use and being interested in gender issues was associated with a higher use. In the fourth step, time, gender, and sample type were no longer significant predictors. Also the beta-weights for political orientation and sexism decreased. The total model explained 32% of the variance. When controlling for all other factors, time contributed to a more positive attitude to a gender-neutral pronoun, although it did not increase the use of the pronoun hen . Thus, H6 was partially supported. Again hypothesis H3 and H4 were supported, and as predicted in H5, the strength of gender identity was a stronger predictor than gender itself. In addition, interest in gender issues proved to be a strong and independent predictor of both attitude and use. Even though it did not override the effect of political orientation, it should be taken as an indicator that this is an important aspect to take into consideration in future research.

Our results show that an introduction of a gender-neutral pronoun in the Swedish language was met with high resistance, but that both attitudes and behavior became more positive over time. We found that time predicted the attitude to hen also when other factors were controlled for. Other factors that contributed with unique variance to the attitude and the behavior were gender identity (but not gender itself), modern sexism, political orientation, and interest in gender issues.

This article has given an overview of the introduction of the new gender-neutral pronoun hen in the Swedish language. Data were collected during 4 years, starting in 2012 when the debate about a gender-neutral pronoun began and continued until 2015, 1 year after the word hen had been officially included in the Swedish dictionary.

The Impact of Time

The results clearly show how the introduction of hen was associated with high resistance (in the media and among lay people), but also that attitudes became positive over time. In 2012, a majority of the study sample was explicitly very negative to the inclusion of a gender-neutral pronoun, whereas only a minority was very positive. However, already in 2013 this polarization was reversed, and in 2015 almost no one was very negative. A similar pattern was found for the use of the gender-neutral pronoun, although this change was smaller.

This is the first study about the introduction of gender-fair language analyzing the attitudes for a specific word over time. Previous research has proposed that variations in attitudes to gender-fair language could be due to how long it has been in use (see for example Sarrasin et al., 2012 ). This is the first study explicitly testing that hypothesis using data measurements at several time points. Indeed, time was the most important predictor of the attitudes, even after controlling for various other factors. This sends a very important message, because it should motivate language amendments also when there are strong reactions against an implementation.

We found that the attitudes changed faster than the behavior. The debate about hen was very wide-spread in the Swedish society, including the broader media landscape, leading to that the familiarity of hen very quickly included the large majority. Already in 2012, almost 95% of participants were familiar with the word, and in 2015, only 1 out of 190 participants were unfamiliar with hen . This may have been of importance for how fast the attitudes changed. For behavior to occur, hen must be activated and accessible in a specific moment ( Fazio et al., 1989 ; Fazio and Olson, 2003 ; Glasman and Albarracín, 2006 ) as an alternative to, for example, double forms such as she or he . Because pronouns are often processed automatically ( Chung and Pennebaker, 2007 ) the traditional system with she and he is probably still cognitively dominant over new forms of pronouns. Accessibility is although likely to increase over time, considering the increasingly widespread use of the word in media ( Ledin and Lyngfelt, 2013 ), and in other arenas. For instance, the word was used in the lyrics of one of the songs to the Swedish contribution to the European Song Contest 2015, indicating its widespread acknowledgment. Social norms also facilitate behavior ( Fazio, 1990 ), and it is plausible that people have been avoiding using hen because they still believe that the majority are negative to it. Thus, when people realize that the attitudes have changed, the word may be more common also among lay people and everyday users.

Factors Explaining the Attitudes and Use

The more strongly participants identified themselves with their gender identity, the more negative attitudes they held and the least often they used the word. Women were somewhat more positive toward hen and used hen more often than men, but gender identity proved to be a much stronger predictor than biological gender. This supports the idea that a gender-neutral pronoun challenges the traditions of a binary gender system. These results also line up with previous research showing that androgynous gender roles were associated with a higher use of gender-fair language than traditional gender roles ( Rubin and Greene, 1991 ). A large body of research indicates that people (especially adults) strongly prefer the system that they currently live in ( Jost et al., 2004 ). People prefer to keep things stable and predictable. Any new word would thus probably elicit some resistance. However, there is reason to believe that a word explicitly challenging such a basic organizing principle such as the binary gender system elicits even stronger resistance. This resistance may also vary depending on individual factors. As was found in the present research a strong gender identity was negatively associated with attitudes toward hen , which can be considered a gender-fair amendment toward neutralization. However a strong gender identity might be positively related to amendments that add feminine alternatives to masculine forms because the binary gender-dichotomy would be even more strongly preserved and perpetuated with such amendments. This is an empirical question.

As in previous research, age, sexism, and political orientation was associated with attitudes to gender-fair language ( Parks and Roberton, 2000 ; Sarrasin et al., 2012 ; Formanowicz et al., 2013 ). However, we also found that the influence of those factors decreased when gender identity and interest in gender issues were included. Even though political orientation still proved to be a significant predictor, this may indicate that interest is an important variable that eventually could diminish this effect, considering that there is a growing feminist movement also within the political right in Sweden.

Opinions associated with feminists may evoke higher resistance among people who do not actively endorse such values ( Blaubergs, 1980 ). Thus, when the trendy entertainment magazine in one issue exchanged all third personal pronouns into hen , and when newspaper media started to use hen , this might have been of more importance than when feminists or linguists debated why hen should be used ( Cialdini and Goldstein, 2004 ). Koeser et al. (2014) have also shown that the reading of gender-fair texts increases the use of gender-fair language. Hence, the fact that hen occurred more often in ordinary newspapers might have had a positive impact on use and might also imply an increase over the coming years.

Hen in Swedish was adapted from the gender-neutral Finnish word hän ( Prewitt-Freilino et al., 2012 ). Maybe there are more words in gender-neutral languages that could be introduced either in natural or gender-marked languages. Some scholars have pointed to the need to be creative and come up with new words ( Wayne, 2004 ), and borrowing them from other languages could be one strategy. New words might have a potential to override previous problems in applying gender fair language, since they may be less associated with a gender bias, which might be the case with other neutral words ( Bäck et al., 2015 ). It should also be noted that both the Finish word hän as well as the Swedish gender-neutral pronoun hen very nicely fits into the Swedish system of pronouns, as being literally very close to, as well as alphabetically positioned between han (‘he’) and hon (‘she’). There is of course a risk that also hen could be associated with a male bias in future. Due to our results in this study we believe that such a risk is lower as long as hen is used as a generic or a transgender pronoun; however, this is an empirical question. When hen is broadly used in society, it is important to replicate studies that investigate how gender is activated when hen is used to refer to a person ( Wojahn, 2013 ; Bäck et al., 2015 ).

Limitations and Future Research

The design of the present study is cross-sectional and not longitudinal, which may imply selection bias in the samples and that other factors such as possible cohort effects may have had an impact on the results. With this in mind, we took care to collect both student and community samples, for which we controlled in the regression analyses. However, these samples were mainly drawn from cities and hence there may still be possible bias in the samples. This implies that generalization from the present study should be done with caution. With respect to cohort effects, our samples were fairly similar, although some minor deviations can be noted. The comparisons of the samples show that sexism was lower in the first year sample and the last year sample, gender interest was higher in the last sample, and gender identity was less strong in the last sample. Political orientation was similar in all samples. Here it can be noted that the last sample was collected using a web survey, which may imply selection bias since those who choose to participate can be expected to be relatively interested in issues of gender and language. With these problems in mind, we computed regressions for 2 years at a time, controlling for sexism, age, gender, and political orientation. Time was a significant factor in all three regressions (2012–2013; 2013–2014; 2014–2015).

This research is fairly explorative and the first of its kind. This entails that the items may not always have been entirely perfectly formulated. For instance, the response scale to the item ‘Do you use hen yourself?’ ranged from ‘No, never’ to ‘Yes, always.’ It may not be very clear to the participant what the response option ‘Yes, always’ entails, and this could be a contributing factor to why the results in general were weaker for the behavioral measure. ‘Always’ could indicate that one replace all personal pronouns with hen , or it could indicate that one always use hen when gender is unknown or irrelevant. Another limit is that this measure does not separate between written and spoken language. It is easier to use hen in writing than it is to use it in speaking. Future research should take these limitations into account when exploring how hen is used.

Language and communication have a large impact on the creation of a common ground and reality, for instance concerning what is considered as normal or desirable ( Clark and Brennan, 1991 ; Hardin and Higgins, 1996 ). Thus, adding a gender-neutral pronoun to a natural gendered language may influence how individuals with a non-binary gender are perceived. In all our datasets ‘gender’ was an open-ended question, making it possible to self-categorize as neither woman or man. There were no such responses in 2012–2014, while in 2015, 4% (eight people) indicated a gender identity outside the gender dichotomy. Although it might be a coincidence, it could also be a consequence of the introduction of hen . This is something that could be further studied. A related important question that remains is what impact the use of hen actually has on representations of gender, and interpersonal attitudes.

We believe it is important to empirically test if common arguments proposed as negative consequences of gender-fair language are true. One such argument that remains to be tested is whether new word forms actually steel attention from the text content. If there is a cognitive load associated with hen , reading a text with hen should take longer time, and less information should also be recalled from such a text. Finally, it is important to note that we do not argue that time in use operates in isolation from other factors. One important aspect we believe is of great importance is that the Swedish society is becoming increasingly egalitarian and has a strong feminist movement, which includes people of all gender identities, and people with different political opinions. The fact that hen has its roots as far back as the 1960’s indicates that something else must have sparked the onset of the use in modern day than just time. One factor may be a societal ‘readiness’ to take this debate. Hence, societies of different levels of such readiness will of course receive a similar implementation differently. However, since there is a strong feminist movement in many societies, as indicated by the UN’s ‘heforshe’ campaign, we believe that the global readiness could be relatively favorable in a near future. Another factor is the word’s practical implications. In the Swedish case hen was introduced by LGBT communities and within the feminist movement, but clearly it met demands also among lay people as the word became as widespread as soon as it did.

This is the first study analyzing the importance of time in implementing gender fair-language. The introduction of a gender-neutral pronoun in Sweden was firstly met with hostile reactions and negative attitudes, but over the course of only a couple of years, attitudes became largely positive. These results are positive for those working with gender equality and motivate implementations although the initial resistance may be high.

Conflict of Interest Statement

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.

Acknowledgment

This work was supported the Swedish Research Council (grant: 2014-1150). We acknowledge students that have participated in the data collections.

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Keywords : gender-fair language, gender-neutral pronouns, attitude change, gender, hen

Citation: Gustafsson Sendén M, Bäck EA and Lindqvist A (2015) Introducing a gender-neutral pronoun in a natural gender language: the influence of time on attitudes and behavior. Front. Psychol. 6:893. doi: 10.3389/fpsyg.2015.00893

Received: 30 March 2015; Accepted: 15 June 2015; Published: 01 July 2015.

Reviewed by:

Copyright © 2015 Gustafsson Sendén, Bäck and Lindqvist. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Marie Gustafsson Sendén, Department of Psychology, Stockholm University, 106 91 Stockholm, Sweden, [email protected]

Disclaimer: 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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• 28 May 2024

Heed lessons from past studies involving transgender people: first, do no harm

• Mathilde Kennis 0 ,
• Robin Staicu 1 ,
• Marieke Dewitte 2 ,
• Guy T’Sjoen 3 ,
• Alexander T. Sack 4 &
• Felix Duecker 5

Mathilde Kennis is a researcher in cognitive neuroscience and clinical psychological science at Maastricht University, the Netherlands.

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Robin Staicu is a neuroscientist and specialist in diversity, equity and inclusion at Maastricht University, the Netherlands.

Marieke Dewitte is a sexologist and assistant professor in clinical psychological science at Maastricht University, the Netherlands.

Guy T’Sjoen is a clinical endocrinologist and professor in endocrinology at Ghent University Hospital, Belgium, the medical coordinator of the Centre for Sexology and Gender at Ghent University Hospital, and one of the founders of the European Professional Association for Transgender Health.

Alexander T. Sack is a professor in cognitive neuroscience at Maastricht University, the Netherlands.

Felix Duecker is an assistant professor in cognitive neuroscience at Maastricht University, the Netherlands.

You have full access to this article via your institution.

Over the past few decades, neuroscientists, endocrinologists, geneticists and social scientists have conducted numerous studies involving transgender people, meaning those whose gender identity does not conform to that typically associated with the sex to which they were assigned at birth. Justifications for doing such research have shifted over the years and, today, investigators are increasingly focused on assessments of transgender people’s mental health or the impact of hormone therapies.

But such work raises challenges. Despite researchers’ best intentions, these studies can perpetuate stigmas and make it even harder for transgender people to access appropriate medical care.

Here we focus on neuroscientific approaches to the study of transgender identity to explore how investigators might navigate these concerns.

Brain scanning

In 1995, neuroscientists at the Netherlands Institute for Brain Research in Amsterdam published findings from a post-mortem study, which included six transgender individuals 1 . They found that the volume of part of the brain’s hypothalamus — called the bed nucleus of the stria terminalis, which tends to be larger in men than in women — corresponded to the gender identity of the transgender individuals, not to their sex assigned at birth. Although the data were only correlative, the researchers suggested that people identify as transgender because of changes in the brain that happen before birth — in other words, that someone can be born with a male-typical body and brain characteristics more typical of a female brain, and vice versa.

Sex and gender in science

Since it was published, the paper has been cited more than 1,000 times, and at least a dozen researchers have probed this theory and related ones using tools such as structural and functional magnetic resonance imaging (MRI).

Although the results of these analyses have been inconsistent, several ideas have nonetheless arisen about a neurobiological basis for gender dysphoria — the distress associated with a person’s gender identity not aligning with the sex they were assigned at birth. These include the ‘own-body perception’ theory 2 , which proposes that a reduced structural and functional connectivity between certain brain networks is responsible. (Previous work has associated these networks with brain regions thought to be involved in people’s ability to link their own body to their sense of self 3 .)

As analytical tools and methods advance, brain research is becoming more sophisticated. The number of neuroscientific studies that include transgender participants has increased considerably since 1991 (see ‘On the rise’).

Some neuroscientists are using functional MRI to study the effects of hormone therapy on brain structure 4 and to examine cognitive processes such as face perception 5 . Others are applying machine-learning techniques to establish whether features in brain scans of cis- and transgender people correlate with their gender identity 6 . Researchers are also trying to assess whether particular features identified in brain scans make it more likely that transgender individuals will benefit from gender-affirming hormone therapy 7 . And some are conducting ‘mega-analyses’ — pooling the brain scans of hundreds of participants — to identify brain characteristics that are specific to transgender people 8 .

Help or harm?

One concern arising from such studies is that neuroscientific findings related to transgender identity could make it even harder for some people to access medical treatment that could help them.

In countries or regions where gender-affirming medical treatment is available, individuals often need a diagnosis of ‘gender dysphoria’ or ‘gender incongruence’ to be eligible for hormone therapy or gender-affirming surgery, and to be reimbursed for such treatments. Results from brain scans could be included in the suite of measurements used to assess whether someone is experiencing gender dysphoria or incongruence.

Those in favour of such requirements argue that it is necessary to prevent people taking irreversible steps that they might regret. Hormonal therapy can have adverse effects on fertility, for instance 9 . However, many transgender people argue that whether someone can receive gender-affirming hormone therapy or other treatment shouldn’t depend on a health-care practitioner deciding that they experience ‘enough’ gender dysphoria to be eligible 10 . The current approach, combined with a shortage of specialists qualified to make such diagnoses, has been linked to long waiting lists. In the Netherlands, waiting times can be more than two years .

A second possibility is that neuroscientific findings related to transgender identity will fuel transphobic narratives 11 .

Take the debate on social media and other platforms about gendered public spaces in countries such as the United States , the United Kingdom and Brazil 12 . Some people argue that allowing transgender women to access infrastructure, such as public toilets or women’s prisons, threatens the safety of “real women” . Neuroscientific research is sometimes misused to bolster flawed claims about what ‘real’ means.

Moreover, such studies could exacerbate tensions between scientific and transgender communities.

Scientists are aiming to identify brain characteristics that are specific to transgender people. Credit: Alain Jocard/AFP/Getty

Although cis- and transgender researchers have taken steps to improve people’s understanding, there is a history of tension between the scientific and transgender communities 13 . In the late 1980s, for instance, a sexologist argued that trans women who are mainly attracted to women experience sexual arousal from their own expression of femininity. He described their feelings of gender dysphoria as resulting from paraphilia — a sexual interest in objects, situations or individuals that are atypical 14 . This theory has not held up under broader scientific scrutiny 15 , but it has become notorious in the transgender community and, from our discussions with transgender people and discussions by other groups 16 , it is clear that such studies have reduced transgender people’s trust in science.

How four transgender researchers are improving the health of their communities

In 2021, for example, a neuroimaging study with transgender participants was suspended in the United States after backlash from the transgender community. The study would have involved showing participants images of themselves wearing tight clothes, with the intention of triggering gender dysphoria — an experience that is associated with depression, anxiety, social isolation and an increased risk of suicide. The study’s researchers had acquired ethical approval from their research institute and obtained informed consent from the participants. Yet they had failed to anticipate how the transgender community would perceive their experimental procedure.

In 2022, to learn more about how transgender people view current neuroscientific approaches to the study of transgender identity, we conducted focus-group interviews that lasted for three hours with eight transgender participants — all of whom had differing levels of knowledge about the topic.

The group expressed concern that studies that look for a neurological basis to transgender identities could have a pathologizing effect. “I think questions of aetiology are just inherently wrong,” one participant said. “We don’t ask ‘Why is someone’s favourite colour blue?’. These are questions that come from wanting to pathologize.” Participants also agreed that a biological-determinist approach does not do justice to the complex and layered experience of identifying as transgender.

Decades of work aimed at establishing how science can benefit minority groups 17 suggest that neuroscientists and other scholars could take several steps to ensure they help rather than harm transgender, non-binary and intersex individuals and other people who don’t conform to narrow definitions around sex and gender. Indeed, the four actions that we lay out here are broadly applicable to any studies involving marginalized groups.

Establish an advisory board. Researchers who work with transgender participants should collaborate with an advisory board that ideally consists of transgender people and members of other groups with relevant perspectives, including those who have some understanding of the science in question. Funding agencies should support such initiatives, to help prevent further distrust being sown because of how studies are designed.

Set up multidisciplinary teams. Researchers trained in neuroscience will view phenomena such as transgender identity through a different lens from, say, those trained in psychology. To prevent the outcomes of neuroscientific and other studies being described and published in an overly deterministic and simplistic way 18 , research teams should include social scientists. Ideally, such collaborations would also include transgender researchers or others with diverse gender identities, because their input would help to prevent a cis-normative bias in study design and in the interpretation of results. Indeed, our own group has benefited from this diversity (one of us is transgender).

Prioritize research that is likely to improve people’s lives. Neuroscientists and others engaged in research involving transgender participants, non-binary people or individuals with diverse gender identities should prioritize research questions that are likely to enhance the health of these groups. Although the applications of basic research can be hard to predict, investigations into the neurobiological impacts of hormone treatment on the brain, for instance, could be more directly informative to health-care practitioners and transgender individuals than might investigations into the underlying bases of transgender identity.

Rethink how ethical approval is obtained. Ethical boards at universities typically consist of scientists with diverse backgrounds. But it is unrealistic to expect them to be educated on the sensitivities of every minority group, whether in relation to gender, religion, ethnicity or anything else. One way to address this problem is for ethical boards to require researchers to state what feedback and other information they have gathered through community engagement. A university’s ethical review committee could then evaluate whether the researchers have done enough to understand and address people’s concerns and sensitivities.

Our aim is not to halt scientific enquiry. But when it comes to transgender identity, knowledge cannot be pursued in isolation from the many societal factors that shape how that knowledge is received and acted on.

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Gender Issues in Genderless Clothing: A Theoretical Framework in Fashion Interdisciplinary Research

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• Benilde Reis   ORCID: orcid.org/0000-0003-0525-0853 5 ,
• Madalena Pereira   ORCID: orcid.org/0000-0002-7526-396X 6 , 7 ,
• Nuno A. Jerónimo   ORCID: orcid.org/0000-0003-2452-0417 8 , 9 &
• Susana Azevedo   ORCID: orcid.org/0000-0001-5229-3130 10  

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Studying fashion’s history and gender problems raises the question of genderless, by highlighting the significance of fashion, as a modern phenomenon. Clothing is considered, in this sense, one of the most noticeable consumer goods and a significant factor in the social formation of identity [ 1 ]. Genderless fashion and gender issues are contemporary. It is present in articles, photography, art, music, movie stars, and fashion and has accompanied the progression of history; several authors have previously handled this subject.

Interdisciplinary research encompasses research and analysis of phenomena in various areas of scientific study. In this case, areas such as Fashion Design, Sociology, and aspects related to product attributes and mainly to consumer behaviour. Consequently, it is pertinent to give the research an interdisciplinary character concerning the design of genderless clothing and link the different aspects addressed in this work, which implicitly belong to it. This theoretical framework in fashion interdisciplinary is based on PhD thesis research entitled: Gender Issues in Genderless Fashion: Trend versus Paradigm (Translated title from: Questões de Género no Vestuário Sem Género: Tendências versus Paradigma. ), which analyses genderless clothing in detail, addressing other associated concepts such as sex, sexual orientation, types of gender, unisex, androgynous, among others [ 2 ].

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LabCom, Beira Interior University, Covilhã, Portugal

Nuno A. Jerónimo

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Reis, B., Pereira, M., Jerónimo, N.A., Azevedo, S. (2023). Gender Issues in Genderless Clothing: A Theoretical Framework in Fashion Interdisciplinary Research. In: Broega, A.C., Cunha, J., Carvalho, H., Providência, B. (eds) Advances in Fashion and Design Research. CIMODE 2022. Springer, Cham. https://doi.org/10.1007/978-3-031-16773-7_20

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