Cisnormative Language and Erasure of Trans* and Genderqueer Student Representation in Biology Education Research

INTRODUCTION

In recent years amidst increasing awareness and action regarding gender and LGBTQ+ equity on college campuses, STEM fields have demanded research-backed methods of developing expansive intersectional communities of people engaging with STEM (Olson and Riordan, 2012; Eddy et al., 2014; Cooper et al., 2020). Evidence suggests that LGBTQ+ students are silenced by exclusion in higher education, challenging the progress STEM leadership aims to enact in academia (Ferfolja et al., 2020). This progress is further limited by the erasure of transgender, nonbinary, and gender nonconforming (collectively referred to here as trans* and genderqueer) individuals from much of the gender and LGBTQ+ political and social advocacy over the past decades, as representation of diverse sexual orientations can be wrongfully conflated with representation of diverse gender identities (Williams et al., 2020).

Research on the educational needs of trans* and genderqueer individuals has historically lagged behind that of other marginalized populations (Vaccaro et al., 2015; dickey et al., 2016; Freeman, 2018; Miller et al., 2020). What research has been done reveals uncomfortable truths. Trans* and genderqueer students who begin college in STEM majors are 10% less likely to continue in those programs than their cisgender peers, despite reporting similar levels of academic ability, participation in so-called high impact practices (e.g., undergraduate research and collaborative learning) and high precollege grades (Maloy et al., 2022). LGBTQ+ students, including trans* and genderqueer students, report worse mental health than their cisgender and heterosexual peers (Stolzenberg and Hughes, 2017) and they fear being perceived negatively by others at a disproportionately higher rate than baseline, especially when expected to work closely in active learning situations (Cooper and Brownell, 2016; Busch et al., 2023). Trans* and genderqueer students report that STEM fields and faculty foster particularly cisheteronormative and unwelcoming working and learning environments (Brown et al., 2004; Cech and Sherick, 2015; Cech and Rothwell, 2018; Dyer et al., 2019), especially when their LGBTQ+ identities and experiences intersect with other demographic characteristics like ability or race (Pawley, 2019; Hales, 2020; Miller and Downey, 2020; Leyva et al., 2022). Particularly in the context of biological sciences, where gender and sexuality are often discussed formally in the curriculum in a manner that either unintentionally erases or intentionally marginalizes the expression of nonheteronormative and noncisnormative identities, trans* and genderqueer students may feel unseen and unwelcome (Bazzul and Sykes, 2011a; Ainsworth, 2015; King et al., 2021). Taken together, this literature demonstrates that any sincere effort to take evidence-based action toward more equitable undergraduate biology learning environments must prioritize the experiences and needs of trans* and genderqueer student populations.

Education research provides one important avenue toward understanding diverse student experiences and building inclusive education experiences. Demographic data are used to authentically illustrate the richness in thought and experiences within research populations. Consequently, demographic data, including data about gender/sex diversity, are recognized for their importance in revealing disparities impacting groups in education research, amplifying the experiences of students whose needs are not being met in academic contexts, and enacting educational justice within oppressive academic systems (Fernandez et al., 2016; Van Anders, 2022).

Representing trans* and genderqueer student populations through gender/sex research data is uniquely valuable and important to making informed advancements toward gender and LGBTQ+ equity in biology education. Because trans* and genderqueer students have been historically oppressed by systems of power in higher education, their perspectives and lived experiences provide a unique standpoint from which to understand and dismantle systems of oppression that impact non only trans* and genderqueer students, but all students who hold minoritized identities (Harding, 2011). Additionally, the strong personal connection to course content experienced by many trans* students can provide valuable perspectives on how biology curriculum can be used to celebrate human diversity and validate unique identities in the classroom (Casper, Rebolledo et al., 2022).

However, literature regarding gendered experiences in education is often known to methodologically reinforce gender binaries, and imprecise applications of language and gender theory in research contexts limits theoretical development (Garvey and Rankin, 2015; Westbrook and Saperstein, 2015; dickey et al., 2016; Galupo et al., 2017; Hyde et al., 2019). Nonbinary populations significantly lack representation in an existing body of literature that fails to express the full intersection of research participants’ identities (Matsuno and Budge, 2017). As a result, trans* and genderqueer individuals and their unique experiences are not well represented in current research models (Garvey et al., 2019; Hyde et al., 2019). Without accurately and equitably representing these individuals in research data, the academic system cannot effectively reform to meet the unique needs of trans* and genderqueer communities.

In this study, we sought to characterize the current state of gender/sex data collection in biology education research, focusing our analysis on all research articles published over a 5-year period in a flagship biology education research journal, CBE-LSE.

A REFLECTION ON LANGUAGE

It is important to approach identity labels and definitions with a critical lens to what labels mean, how they can be useful in education research, and the ways in which they fall short. We and other researchers within and outside of the trans* and genderqueer community have found it difficult to define terms in a way that respects and celebrates the diversity of individuals’ identities (Stachowiak, 2017; Thorne et al., 2019). While there is a clear biological and societal relevance to trans* and genderqueer identities, language often fails to fully convey the experience of these identities. Trans* and genderqueer individuals represent a small minority of the population, however, within this group there are many diverse identities. Thus, labels and definitions will never map perfectly to the breadth of human experience. Furthermore, language changes over time. Some terms that were previously considered offensive have been widely reclaimed, while other terms that were once commonplace are now often seen as outdated. The way individuals label their identities can also change. Indeed, many critical gender scholars view the porous and fluid quality of these labels as essential components of Queer (including trans* and genderqueer) identities (Davis, 2009; Stryker, 2013). As Nicolazzo (2017) states, “Being trans* may have little to do with others being able to define an individual as such” (Nicolazzo, 2017). Consequently, self-identification should be the primary way to understand how someone identifies.

For the purpose of this manuscript, we use the terms trans* and genderqueer to encompass a broad range of gender identities, embodiments, or expressions that have been historically excluded from dominant discourse. For our audience, we use “trans*” with an asterisk as a reminder that our discussion of trans* identities represents a diverse spectrum of trans* and genderqueer experiences. While it is understood within LGBTQ+ communities that “trans” without an asterisk can be similarly representative, we have included this symbol here to make explicit space for trans* identities often pushed to the margins of trans* representation and advocacy.

As with any umbrella label, this term should be understood to carry some degree of imprecision: some trans* students do not identify as gender nonconforming, and some gender nonconforming students would not self-identify as trans*. For example, the 2015 US Transgender Survey includes results from almost 28,000 respondents who qualify for the survey, and within this sample 12% of respondents indicated that they do not think of themselves as transgender (James et al., 2016). Furthermore, this label may exclude some individuals who identify outside of the normative gender/sex binary or who do not identify with the sex they were assigned at birth, depending on how they self-identified or were assigned identities by education researchers. Additionally, some of these identities overlap in some places and not in others. For instance, some Intersex people identify as trans*, nonbinary, and/or gender fluid. Others do not. Some nonbinary people identify as trans* and others do not. The web of identifications is neither completely exclusive nor inclusive of one another. The importance of using appropriate language and identifications cannot be understated. Even when mistakes are made, correcting oneself and others can help create a culture of learning and growth, and shows a commitment to fostering an inclusive environment.

LITERATURE REVIEW

Persistence of Trans* and Genderqueer Populations in the United States

It is difficult to accurately estimate the size of the trans* and genderqueer population because of a lack of sufficient data collection, overt discrimination, political opposition to the rights of trans* and genderqueer people, and potential reluctance to self-identify as LGBTQ+, especially among older generations (Meerwijk and Sevelius, 2017). According to a recent estimate, amongst all adults in the United States, 0.5% (1.3 million) identify as trans* and/or genderqueer, whereas amongst youths aged 13–17 in the United States, 1.4% (300,000) identify as trans* and/or genderqueer (Herman et al., 2022).

Despite the movement toward increasing identification with trans* and genderqueer identities in younger generations, social awareness and acceptance of these identities has lagged, as well as their representation in education research.

Trans* and Genderqueer Experiences in Higher Education

The impact of political (“2024 Anti-Trans Bills,” n.d.; Grant et al., 2011; Winter et al., 2016) and cultural (Meerwijk and Sevelius, 2017; Parker et al., 2022) hostility toward trans* and genderqueer people extends even to ostensibly progressive settings such as institutions of higher education, where trans* and genderqueer people face extensive and persistent microaggressions and erasure (Nicolazzo, 2017). Despite recent movement toward creating more trans* and genderqueer inclusive spaces, college campuses remain largely cisnormative spaces both structurally and socially. Reinforcement of cisnormative gender binaries like gender/sex-segregated spaces perpetuate distinctly exclusionary environments for trans* and genderqueer campus communities compared with cisgender students (Seelman, 2014).

Early approaches to research focused on gendered experiences in higher education often erased trans* and genderqueer identities. Emerging research centering trans* and genderqueer identities provides important glimpses into trends of adversity for trans* and gender-nonconforming students (Haverkamp, 2019; Maloy et al., 2022). This body of work has uncovered significant distinctions between the experiences of trans* and genderqueer students compared with both their cisgender peers and other members of LGBTQ+ communities, including higher rates of harassment and decreased sense of belonging (Dugan et al., 2012). Trans* and genderqueer students and faculty cope with the added pressure of deciding whether and how to disclose their identities in academic spaces, while navigating gendered and cisnormative expectations that may paint them as “too trans” or “not trans enough” (Siegel, 2019). These added considerations constitute a significant “minority tax” for trans* and genderqueer individuals on college campuses, requiring a significant additional emotional burden that may overshadow their own experiences and expressions of personal identity (Catalano, 2015; Rodríguez et al., 2015). Even when trans* and genderqueer spaces and allyship are available on campus, students who need them most struggle to get in touch with these resources (Siegel, 2019). Further, empirical focus on a holistic idea of “campus climate” rarely considers the impacts of microclimates in and beyond institutions, which vary in inclusion and support, emphasizing a need for progress beyond “one-size-fits-all” activism.

Specifically within STEM fields, research amplifying trans* and genderqueer student voices indicates that STEM courses may be perceived as more rigidly gendered than non-STEM courses (Pryor, 2015). These findings highlight the need for discipline-specific studies in STEM fields to reveal nuance between practices (Cooper et al., 2020). Within STEM fields, biology is unique as a discipline in that it explicitly addresses topics of sex, gender, and sexuality that have particular salience for trans* and genderqueer students (Casper, Rebolledo et al., 2022). Although this topical relevance could be leveraged to engage diverse students in biology classes and research, previous studies have found that the current landscape of biology education materials, including textbooks, tend to present these issues in a heteronormative and cisnormative manner, promoting an inaccurate and incomplete understanding of the complex biological realities underlying sex, gender, and sexuality that may actively exclude and harm trans* students (Bazzul and Sykes, 2011b; King et al., 2021). As a result, trans* students have described biology as a particularly hostile discipline and have highlighted the need for urgent change in undergraduate biology education to incorporate more diverse student perspectives and validate trans* identities (Casper, Rebolledo et al., 2022).

For higher education to advance with the valuable and increasing trans* and genderqueer community of biology students, there is a growing necessity to transform research practice and institutional systems to center their perspectives and learn from the diverse and nuanced experiences of trans* and genderqueer members of the biology community (Beemyn, 2003; McKinney, 2005; Negrete and Purcell, 2011; Catalano, 2015; Siegel, 2019), in part through data representation. This transformation has the capacity to greatly expand current efforts toward greater gender inclusivity in biology education by including the full spectrum of minoritized genders in undergraduate biology education. Doing so will require an intentional and sustained effort to ensure that research efforts undertaken by the biology education community accurately and fully depict student demographics and intersectional identities, including those of trans* and genderqueer students.

The Importance of Demographic Data

Failure to correct our approaches to collecting gender demographic data will perpetuate trans* and genderqueer erasure in higher education research, and in turn fail the trans* and genderqueer communities (Galupo et al., 2017; Meerwijk and Sevelius, 2017; Jones, 2022). We know that sociocontextual factors within STEM education such as stereotype threat, exam anxiety, and social exclusion interact with gender identity, which influences students’ capacity to thrive (Eddy et al., 2014; Wright et al., 2016; Cooper et al., 2018; Harris et al., 2019; Aguillon et al., 2020; Casper, Rebolledo et al., 2022). Demographic data are necessary for representing and understanding these gendered experiences. However, frequently used methods of studying and interpreting gender may be stunting the progress of research about and beneficial for trans* and genderqueer students.

Research Questions

For these reasons, we sought to engage in the first exploratory study into methods of data collection, analysis, and reporting about sex and gender used in biology education research. To address the question of gender representation and equity in impactful biology education research, our group assessed current methodological practices and conceptual limits in research papers from CBE-LSE, a premier biology education research journal. We selected CBE-LSE because it is the most highly cited STEM education research journal specific to undergraduate biology education research in the United States, with an impact factor of 3.7 (Clarivate, 2023). CBE-LSE was identified as priority for analysis due to the contributors, intended audiences, and goals the journal engages with:

We focused our analysis on all articles published between 2018 and 2022, as this period represents a critical period of rapidly changing social and political conditions experienced by trans* and gender nonconforming individuals in the United States. We reviewed and coded original research studies to explore the following questions:

1. How are biology education researchers who publish in CBE-LSE collecting gender/sex data, and do their methods include options beyond cisnormative narratives?

2. How are biology education researchers who publish in CBE-LSE analyzing and reporting gender/sex data, and does their language extend beyond cisnormative narratives?

3. Have biology education researchers who publish in CBE-LSE moved away from cisnormative narratives over the past 5 years in their discussion of gender/sex data?

We then utilized this analysis in tandem with existing queer literature to develop an introductory pivotal concepts model to guide biology education researchers, authors, and editors in their critical consideration of gender/sex in research design and practice.

MATERIALS AND METHODS

Positionality Statement

Our author group includes undergraduate students, graduate students, postdoctoral scholars, faculty members, and administrators from a variety of institution types across the United States. We hold many varied academic and personal identities that inform this work. Our fields of study include audiology, biochemistry, biology education research, biophysics, cell biology, chemistry education research, critical gender studies, ecology, entomology, immunology, learning sciences, mathematics education, microbiology, neurobiology, physiology, psychology, research ethics, speech pathology, and women's studies. Collectively, we incorporate critical perspectives from our transdisciplinary experiences to identify how academic idealization of false narratives of objectivity has impacted students, researchers, and society at large (Imad et al., 2023).

We approach discussions of inclusivity in regards to gender and sex from the lived experiences of authors who identify as genderqueer, genderfluid, transgender women, transmasculine, nonbinary, cisgender men, cisgender women, queer, bisexual, polyamorous, pansexual, gay, lesbian, demisexual, and asexual. We also recognize the importance of intersectional experiences that are informed by other aspects of our social identities: individuals in our author group identify as African American, Asian American, Canadian, Hispanic, Latino, Multiracial, Third-culture, and White. Some of us are able-bodied, Deaf, deaf, disabled, hard of hearing, hearing, and neurodivergent. Members of our group experience attention-deficit/hyperactivity disorder and autism. We are first- and continuing-generation academics from different socioeconomic backgrounds, and some of us experience mental health challenges and/or are trauma survivors. These complex interacting identities represent positionalities that carry varying levels of power, influence, marginalization, or erasure in our society. We draw upon these diverse experiences and perspectives to recognize the varied ways in which students and practitioners of science participate in and experience oppressive sex and gender norms and expectations while amplifying voices that have been oppressed and systemically silenced by a cisheteropatriarchal culture within STEM communities (Leyva, McNeill, Balmer et al., 2022; Leyva, McNeill, and Duran, 2022). Our experiences of sex and gender discovery, liberation, expression, oppression, and tokenization inform our desire to highlight existing inequities and pathways toward more inclusive practice. Simultaneously, these experiences inform our decision to not impose overly prescriptive best practices that obscure the expansive, unique, ever-changing identities and lives of trans* and genderqueer people who have always existed within STEM communities. Listening to trans* and genderqueer people is vital to informing a constantly evolving ethic of inclusion and care in these communities.

Research Article Inclusion Criteria

We examined how researchers collected, measured, and described data about sex and gender in biology education research (hereafter, gender/sex data). To do this, we chose to focus on articles in CBE-Life Sciences Education (LSE). We analyzed every original research study (n = 328) published in LSE over a recent 5-year period, from 2018 to 2022. We limited our focus to this 5-year period because this timeframe has been a critical period of increased political and social activity regarding the trans* community, with increasing trans* identification and increasingly hostile legislative activity and social attitudes reshaping how trans* students experience college classrooms. Because we were focused on gender/sex data collection, measurement, and description, we excluded essays and review articles. Thus, our data were collected only from original research articles, to specifically capture researchers’ methodologies.

Data Analysis

To develop the codebook, nine co-authors (B.C., B.M., C.G., C.L., C.A.B., K.M., N.B.-C., R.V., T.G.) developed initial guiding questions about the collection, use, analysis, and reporting of gender/sex data in biology education research that were used to inductively code a subset of 15 articles. The coding book was developed through ongoing discussions: once the 15 articles were initially independently coded, the research team continued to discuss codes and definitions until we reached consensus; we continued to recode the articles throughout that process. Throughout our coding process, we reached consensus about uncertainties and disagreements in coding through discussion, discussing the data and codes until reaching agreement among ourselves.

Once consensus regarding the codebook was reached, nine of these 10 co-authors reviewed either 28 or 29 articles; one of the 10 co-authors reviewed 58 articles to replace a researcher who left the team. A total of 328 articles were reviewed and coded using the collaboratively developed coding rubric. Codes were related to gender/sex data collection and description of results, such as how the data were collected and reported, whether the language was inclusive of trans* and genderqueer students, and whether sex and gender were conflated (Supplementary Appendix 1).

To test the reliability of the codes, two co-authors (A.K., L.F.) independently coded a subset of 20 articles, representing one paper from each of the 10 individual coders. This initial step determined whether the codebook was reliable, that is, if it allowed for agreement for researchers who did not participate in original codebook design. This initial examination provided an agreement of 82.4%. After this initial assessment, A.K. and L.F. chose three different, random articles from each of the 10 coders to evaluate for intercoder reliability. The percent agreement across the 30 articles was 83.3%, thus denoting a strong intercoder reliability with use of the codebook (Gisev et al., 2013).

Once coding and coding agreement was complete, we calculated descriptive statistics and created data visualizations in R (R Core Team, 2022). To assess whether there was a change over time with regard to using cisnormative language or conflating sex and gender (e.g., requesting participants to provide gender options but providing words describing biological sex, like “male” and “female), we ran two logistic regression models using the stats package. In each model, year of publication was the predictor and the outcome was whether the article used counternormative language (0/1) or conflated gender/sex (0/1). For each model, we report the odds ratio, calculated by exponentiating the beta coefficient, to characterize the effect size (Deeks et al., 1998; Agresti and Franklin, 2007).

RESULTS

Biology Education Research Studies Most Often Use Surveys to Collect Gender/Sex Data

First, we calculated how many articles that we reviewed (out of n = 328) included the collection of gender/sex data. Although only 33 (10.1%) of the articles reviewed included a focus on gender/sex in their research questions, gender/sex data were collected in 223 (68.0%) of the research articles published in CBE-LSE from 2018-2022. Then, we analyzed how gender/sex data were collected in those 223 articles. The intent of this analysis was to examine the extent to which authors had control over how gender/sex data were collected. For example, gender/sex data gathered from institutional sources granted authors little flexibility in options for which types of gender/sex data were collected, as compared with data collected through a survey designed by the research team. Furthermore, our analysis can serve as a potential proxy for the degree of importance that the authors assigned to collecting gender/sex data.

Researchers most often collected gender/sex data via surveys (56.1%, n = 125) (Figure 1). While we recognize that there are many ways that a research team could collect gender/sex data via surveys (e.g., free response, categorical lists), in many cases the full surveys were not included in the manuscript or corresponding supplemental material so we are unable to analyze differences across these methods. However, in instances where the survey materials were available, they most frequently included categorical lists of gender/sex identities. Gender/sex data were also collected using institutional data (12.6%; n = 28) or interviews (0.9%; n = 2). For the remaining 30.5% (n = 68) of articles, there was no method described for the collection of reported gender/sex data. Given that a majority of research studies used surveys to collect gender/sex data, it can be inferred that most authors had some level of control over the types of information collected and the gender/sex labels or classifications used.

Notably, one-third of the studies without a focus on gender/sex collected these data. Only 33 studies focused on gender/sex as a part of their study purpose, and of those 57.6% collected gender/sex data via surveys, 12.1% via institutional data, and 21.2% did not provide an explanation. The remaining three (9.1%) studies with a focus on gender/sex did not report on the gender/sex data of their participants.

Gender/Sex Data are Most Often Reported Using Cisnormative (e.g., Binary) Language

Regardless of data collection methodology, gender/sex data were most often reported using binary classifications, labels, and language, when gender/sex data were reported (71.7% of the 223 studies that collected gender/sex data). Interestingly, while 68.0% of all studies collected gender/sex data, only 19.5% (n = 64) of all studies reported gender/sex data findings. We labeled an article as using cisnormative language when it collected and presented the data using only dichotomous categories (e.g., using the categories “man” and “woman,” or “male” and “female”). Conversely, an article using language inclusive of trans* and genderqueer individuals acknowledged the diversity of sex and gender identities beyond the binary, such as by adding categories like “nonbinary” or “gender nonconforming” when collecting and presenting data.

When authors relied on institutional gender/sex data, cisnormative language was used 92.9% of the time. When authors used surveys, cisnormative language was considerably reduced (60.4%). Finally, when no details were provided as to what method was used to collect the data, cisnormative language was used 83.6% of the time (Figure 1). The majority of articles used cisnormative language across all data collection methods. However, authors were more likely to use inclusive language and classifications when they had a greater degree of control over the type of gender/sex data collected, such as when researchers designed their own surveys.

In studies where gender/sex was a focus, 56.7% (n = 17) used cisnormative language and the remaining 43.3% used language inclusive of trans* and genderqueer individuals.

Sex and Gender were Conflated Across All Data Collection Methods

We were curious whether authors conflated sex—a classification based on the structural and functional characteristics of a person—with gender—a socially constructed identity. This most commonly manifests in situations where researchers request gender information (most common terms are “man,” “woman,” and “nonbinary,” among many others) but provide options with language relating to biological sex (like “male,” “female,” or “intersex”). Conflation of sex and gender terms may be intentional or unintentional and can be influenced by differences in ever-changing language and cultural interpretations of terms. We used the predominant contemporary definition of sex as including the terms male, female, intersex, etc., and gender as including the terms man, woman, genderqueer, nonbinary, agender, etc. If an author stated that they collected gender data but their categories reflected sex data (e.g., using terms such as “male” and “female”), this was categorized as conflation. We did not find examples of papers whose authors specified working statements on their definitions of sex or gender, and our analysis revealed that 40.5% (n = 133) of all articles conflated sex and gender data. In studies with a focus on gender and/or sex, sex and gender were conflated 57.6% of the time.

Sex and gender were frequently conflated when institutional data were collected (76.0% of 25 articles that reported gender/sex data). Conflation was lowest when gender/sex data were collected via surveys; 52.0% of all articles using surveys (n = 125) conflated sex and gender. In the interview studies (n = 2) where gender/sex was collected, sex and gender were conflated 50.0% of the time; however, we are unable to draw conclusions about this method due to the small sample size. Last, when no explanation was provided for the collection method but gender/sex data were reported, sex and gender were conflated in 77.8% of the 45 articles (Figure 2, A–C).

Articles Often did not Include Trans* and Genderqueer Participants in their Data Analyses and Failed to Acknowledge this as a Limitation

Of the 223 articles that collected gender/sex data, 209 (93.7%) specified how they collected gender/sex data. We expected that only providing cisnormative gender/sex options would result in researchers failing to consider gender diversity in analyses. Indeed, none of the articles with cisnormative gender/sex data collection included trans* and genderqueer identities in their data analysis. Surprisingly, our analysis revealed that even when gender/sex data collection in an article was not cisnormative (n = 49), only 55.1% (n = 27) of articles acknowledged this gender diversity in their analysis. Considering studies with a focus on gender/sex where data were collected using language inclusive of trans* and genderqueer individuals, 53.8% (n = 7) included trans* and genderqueer participants in their data analysis. Therefore, while cisnormative data collection guaranteed that trans* and genderqueer participants were excluded from data analysis, inclusive data collection methods also presented instances of excluding trans* and genderqueer participants from analysis.

Reasons for the lack of representation of trans* and genderqueer participants in data analysis varied depending on whether the articles used cisnormative data collection or not. Studies relying on cisnormative data collection excluded trans* and genderqueer participants in their data analysis due to the limitations of their data. A subset of studies using counternormative data collection practices acknowledged that they did not have enough data to achieve sufficient statistical power to analyze gender minorities (i.e., trans* and genderqueer participants). For example, one publication included in our analysis noted that, “As opposed to combining subcategories, we dropped the gender identity categories of ‘agender’ and ‘genderqueer’ identities from our analysis, as combining these nonbinary gender identities together did not result in statistical power required for analysis” (Weatherton and Schussler, 2022).

Regardless of the reason, good research practice posits that this lack of an exhaustive analysis be addressed in the methods and/or limitations section of a paper. Articles that did not collect, analyze, or discuss gender data representative of trans* and genderqueer participants oftentimes did not address this as a limitation either in the methods section itself or the limitation section of the discussion. Considering that collecting gender/sex data via surveys gives the most control to the research team, we further investigated the data collection and analysis practices for the studies that used surveys to collect gender/sex data and specified how they collected this data. Of the survey studies that used cisnormative data collection (n = 75), only 12.0% addressed gender exclusivity and/or lack of gender diversity as a limitation. Of these survey studies that used counternormative data collection but did not account for that gender diversity in their analyses (n = 19), 36.8% addressed gender exclusivity (i.e., the inclusion of only binary or cisgender students in analysis) and/or lack of gender diversity as a limitation (Figure 3). This trend held for studies that focused on gender/sex, with only 1 of 17 addressing their cisnormative data collection of gender/sex data as a limitation and 3 of 6 addressing the exclusion of trans* and genderqueer identities from their data analysis as a limitation.

The Prevalence of Counternormative Language in Research Articles did not Change Over the 5-Year Period Studied

Given increasing recognition of the unique experiences of trans* and genderqueer students, we predicted that biology education researchers publishing in CBE-LSE would respond with a greater prevalence of data collection and analysis practices representing trans* and genderqueer participants over the 5-year time period. However, there has been no change over time away from cisnormative language (OR = 1.0, p = 0.93) and only a slight decrease in likelihood that sex and gender are conflated (OR = 0.8, p = 0.008; Figure 4) (Supplemental Table S1). Though on a limited timescale, these data indicate that the use of trans* and genderqueer inclusive language has not improved over the past 5 years in articles published in LSE.

DISCUSSION

From our review of research articles in CBE-LSE from 2018 to 2022, we learned that cisnormative language continues to dominate descriptions of gender/sex data, with the majority of sampled studies reporting on gender using exclusively binary language. This trend in our data depicts the explicit exclusion and resulting erasure of trans* and genderqueer participants. Additionally, sex and gender data were often conflated in just over 40% of our sample. Our analysis reveals institutional data as a particular source of concern, as over 70% of articles utilizing institutional data conflated sex and gender. This trend limits research by perpetuating weaponized gender narratives including “biological sex” and biological determinism (Sobieraj, 2020). When trans* and genderqueer students are included in data collection, these data are analyzed or reported in about half of our sample. Furthermore, fewer than 20% of studies that claimed to sample gender reported those data, and few studies acknowledged the practice as a data limitation. The absence of progress toward trans* and genderqueer inclusive language we observed over the past 5 years is an additional point of concern and should be taken into consideration by researchers moving forward. The lack of reporting depicted in our data are not only indications of erasure, but further raise concern for causing unnecessary distress for trans* and nonbinary participants without just intention or effort to represent these populations within the research product. Our findings indicate that the current body of biology education research published in CBE-LSE utilizes design that systematically excludes, erases, and disempowers trans* and genderqueer students. Although our findings are limited to one high impact journal in biology education research, our analysis of publications in one key journal in the field provides an important case study that can serve as a foundation for future research.

In these ways, our data depict research practices inhibiting understanding of trans* and genderqueer students’ experiences by failing to engage and communicate with these participants equitably. This is a form of epistemic injustice known as hermeneutical injustice, as researchers’ lack of responsibility to communicate with and understand marginalized participants results in their exclusion from research, in the lack of empirical development propelling progress for these groups, and in the perpetuation of invalidation and harm among trans* and genderqueer participants (Fricker and Jenkins, 2017). We know that robust and trans*-inclusive survey methods capture richer information about participants compared with conventional (i.e., binary or trinary) gender surveying methods to strengthen our science (Casper, Atadero et al., 2022). Indeed, patches of literature make concerted efforts to depict impactful experiences of trans* and genderqueer individuals in higher education often ignored through inadequate sampling methods (Pryor, 2015; Nicolazzo, 2017; Maloy et al., 2022). These patches create an academic record of the information lost to erasing these populations through cisnormative methods depicted across our data. Our authors have developed guidance informing novel approaches to gathering these missing data in the future.

GUIDING PRINCIPLES FOR INCLUSIVE DATA COLLECTION

We used our findings to develop a set of guiding principles for researchers to consider when incorporating sex and gender data into their experimental design and analysis to include trans* and genderqueer participants and move beyond cisnormative narratives. Further, these principles must be considered by publishers and editors, who serve as distinctly influential members of the research community by leading the final line of defense in flagging actionable areas for LGBTQ+ inclusivity within manuscripts (Cooper et al., 2020). We have taken care to avoid an overly prescriptive “checklist” approach to inclusive practices (Nicolazzo, 2017), as these checklists quickly become outdated, can be (mis)used prescriptively and without thorough consideration, and (mis)lead individuals toward a false destination of inclusive practice rather than guiding individuals through developing ongoing, ever-changing practices (Nicolazzo, 2016). Instead, we aim to highlight ways in which education researchers in biology and other disciplines can engage in reflective practices that encourage us to be more intentional, creative, and inclusive in our exploration of gender as a critical identity variable impacting student experiences within biology education contexts.

First, we recommend using language to distinguish between biological sex and gender. Conflating terms describing gender (man, woman, nonbinary, etc.) with those describing biological sex (male, female, intersex, etc.) obfuscates the experiential differences of individuals with the same assigned sex but differing gender identities. A study that asked students to indicate their sex in a demographic questionnaire would then force trans* and genderqueer participants to interpret the researchers’ intentions or exit the study entirely because their identities are excluded by the assumptions of the research design (Van Anders et al., 2017; Schudson et al., 2019). This uncertainty undermines the power of a study to resolve various gendered experiences in the context of its results.

Based on our study results, we recommend against choosing institutional data as the source for information on participant's gender. In our analysis, institutional data were disproportionately more likely to use cisnormative language (Figure 1) and to conflate sex and gender (Figure 2A) than surveys or nonspecified collection methods. Similarly, none of the studies we examined that used institutional data reported sex or gender using trans* and genderqueer inclusive language (Figure 1). Students also experience rapid identity development, with a significant portion of this development occurring during years traditionally associated with college (Erikson, 1968; McAdams, 1993). Given that most institutional demographic information on sex and gender identity is gathered at enrollment (i.e., freshman year), much of it may be outdated as many students develop their gender identities during their undergraduate years and may have space to report their gender differently without parental supervision on campus. Researchers seeking to improve their methodology should query students for their most-current identity information using methods that accurately represent trans* and genderqueer identities, and they should clearly discuss any known limitations in data acquisition and analysis. As a field, we should take greater accountability for limitations in the data and analysis, regardless of whether the data collection itself was cisnormative or not.

For surveys collecting gender/sex data, we recommend offering a multitude of response options to accurately reflect the diversity of sex and gender that exists within participant populations. Including a third option of “other” in addition to binary categories is the least informative choice and should no longer be used. Only offering two binary options such as “man/male and woman/female” ignores the lived realities of many trans* and genderqueer individuals. The latent cisnormative narratives in binary research design require trans* and genderqueer participants to undergo the stress of navigating norms and being misrepresented or erased entirely. To progress beyond binary methods of inquiry, Casper and authors saw increased reporting of queer identities when participants had extensive options and could select more than one option (Casper, Atadero et al., 2022). However, Puckett and authors state that the variety of responses may be impractical to researchers (Puckett et al., 2020). To address this, Beichel and authors remind researchers to hone in on what aspects of gender are relevant to their studies by showing how different lived identities can be amongst individuals selecting the same option on a survey mechanism (Beischel et al., 2023).

Of the research articles that we reviewed, 33.8% gathered demographic information using surveys which included nonbinary language (Figure 1). Any survey that included trinary gender options or “other” was considered part of this category because these options went beyond binary language, even though they did not meaningfully and accurately represent trans*, genderqueer, and intersex individuals.

One pitfall of this approach is that participants may feel obligated to choose between accurately representing their gender identity or settling for less accurate and affirming options. Not allowing participants to select from multiple representative options may effectively compress trans women, trans men, nonbinary people, and gender nonconforming people into a single umbrella category.

Additionally, utilizing trinaries including the word “other” or “transgender” as the only nonbinary option has a covertly alienating effect known as othering, which situates the binary gender options as the norm and the trans* and genderqueer options as aberrations (Blair and Deckman, 2019). If participants cannot select multiple options, researchers compress trans women, trans men, nonbinary people, and gender nonconforming people into a single umbrella category. This creates the uncomfortable situation where individuals must choose between accurately representing their gender identity or settling for less accurate and affirming options. In essence, any “third option” to a single question will compress some dimension of the identities of participants and reduce the quality of the resulting data to a gender trinary stunted in almost the exact ways as gender binaries. Reasons for not including gender affirming options in biology education research should be discussed in the study limitations.

ADDITIONAL CONSIDERATIONS

In addition to the above recommendations that are rooted in the data reported in this manuscript, we provide the following additional considerations that education researchers, authors, and editors may want to consider in their efforts to collect and report data in a more inclusive manner.

In addition to expanding language beyond trinaries, we suggest that surveys can be improved by exploring survey mechanisms with potential to accommodate intersectionality, fluidity, and autonomy for participants. Queered survey methods include updated diverse options, allow participants to select multiple options (Casper, Atadero et al., 2022), and protect genderqueer participants from erasure (Fish and Russell, 2018). Queered survey designs capture both a greater number and greater diversity of responses from trans* and gender queer individuals compared with conventional (i.e., binary or trinary) demographic surveys (Casper, Atadero et al., 2022). Including a free answer box is not in itself a solution because the same study found that open-ended demographic prompts, though well-intentioned, have a significant no-response rate. Further, allowing participants to select multiple answers on one question with inclusive options is more appropriate, efficient, and manageable than asking an extensive series of clarifying questions regarding sex/gender, a method sometimes suggested due to its utilization in medical research (Tate et al., 2013; Bosse and Chiodo, 2016; Bauer et al., 2017; Frohard-Dourlent et al., 2017). Last, allowing multiple-select enhances accuracy when recording the multidimensionality and fluidity of queer identities (Galupo et al., 2017), while still allowing for analytical differentiation and contextualization when processing data (Harrison et al., 2012). Therefore, we recommend that researchers utilizing demographic surveys enable participants to check multiple boxes referring to distinct identities.

When gender identity is recorded for formal statistical analyses in sample populations with low numbers of trans* and genderqueer participants, researchers should consider a follow-up question regarding informed consent to analytically required grouping of participants into gendered categories. This approach should include an option that gives participants the autonomy to resist the expectations of the analysis (e.g., “In the case that representative groups must be formed for some parts of the data analysis, which of the following groups most accurately describes you within the context of this research: “woman”, “man”, “trans* and/or genderqueer,” “exclude my data from those analyses”). Including this measure of informed consent within the survey mechanism is important because it is likely to be overlooked if added onto already lengthy consent forms for recruitment, thus ultimately inhibiting informed consent (Perrault and Nazione, 2016). Further, identities of participants who are ultimately excluded from data analysis are still recorded and must be reported to accurately describe the analyzed and excluded populations and inform the future development of representative methods uniquely designed to include previously erased populations (Doan, 2011). This approach is most appropriately utilized when absolutely necessary to avoid undue stress when asking participants to categorize themselves into the limiting assumptions of essential statistical analyses. If there is any intention to entirely exclude genderqueer data from analysis and reporting, risk of erasure should be disclosed during recruitment to obtain informed consent from populations uniquely impacted by this risk (Karbwang et al., 2018; Millum and Bromwich, 2021).

No matter how the categories are constructed, the resulting sample size of the trans* and genderqueer dataset is likely to be small. At extremely small sample sizes, if excluding trans* and genderqueer data is required to fulfill the assumptions of the statistical analysis and no alternatives are available, we recommend that this action is explicitly acknowledged in the discussion as a limitation of the quantitative analysis included in the research methodology (as was done by the studies represented in yellow inFigure 3). If trans* and genderqueer responses are noticeably present but small in proportion compared with the general study population, researchers may choose to present the analysis of trans* and genderqueer responses alone with the caveat that findings for this group may be less robust due to the smaller sample size. This is important because oppression and support impacting trans* and genderqueer participants do not need to be statistically significant to be acted upon on an individual level, or to signal a need for follow-up research further amplifying silenced populations.

Ultimately, there is no one-size-fits-all approach for how to best collect and analyze data on participant gender/sex (Casper, Atadero et al., 2022). It is up to researchers to take into consideration their study's research questions, overall aims, and logistical limitations when selecting an approach that is most appropriate for their study. While our data directly depict erasure of trans* and genderqueer participants in demographic data, the significant parallels of exclusionary research design across our sample logically suggest causal epistemological limits within the discipline which have been neglected.

LIMITATIONS

The results described here should be interpreted with some caution, given the limited disciplinary and chronological scope of our analysis. Although we provide a comprehensive analysis of all biology education research articles published over a recent 5-year period in CBE-LSE, it is possible that similar analyses performed over different time periods or in different journals might portray an alternative landscape of trans* inclusivity or erasure. Indeed, prior research has suggested that across STEM fields, there is significant variance in perceived openness to inclusion of LGBTQ+ individuals (Yoder and Mattheis, 2016). Additionally, given the rapidly changing nature of societal attitudes toward trans* populations, care must be taken to avoid extrapolating current trends beyond the near future (Parker et al., 2022). Future analyses should consider whether and how other STEM disciplines are incorporating the perspectives and experiences of these students within education research.

CONCLUSION

In conclusion, our analysis of biology education research published in CBE-LSE between 2018 and 2022 depicts significant trends of dismissal of trans* and genderqueer identities in research participants. Only 8% of the biology education research studies we analyzed collected demographic data on the identities of trans* and genderqueer students and included those students’ experiences in their analyses. For undergraduate STEM education to become a more inclusive place for students with diverse social identities and life experiences, it is essential that we undertake a critical reflection and revision of our research practice to include trans* and genderqueer students. While not providing a checklist or an endpoint for inclusive research practices, we have provided a set of recommendations to reduce harm and begin a restorative process of producing more equitable and impactful undergraduate STEM education research for all.

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