Chapter 3 Results

3.1 Demographics

477 undergraduates from Reed College participated in this study. Their median age was 20 (M = 20.14, SD = 1.32). A majority of participants identified as White (74.2%). The sample also included 9.4% mixed ethnicity, 7.1% Asian, 1.7% Black or African American, and 1.3% Hispanic/Latino participants. 5.9% of participants preferred not to disclose their ethnicity. When compared to data on first year students’ ethnicity, this sample appears to be approximately representative of the population (Reed College Institutional Research, 2019).

There were 102 first years, 118 second years, 131 third years, and 120 fourth years in the sample. There were 38 majors represented in the sample, including 15 majors with 10 or more students represented. The most common majors were psychology (N = 32), biology (N = 27), anthropology (N = 26), english (N = 24), political science (N = 21), chemistry (N = 19), linguistics (N = 19), comparative literature (N = 18), history (N = 18), and computer science (N = 17).

3.1.1 Gender

Gender-related demographic data was collected by asking participants to write in their gender identity and answer a series of yes/no questions: “Are you cisgender?,” “Are you transgender?,” and “Is your gender non-binary?” Answering yes on one question did not force the participants to answer no on others—this treated gender identity as a collection of separate, related labels that participants may or may not identify with simultaneously. Responses for the write-in question were qualitatively coded by the author.

Overall, 317 participants identified as cisgender, 81 identified as transgender, and 141 identified their gender as non-binary. It is important to note that there is overlap among these groups. 63 participants said they were transgender and non-binary, 16 participants said they were cisgender and non-binary, and 1 participant said they were cisgender, transgender, and non-binary.

Qualitative themes were decided by the author after examining the data. She used her own knowledge of gender terminology, as well as the help of a number of transgender and non-binary peers. The most commonly occurring themes were woman (N = 220), man (N = 120), non-binary (N = 94), cisgender (N = 36), transgender (N = 26), questioning (N = 24), masculine (N = 18), agender (N = 15), genderfluid (N = 15), and queer (N = 8).

For the purposes of analysis, seven artificial gender groups were created: cisgender man, cisgender woman, transgender man, transgender woman, cisgender non-binary person, non-binary person, and transgender non-binary person. It is important to note that these bins are artificial and are not representative of each individual’s own gender and experience. For example, “non-binary” can have many meanings and is best understood as an umbrella term that encompasses many genders, including individuals whose gender is just “non-binary.”

Table 3.1: Artificial gender bins created for the purpose of analysis.
Gender Bin N
Cis Woman 182
Cis Man 101
Non-binary 80
Trans Non-binary 48
Trans Woman 20
Cis Non-binary 15
Trans Man 12

The cisgender man and cisgender woman groups include all participants that only indicated that they were cisgender and indicated that they were a man or woman in the write-in gender field. The transgender man and transgender woman groups were the same as the cisgender groups, but included participants who indicated that they were transgender.

The cisgender non-binary group includes all participants who indicated that they were cisgender and non-binary. This group includes cisgender non-binary men and cisgender non-binary women. The non-binary group includes all participants that only indicated that they were non-binary, as well as participants who indicated that they were neither cisgender nor transgender. This group includes non-binary men and non-binary women. The transgender non-binary group includes all participants that indicated that they were non-binary and transgender. This group includes transgender non-binary men and transgender non-binary women.

3.1.2 Pronouns

Participants were asked their pronouns in a write-in box. Pronouns were qualitatively coded by the author. No participants reported using any other pronouns besides he/him, she/her, and they/them. However, many participants reported using multiple pronouns. It should be noted that individuals that use multiple pronouns may prefer one over the other, or use different pronouns in specific situations. This is not reflected in these data.

Table 3.2: Participant pronouns
Pronouns N
she/her 199
he/him 127
they/them 65
she/her & they/them 35
he/him & they/them 19
all pronouns 10
he/him & she/her 2

The most common gender and pronoun combinations were cisgender women that used she/her, (N = 175), cisgender men that used he/him, (N = 96), transgender non-binary people that used they/them, (N = 32), non-binary people that used they/them, (N = 28), non-binary people that used she/her and they/them, (N = 16), trans men that used he/him, (N = 12), and trans women that used she/her, (N = 11).

3.1.3 Sexuality

Participants were asked to report their sexuality in a write-in field. Responses were qualitatively coded by the author. Many responses were coded with multiple themes, so the total N exceeds the sample size. One exceptionally common response was “bisexual/pansexual,” (N = 11), which was coded with both themes.

Table 3.3: Participant sexuality
Sexuality N
Bisexual 178
Straight 115
Pansexual 49
Queer 40
Questioning 39
Gay 35
Lesbian 35
Asexual 16
Aspec 15

“Aspec” was an umbrella term for sexual orientations that fell under the asexual/aromatic umbrella. Tese were a variety of orientation that involved the split sexuality/romantic attraction model (Mod J, 2017). Additionally, 3 participants described their sexuality as demisexual, 2 as polyamourous, and 1 as enbian. Some terms, such as “gynophile,” were coded as “straight” or “queer” depending on the participant’s gender.

The most common gender and sexualities were bisexual cisgender women, (N = 70), straight cisgender men, (N = 56), straight cisgender women, (N = 50), bisexual non-binary people, (N = 33), bisexual cisgender men, (N = 26), and bisexual transgender non-binary people, (N = 23).

3.2 Experiences with Misgendering

Similar to McLemore (2015), we had participants report how frequently they were misgendered and how stigmatized it made them feel. However, unlike McLemore (2015), we administered these questions to cisgender people as well. Independent t-tests were used to compare the cisgender and non-cisgender participants. Non-cisgender participants (M = 3.28, SD = 0.96) reported being misgendered more frequently than cisgender participants (M = 1.45, SD = 1.45), t(231) = 21.6, p < 0.001. Non-cisgender participants (M = 3.15, SD = 1.3) also reported feeling more stigmatized when misgendered than than cisgender participants (M = 1.59, SD = 1.59), t(261) = 12.9, p < 0.001.

Table 3.4: Misgendering frequency for non-cisgender and cisgender participants
“How often do people ‘misgender’ you?” Non-cisgender (%) Cisgender (%)
Never 6.4 68.8
Rarely 14.0 24.9
Sometimes 30.6 4.7
Often 44.6 1.3
Always 4.5 0.3
Table 3.5: Felt stigma when misgendered for non-cisgender and cisgender participants
“I feel stigmatized (…) when I am misgendered.” Non-cisgender (%) Cisgender (%)
Not at all 12.2 68.5
Slightly 20.5 12.0
Somewhat 28.2 13.4
Considerably 18.6 4.0
Very 20.5 2.2

Pearson’s Chi-squared tests were used to compare the misgendering frequency observed in McLemore (2015) to the non-cisgender participants in the present study. There were significant differences when compared to both the study 1 population, X2 (4, N = 864) = 178.18, p < 0.001, and the study 2 population, X2 (4, N = 902) = 228.69, p < 0.001.

We performed a one-way ANOVA examining gender and pronouns’ effect on misgendering frequency and felt stigma. There was a significant effect of gender, F(6, 428) = 131.73, p < 0.001, and pronouns, F(6, 428) = 12.53, p < 0.001, on misgendering frequency. A post-hoc Tukey test revealed that cis men, (M = 1.3, SD = 0.5), and cis women, (M = 1.36, SD = 0.62), get misgendered less frequently than trans men, (M = 3.25, SD = 0.87), trans women, (M = 3.5, SD = 0.95), cis non-binary people, (M = 2.07, SD = 1.28), non-binary people, (M = 3.03, SD = 1.06), and trans non-binary people, (M = 3.56, SD = 0.77). Cis non-binary people also get misgendered less than trans men men, trans women, non-binary people, and trans non-binary people. Trans non-binary people also get misgendered more than non-binary people. Additionally, people who use they/them pronouns, (M = 3.71, SD = 0.82), get misgendered more than people who use he/him pronouns, (M = 1.6, SD = 0.94), she/her pronouns, (M = 1.48, SD = 0.79), both he/him and they/them pronouns, (M = 2.84, SD = 1.01), and both she/her and they/them pronouns, (M = 2.66, SD = 1.08).

There was also a significant effect of gender, F(6, 389) = 43.4, p < 0.001, but not of pronouns, F(6, 389) = 0.74, p = 0.61, on felt stigma when misgendered. A post-hoc Tukey test revealed that cis men, (M = 1.42, SD = 0.88), and cis women, (M = 1.67, SD = 1.05), feel less stigmatized when misgendered than trans men, (M = 4.25, SD = 0.75), trans women, (M = 3.45, SD = 1.54), non-binary people, (M = 2.59, SD = 1.09), and trans non-binary people, (M = 3.62, SD = 1.23). Cis non-binary people, (M = 1.87, SD = 0.99), also feel less stigmatized when misgendered than trans men, trans women, and trans non-binary people. Non-binary people also feel less stigmatized when misgendered than trans men and trans non-binary people.

3.3 Gender Congruence

Kozee et al. (2012) developed the TCS (Transgender Congruence Scale) to measure transgender individuals’ relationship and comfort between their inner gender identity, physical appearance, and social experience of gender. In this study, the TCS was administered to cisgender participants as well.

A single sample t-test revealed that non-cisgender participants (M = 34.26, SD = 5.5) scored lower on the TCS than cisgender participants (M = 45.53, SD = 6.23), t(348.89) = -20.04, p < 0.001.

A one-way ANOVA demonstrated significant effects of gender on TCS scores, F(6, 445) = 71.24, p < 0.001. A post-hoc Tukey test revealed that cis men, (M = 46.19, SD = 5.55), and cis women, (M = 45.98, SD = 5.8), have significantly higher TCS scores than trans men, (M = 36.08, SD = 2.84), trans women, (M = 35.11, SD = 4.12), cis non-binary people, (M = 37.93, SD = 9.05), non-binary people, (M = 33.97, SD = 5.89), and trans non-binary people, (M = 33.94, SD = 5.81).

TCS Scores by Gender

Figure 3.1: TCS Scores by Gender

A possible relationship between congruence and misgendering frequency was explored. A factorial ANOVA revealed that congruence had a significant effect on misgendering frequency, F(1, 424) = 136.56, p < 0.001 and felt stigma when misgendered, F(1, 424) = 69.06, p < 0.001, but not frequency and stigma when combined as a single factor, F(1, 424) = 0.2, p = 0.65.

3.4 Transgender Inclusive Behaviors

Kattari et al. (2018) developed the Transgender Inclusive Behavior Scale (TIBS) as a method of quantifying the number of behaviors that may support and include transgender people that one regularly does. Scores are a sum of responses on a series of five-point likert scales ranging from “Never” to “Often.”

An independent samples t-test revealed that non-cisgender people (M = 51.34, SD = 9.14) reported performing more inclusive behaviors than cisgender people (M = 41.98, SD = 9.26), t(304) = 10.22, p < 0.001.

A one-way ANOVA demonstrated that there was a significant effect of gender F(6, 260) = 26.14, p < 0.001. A Tukey post-hoc comparison revealed that cisgender men (M = 37.31, SD = 8.92) do significantly fewer trans inclusive behaviors than cisgender women (M = 44.43, SD = 8.18), transgender men (M = 55.91, SD = 9.16), transgender women (M = 50.58, SD = 9.97), cisgender non-binary people (M = 45.73, SD = 8.18), non-binary people (M = 49.26, SD = 9.3), and transgender non-binary people (M = 53.85, SD = 7.71). Cisgender women do significantly fewer trans inclusive behaviors than transgender men, transgender women, non-binary people, and transgender non-binary people. Cisgender non-binary people also do fewer trans inclusive behaviors than transgender non-binary people.

TIBS Scores by Gender

Figure 3.2: TIBS Scores by Gender

3.5 Pronouns

3.5.1 Comfort sharing pronouns

Items 1 (“I feel comfortable sharing my pronouns in most settings”), 2 (“I feel comfortable sharing my pronouns in non-academic settings in the Reed community”), 3 (“I feel comfortable sharing my pronouns in classes at Reed”), 7 (“I feel more comfortable sharing my pronouns if I am with people who may have similar gender identities to me”), 8 (“I feel more comfortable introducing myself with my pronouns if someone else does first”), and 9 (“I feel more comfortable introducing myself with my pronouns in class if the professor does first”) touched on participant’s comfort sharing their pronouns. A one-way ANOVA found a significant effect of setting, F(2, 1311) = 16.39, p < 0.001, gender, F(6, 1311) = 40.08, p < 0.001, and pronouns, F(6, 1311) = 19.19, p < 0.001, on comfort sharing pronouns. A post-hoc Tukey test found that generally, students are more comfortable sharing pronouns in class, (M = 4.5, SD = 0.98), and in non-academic settings at Reed, (M = 4.43, SD = 1.07), than they are in general, (M = 4.14, SD = 1.31). It also found that cisgender men, (M = 4.65, SD = 0.78), are more comfortable sharing their pronouns than trans men, (M = 4.11, SD = 1.24), trans women, (M = 3.22, SD = 1.51), and non-binary people, (M = 3.66, SD = 1.4).

One-way ANOVAs were used on each setting to elucidate effects of gender and pronoun within each setting. There were significant effects of gender in general, F(6, 435) = 34.7, p < 0.001, in non-academic settings at Reed, F(6, 435) = 9.07, p < 0.001, and in class, F(6, 435) = 19.93, p < 0.001. There were also significant effects of pronouns in general, F(6, 435) = 34.7, p < 0.001, in non-academic settings at Reed, F(6, 435) = 9.07, p < 0.001, and in class, F(6, 435) = 19.93, p < 0.001.

Responses to items 1 ("I feel comfortable sharing my pronouns in most settings"), 2 ("I feel comfortable sharing my pronouns in non-academic settings in the Reed community"), 3 ("I feel comfortable sharing my pronouns in classes at Reed")

Figure 3.3: Responses to items 1 (“I feel comfortable sharing my pronouns in most settings”), 2 (“I feel comfortable sharing my pronouns in non-academic settings in the Reed community”), 3 (“I feel comfortable sharing my pronouns in classes at Reed”)

Post-hoc Tukey tests were used to compare gender groups within each setting. In a general setting, cis men, (M = 4.53, SD = 0.93), were more comfortable sharing their pronouns than trans women, (M = 4.76, SD = 0.68), non-binary people, (M = 3.02, SD = 1.5), and transgender non-binary people, (M = 3.25, SD = 1.49). In addition, cis women, (M = 4.76, SD = 0.68) were more comfortable sharing their pronouns than trans men, (M = 3.67, SD = 1.67), trans women, cisgender non-binary people, (M = 3.87, SD = 1.13), non-binary people, and transgender non-binary people. In non-academic settings at Reed, cis men, (M = 4.59, SD = 0.85), and cis women, (M = 4.59, SD = 0.85), were more comfortable sharing their pronouns than trans women, (M = 3.4, SD = 1.6), cis non-binary people, (M = 3.8, SD = 1.52), non-binary people, (M = 4.04, SD = 1.16), and trans non-binary people, (M = 4.1, SD = 1.39). In class, cis men, (M = 4.74, SD = 0.6), and cis women, (M = 4.85, SD = 0.53), were more comfortable sharing their pronouns than trans women, (M = 3.35, SD = 1.57), non-binary people, (M = 3.82, SD = 1.28), and trans non-binary people, (M = 4.17, SD = 1.14). Cis women were also more comfortable sharing their pronouns than cis non-binary people, (M = 4.4, SD = 0.83). Finally, trans women were less comfortable sharing their pronouns than cis non-binary people and trans non-binary people.

A one-way ANOVA was used to examine effects of social factors, gender, and pronouns on comfort sharing pronouns. Specifically, we examined whether people were more comfortable sharing their pronouns when a professor did so first, when someone else did first, and when the participant was with people of similar genders to their own. There were significant effects of social factor, F(2, 1311) = 60.03, p < 0.001, gender, F(6, 1311) = 6.95, p < 0.001, and pronouns, F(6, 1311) = 15.66, p < 0.001. A post-hoc Tukey test revealed that someone else saying their pronouns first makes the largest difference in making others comfortable sharing their pronouns. This is followed by the professor sharing their pronouns first, and finally the presence of people of similar genders to one’s own.

Responses to items 7 ("I feel more comfortable sharing my pronouns if I am with people who may have similar gender identities to me"), 8 ("I feel more comfortable introducing myself with my pronouns if someone else does first"), and 9 ("I feel more comfortable introducing myself with my pronouns in class if the professor does first")

Figure 3.4: Responses to items 7 (“I feel more comfortable sharing my pronouns if I am with people who may have similar gender identities to me”), 8 (“I feel more comfortable introducing myself with my pronouns if someone else does first”), and 9 (“I feel more comfortable introducing myself with my pronouns in class if the professor does first”)

3.5.2 Desire to share pronouns

Items 4 (“I want to share my pronouns in most settings”), 5 (“I want to share my pronouns in non- academic settings in the Reed community”), and 6 (“I want to share my pronouns in classes at Reed”) touched on participant’s desire to share their pronouns. A one-way ANOVA revealed significant effects of setting, F(2, 1314) = 18.12, p < 0.001, gender, F(6, 1314) = 7.22, p < 0.001, and pronouns F(6, 1314) = 13.46, p < 0.001. A post-hoc Tukey test revealed that people’s desire to share their pronouns is highest in classroom settings, followed by non-academic settings at Reed, and then lowest in general. Trans men reported a higher desire to share their pronouns than cisgender men, cisgender women, transgender women, cisgender non-binary people, and non-binary people. Transgender non-binary people also reported a higher desire to share their pronouns than cisgender men and non-binary people.

Responses to items 4 ("I want to share my pronouns in most settings"), 5 ("I want to share my pronouns in non- academic settings in the Reed community"), and 6 ("I want to share my pronouns in classes at Reed")

Figure 3.5: Responses to items 4 (“I want to share my pronouns in most settings”), 5 (“I want to share my pronouns in non- academic settings in the Reed community”), and 6 (“I want to share my pronouns in classes at Reed”)

3.5.3 Concerns about sharing pronouns

Items 10 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in most settings”), 11 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in non-academic settings in the Reed community”), and 12 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in class at Reed”) touched on participant’s concern that sharing their pronouns would draw unwanted attention to themselves. There were significant effects of setting, F(2, 1314) = 27.49, p < 0.001, gender F(6, 1314) = 19.69, p < 0.001, and pronouns, F(6, 1314) = 23.44, p < 0.001 on concern that sharing one’s pronouns would draw unwanted attention to oneself. A post-hoc Tukey test revealed that participants were most concerned that sharing their pronouns would draw unwanted attention to them in general, followed by in non-academic settings at Reed, and least concerned in class.

Responses to items 10 ("I am concerned that sharing my pronouns will draw unwanted attention to myself in most settings"), 11 ("I am concerned that sharing my pronouns will draw unwanted attention to myself in non-academic settings in the Reed community"), and 12 ("I am concerned that sharing my pronouns will draw unwanted attention to myself in class at Reed")

Figure 3.6: Responses to items 10 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in most settings”), 11 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in non-academic settings in the Reed community”), and 12 (“I am concerned that sharing my pronouns will draw unwanted attention to myself in class at Reed”)

3.5.4 Congruence and perception of pronouns

Items 13, 14, 15, 16, 17 and 18 were centered around participant’s feelings of congruence between their pronouns and other aspects of their gender. We ran one-way ANOVAs examining effects of gender and pronouns on each item with post-hoc Tukey tests where relevant.

On item 13 (“I feel that the gender that people perceive me as and my pronouns are consistent with one another.”), there was a significant effect of gender, F(6, 449) = 116.89, p < 0.001. A post-hoc Tukey test found that cis men, (M = 4.76, SD = 0.6), experience higher consistency than trans men, (M = 2.58, SD = 1.62), trans women, (M = 2.05, SD = 1.1), cis non-binary people, (M = 3.13, SD = 1.77), non-binary people, (M = 2.2, SD = 1.27), and trans non-binary people, (M = 1.85, SD = 1.07). Cis women, (M = 4.65, SD = 0.85), also experience higher consistency than trans men, trans women, cis non-binary people, non-binary people, and trans non-binary people. Cis non-binary people also experience higher consistency than trans women. Finally, cis non-binary people experience higher consistency than non-binary people and trans non-binary people. There were no other significant differences between groups.

On item 14 (“I feel that my internal gender identity and pronouns are consistent with one another.”), there was a significant effect of gender, F(6, 430) = 18.52, p < 0.001 and pronouns, F(6, 430) = 3.87, p < 0.001. A post-hoc Tukey test found that cis men, (M = 4.59, SD = 0.8), and cis women, (M = 4.53, SD = 0.93), reported higher consistency than cis non-binary people, (M = 3.07, SD = 1.67), non-binary people, (M = 3.23, SD = 1.42), and trans non-binary people, (M = 3.85, SD = 1.34). Trans men, (M = 4.5, SD = 1.17), also reported higher consistency than cis non-binary people and non-binary people. Trans non-binary people also reported higher consistency than non-binary people. People who use they/them and she/her pronouns, (M = 3.03, SD = 1.53), reported higher consistency than people who just used they/them pronouns, (M = 3.85, SD = 1.21). There were no other significant differences between groups.

On item 15 (“I feel that my pronouns represent my gender identity well.”), there was a significant effect of gender, F(6, 450) = 14.67, p < 0.001. A post-hoc Tukey test revealed that cis men, (M = 4.35, SD = 1.06), and cis women, (M = 4.39, SD = 1.07), reported higher representativeness than cis non-binary people, (M = 3.07, SD = 1.67), non-binary people, (M = 3.11, SD = 1.46), and trans non-binary people, (M = 3.71, SD = 1.3). Furthermore, trans men, (M = 4.5, SD = 0.9), reported higher representativeness than cis non-binary people and non-binary people. There were no other significant differences between groups.

Responses to items  13 ("I feel that the gender that people perceive me as and my pronouns are consistent with one another."), 14 ("I feel that my internal gender identity and pronouns are consistent with one another."), and 15 ("I feel that my pronouns represent my gender identity well.")

Figure 3.7: Responses to items 13 (“I feel that the gender that people perceive me as and my pronouns are consistent with one another.”), 14 (“I feel that my internal gender identity and pronouns are consistent with one another.”), and 15 (“I feel that my pronouns represent my gender identity well.”)

On item 16 (“If I don’t tell people what my pronouns are, they will misgender me.”), there was a significant effect of gender, F(6, 450) = 75.91, p < 0.001. A post-hoc Tukey test revealed that cis men, (M = 1.95, SD = 0.3), and cis women, (M = 1.91, SD = 0.47), are misgendered significantly less when they do not share their pronouns when compared to trans men, (M = 3.75, SD = 1.54), trans women, (M = 4.1, SD = 1.25), non-binary people, (M = 3.32, SD = 1.54), and trans non-binary people, (M = 4.31, SD = 1.17). Furthermore, cis non-binary, (M = 2.47, SD = 0.92), people are misgendered significantly less than trans men, trans women, and non-binary people. There were no other significant differences between groups.

On item 17 (“I don’t need to tell people what my pronouns are, because they usually assume correctly.”), there was a significant effect of gender, F(6, 449) = 78.45, p < 0.001. A post-hoc Tukey test revealed that people correctly assume cis men’s, (M = 4.56, SD = 0.95), and cis women’s, (M = 4.49, SD = 1.09), pronouns more frequently when compared to trans men, (M = 2.5, SD = 1.17), trans women, (M = 2.15, SD = 1.04), cis non-binary people, (M = 3.27, SD = 1.58), non-binary people, (M = 2.46, SD = 1.2), and trans non-binary people, (M = 1.92, SD = 0.65). Cis non-binary people’s pronouns are also assumed correctly more frequently than trans women’s and trans non-binary people.

Responses to items 16 ("If I don’t tell people what my pronouns are, they will misgender me.") and 17 ("I don’t need to tell people what my pronouns are, because they usually assume correctly.")

Figure 3.8: Responses to items 16 (“If I don’t tell people what my pronouns are, they will misgender me.”) and 17 (“I don’t need to tell people what my pronouns are, because they usually assume correctly.”)

Finally, on item 18 (“I feel like people understand me better when I share my pronouns.”), there was a significant effect of gender, F(6, 449) = 25.69, p < 0.001. A post-hoc Tukey test revealed that trans men, (M = 3.58, SD = 1.56), trans women, (M = 3.7, SD = 1.22), non-binary people, (M = 3.67, SD = 1.22), and trans non-binary, (M = 3.98, SD = 1.12), people feel better understood when they share their pronouns when compared to cis men, (M = 2.39, SD = 0.93) and cis women, (M = 2.54, SD = 0.96).

Responses to item 18 ("I feel like people understand me better when I share my pronouns.")

Figure 3.9: Responses to item 18 (“I feel like people understand me better when I share my pronouns.”)

3.5.5 Historical experience at Reed College

Item 19 (“In classes at Reed, professors usually introduce themselves with their pronouns”) asked students to report how frequently professors introduced themselves with their pronouns. A one-way ANOVA did not find a significant effect of gender, F(6, 339) = 1.97, p = 0.07, or major, F(70, 339) = 1.26, p = 0.1, on reported frequency of professors sharing their pronouns. However, when we only compared majors in which we had more than 6 students in, there was a significant effect of major, F(18, 301) = 2.23, p < 0.001, but not gender, F(6, 301) = 2.04, p = 0.06.

Responses to items 19 ("In classes at Reed, professors usually introduce themselves with their pronouns")

Figure 3.10: Responses to items 19 (“In classes at Reed, professors usually introduce themselves with their pronouns”)

Item 20 (“In classes at Reed, students usually introduce themselves with their pronouns”) asked students to report how often their peers introduced themselves with their pronouns. A one-way ANOVA revealed a significant effect of gender, F(6, 339) = 3.67, p < 0.001, but not major. When we only compared majors that we had more than 6 students in, there were significant effects of gender, F(6, 301) = 3.17, p < 0.001, but not major, F(18, 301) = 1.35, p = 0.16. A post-hoc Tukey test revealed that trans women, (M = 2.25, SD = 1), report that students share their pronouns significantly less than cis men, (M = 2.99, SD = 0.93), cis women, (M = 3.12, SD = 0.75), cis non-binary people, (M = 3.33, SD = 0.49), and non-binary people, (M = 2.98, SD = 0.81) do.

Responses to items 20 ("In classes at Reed, students usually introduce themselves with their pronouns")

Figure 3.11: Responses to items 20 (“In classes at Reed, students usually introduce themselves with their pronouns”)

It should be noted that no participants responded “Strongly disagree” to item 20, indicating that it’s common for at least some students to share their pronouns in most classes.

3.5.6 Primary Component Analysis

Principal component analysis (PCA) is a method of simplifying a model containing many variables to a small number of components that explain more variation than one component could do alone. We used PCA on the pronoun and misgendering data. Using a Screen plot, we retained three components with an eigenvalue of 3.07, accounting for 52.16% of the variance.

Table 3.6: PCA Component Loadings. Variables are results from the survey, in order of presentation.
Variable Comp. 1 Comp. 2 Comp. 3
cis -0.12 -0.01 0.01
trans 0.07 0.02 0.03
nonbinary 0.11 0.01 -0.02
gender.man -0.04 -0.03 0.02
gender.woman -0.05 0.02 0.01
comfort_general -0.26 0.21 0.09
comfort_reed -0.12 0.22 0.00
comfort_class -0.15 0.21 0.04
desire_general 0.02 0.42 0.03
desire_reed 0.11 0.42 -0.04
desire_class 0.06 0.41 -0.03
comfort_withsimilargenders 0.27 0.21 -0.03
comfort_someoneelsefirst 0.03 0.16 0.22
comfort_proffirst 0.04 0.18 0.21
attention_general 0.27 -0.15 0.38
attention_reed 0.12 -0.18 0.56
attention_class 0.16 -0.14 0.37
gender_perception_consistent -0.40 0.03 0.26
gender_pronouns_consistent -0.15 0.21 0.25
pronouns_represent -0.14 0.22 0.28
willmisgender_ifnopronouns 0.30 0.09 -0.06
assume_pronouns_correctly -0.37 -0.03 0.13
understand_better 0.20 0.19 0.03
profs_share -0.08 0.02 -0.18
students_share -0.03 0.04 -0.07
reed_support -0.19 -0.09 -0.05
misgendering_freq 0.30 0.02 -0.08
misgendering_stigma 0.24 0.12 0.14

Inspection of the first component’s loadings indicate that consistency between others’ perception of one’s gender, others’ assumptions about gender and pronouns, misgendering, and comfort when with people with similar genders to one’s own are making significant contributions to the first component. Because these items are mainly concerned with the assumptions other people place on one’s gender and pronouns, this component appears to be the amount that cisnormative assumptions about one’s gender and appearance harms individuals.

Loadings from the second component encompasses one’s desire to share one’s pronouns in various settings, as well as how comfortable one feels doing so. Because the largest loading in the second component is one’s desire to share pronouns, this seems to indicate one’s readiness to share pronouns.

Loadings from the third component emphasize concern that sharing one’s pronouns will draw unwanted attention, as well as when others—not necessarily of the same gender—share their pronouns first and how consistent and representative one’s pronouns are with one’s gender. This component appears to represent concern around sharing pronouns and fears of judgment or lack of understanding about one’s pronouns. While this may seem like the inverse of component 2, it’s possible that one may not want to share their pronouns, but be relatively unconcerned that doing so would draw unwanted attention or harm. So, we retained component 3 in addition to component 2.

PCA Components 1 & 2 by Gender. Percentage values along the axes represent % variation in the data explained by the component.

Figure 3.12: PCA Components 1 & 2 by Gender. Percentage values along the axes represent % variation in the data explained by the component.

A one-way ANOVA indicated a significant effect of gender, F(6, 377) = 219.3, p < 0.001 on the first component. A post-hoc Tukey test revealed that cisgender men, (M = -2.7, SD = 1.05), and women, (M = -2.21, SD = 1.35), are significantly less affected by cisnormativity than trans men, (M = 3.49, SD = 2.68), trans women, (M = 4.48, SD = 2.09), cisgender non-binary people, (M = 0.69, SD = 2.87), non-binary people, (M = 3.37, SD = 2.25), and transgender non-binary people, (M = 4.57, SD = 1.35). Cisgender non-binary people are also less affected than trans men, trans women, non-binary people, and transgender non-binary people. Trans non-binary people are also more affected than non-binary people. Additionally, results of Spearman correlations indicated a significant negative relationship between the first component and TCS scores, rs(382) = -0.72, p < 0.001, and a significant positive relationship with TIBS scores, rs(382) = 0.51, p < 0.001.

PCA Component 1 by Gender

Figure 3.13: PCA Component 1 by Gender

Visualization of the first component indicated possible bimodality along the first component. Hartigan’s dip test indicated that the distribution along the first component is unlikely to be unimodal, (D = 0.031, p = 0.009). Experiences with cisnormativity may be as bimodal. This indicates that cisgender and non-cisgender people may have significantly different experiences navigating the world as their gender.

Another one-way ANOVA demonstrated a significant effect of gender, F(6, 377) = 6.14, p < 0.001 on the second component. A post-hoc Tukey test revealed that cisgender men, (M = -2.7, SD = 1.05), are less willing to share their pronouns than cisgender women, (M = -2.21, SD = 1.35) trans men, (M = 3.49, SD = 2.68), and non-binary people, (M = 3.37, SD = 2.25). Non-binary people are also more willing to share their pronouns than transgender women, (M = 4.48, SD = 2.09). Additionally, results of Spearman correlations indicated a significant positive relationship between the second component, TCS scores, rs(382) = 0.16, p < 0.01, and TIBS scores, rs(382) = 0.35, p < 0.001.

PCA Components 1 & 3 by Gender. Percentage values along the axes represent % variation in the data explained by the component.

Figure 3.14: PCA Components 1 & 3 by Gender. Percentage values along the axes represent % variation in the data explained by the component.

A final one-way ANOVA demonstrated a significant effect of gender, F(6, 377) = 4.09, p < 0.001, TCS scores, F(377, 377) = NA, p < 0.001, and TIBS scores, NA, on the third component. Non-binary people, (M = 3.37, SD = 2.25), are significantly less concerned that sharing their pronouns will draw unwanted attention than cisgender men, (M = -2.7, SD = 1.05), cisgender women, (M = -2.21, SD = 1.35), transgender men (M = 3.49, SD = 2.68), and transgender women (M = 4.48, SD = 2.09). There were no significant effects between any other groups. Additionally, results of Spearman correlations indicated a significant positive relationship between the third component, TCS scores, rs(382) = 0.15, p < 0.01, and TIBS scores, rs(382) = 0.1, p = 0.05.

This may be due to the fact that this is the third component which only accounts for 8% of the total variation. Visualization of the third component shows that there is considerable variation within groups. This may be due to the orthogonal nature of PCA in which it attempts to find the line that explains the greatest amount of variation, given the constraints of the previous components. Given that the first component (cisnormativity) explains the greatest amount of variation, we see less variation in concern around sharing pronouns.