# data[].attributes.body
Ten teachers of fifth-grade students (ages 10-11) were recruited from a large, urban district in the United States with a high percentage of students from marginalized backgrounds.

Teachers were randomly assigned to conditions, with three English-only and five bilingual English & Spanish classes in each.

We tried to ensure similar proportions across both conditions according to students’ levels of economic challenges, multilinguality, disabilities, and reading levels, all of which we obtained from enrollment data.

# data[].attributes.body
We analyzed 140,000 test responses from a curriculum designed for 6-10th grade students. Most (80%) of the students in our sample were 11-16 years old, with the median age being 13.

Students could report one gender and one or more races alongside their responses. The demographics of students we analyzed test data from are reported in Table 1.

[click on the image to make it larger]

# data[].attributes.body
...a behavior that (intentionally or not) perpetuates dominant practices or perspectives in CER, which can exclude, harm, or misrepresent people from minoritized groups.

When responding to the following questions, reflect on this activity as well as your own experiences doing computing education research.

# data[].attributes.body
demographics of a certain type are provided for ALL participants. Ex: "We had 20 students (12 women, 7 men, 1 nonbinary person)"

# data[].attributes.body
demographics must be inferred for some participants. Can reinforce norms through assumptions. Ex: "We had 20 students (12 women)."

# data[].attributes.body
demographics of a certain type are provided for ALL participants. Ex: "We had 20 students (12 women, 7 men, 1 nonbinary person)"

# data[].attributes.body
demographics must be inferred for some participants. Can reinforce norms through assumptions. Ex: "We had 20 students (12 women)."

# data[].attributes.body
the paper doesn't report that information at all.

# data[].attributes.body
the paper doesn't report that type of demographic at all.

# data[].attributes.body
the condition assignment? not sure that's demographics

# data[].attributes.body
fifth grade student age

# data[].attributes.body
"marginalized backgrounds" (high %)

# data[].attributes.headline
"high percentage of marginalised backgrounds" - aggregation 

# data[].attributes.subject
"high percentage of marginalised backgrounds" - aggregation 

# data[].attributes.headline
What marginalized backgrounds are/aren't present

# data[].attributes.subject
What marginalized backgrounds are/aren't present

# data[].attributes.headline
Student racial demographics in this 'urban' district 

# data[].attributes.subject
Student racial demographics in this 'urban' district 

# data[].attributes.body
student gender, race, ethnicity, disabilities, SES, ...

# data[].attributes.body
Age - they give the range but do not FULLY describe the breakdown

# data[].attributes.body
all of the "similar proportions across conditions data", like SES, multilinguality, etc

# data[].attributes.body
They did not allow students to "check all that applies"

# data[].attributes.headline
Race (how would multiple selection be reported here?)

# data[].attributes.subject
Race (how would multiple selection be reported here?)

# data[].attributes.headline
Teachers are teaching students from marginalized backgrounds HOWEVER demographics of teachers are not provided. 

# data[].attributes.subject
Teachers are teaching students from marginalized backgrounds HOWEVER demographics of teachers are not provided. 

# data[].attributes.body
age

# data[].attributes.headline
I think all the demographics given are only partial. There are no actual numbers given? Just "there are..."

# data[].attributes.subject
I think all the demographics given are only partial. There are no actual numbers given? Just "there are..."

# data[].attributes.body
any multiselect of race is missing in the table 1 eg african american and asian

# data[].attributes.headline
"tried to ensure similar proportions across both conditions according to students’ levels of economic challenges, multilinguality, disabilities, and reading levels". but actually none of this is reported (so it´s either partially or no report)

# data[].attributes.subject
"tried to ensure similar proportions across both conditions according to students’ levels of economic challenges, multilinguality, disabilities, and reading levels". but actually none of this is reported (so it´s either partially or no report)

# data[].attributes.body
Compound ethnicities (A/B) may or may not be appropriate depending on purpose. "Asian may be far too broad.

# data[].attributes.headline
Could report the demographics of the schools if the district won't allow them to have individual student data.

# data[].attributes.subject
Could report the demographics of the schools if the district won't allow them to have individual student data.

# data[].attributes.headline
Could a cross reference to the meaning of all the conditions be provided for non US readers?

# data[].attributes.subject
Could a cross reference to the meaning of all the conditions be provided for non US readers?

# data[].attributes.headline
Teacher Race/ethnicity, disability, years teaching, years teaching CS, years in language that they are teaching, 

# data[].attributes.subject
Teacher Race/ethnicity, disability, years teaching, years teaching CS, years in language that they are teaching, 

# data[].attributes.body
Ability

# data[].attributes.body
Language fluency, disability, socio-economic status, major/program, geographic location

# data[].attributes.headline
Not sure. Is the study about teachers or students? It doesn't specify. Teachers were recruited/assigned, but then it talks about students' demographics. 

# data[].attributes.subject
Not sure. Is the study about teachers or students? It doesn't specify. Teachers were recruited/assigned, but then it talks about students' demographics. 

# data[].attributes.body
10 teachers noted in first paragraph, but only 8 noted in language descriptions

# data[].attributes.body
Facility in language of instruction

# data[].attributes.headline
Anything that doesn't fit into this US-centric categorization in the table

# data[].attributes.subject
Anything that doesn't fit into this US-centric categorization in the table

# data[].attributes.headline
That we have a consistent and agreed definition of Computing Education Research.

# data[].attributes.subject
That we have a consistent and agreed definition of Computing Education Research.

# data[].attributes.headline
At minimum report split between majority/minority %'s

# data[].attributes.subject
At minimum report split between majority/minority %'s

# data[].attributes.body
Though who falls in each of those groups is not always fully reported.

# data[].attributes.body
American exceptionalism

# data[].attributes.body
Arguably, full reporting is ALWAYS necessary to show the community WHO has been represented in research

# data[].attributes.headline
Assumptions of who belongs to aggregate term groups ("underrepresented")

# data[].attributes.subject
Assumptions of who belongs to aggregate term groups ("underrepresented")

# data[].attributes.headline
US heavily influences perceptions of which populations are minoritized

# data[].attributes.subject
US heavily influences perceptions of which populations are minoritized

# data[].attributes.headline
Assumption of English as a dominant language and that any other language is an exception to this

# data[].attributes.subject
Assumption of English as a dominant language and that any other language is an exception to this

# data[].attributes.headline
Have a set of definitions that are available for researchers to reference/ review. Could this be for publication sets? 

# data[].attributes.subject
Have a set of definitions that are available for researchers to reference/ review. Could this be for publication sets? 

# data[].attributes.headline
Page limits that make it hard to not lean on norms to not need to report every detail.

# data[].attributes.subject
Page limits that make it hard to not lean on norms to not need to report every detail.

# data[].attributes.headline
Have a “best accepted” way to ask these demographic questions on surveys

# data[].attributes.subject
Have a “best accepted” way to ask these demographic questions on surveys

# data[].attributes.body
create guidelines for collecting and reporting demographic data for CER research

# data[].attributes.headline
That researchers decide how participants are described and classified, instead of participants themselves

# data[].attributes.subject
That researchers decide how participants are described and classified, instead of participants themselves

# data[].attributes.body
Only looking at English language papers

# data[].attributes.attachment_link.readable_text
HCI Guidelines for Gender Equity and Inclusivity
Version 1.1 | Date modified: 5/21/2020
Authors: Morgan Klaus Scheuerman, Katta Spiel, Oliver L. Haimson, Foad Hamidi, Stacy M. Branham.
Contributors*: Os Keyes, Kate Ringland, Brianna Dym, Leo Stewart, Danielle Lottridge, Jes Feuston, Ashley Marie Walker, Michael Ann DeVito, Emily Q. Wang, Danaë Metaxa, Blake Hallinan, Julia Fernandez.
Reviewers / Editors✝: Alex Ahmed, Os Keyes, Danielle Lottridge.
This is a living document. We encourage feedback, suggestions, conversations, and criticisms. We are also looking for authors/collaborators in writing two new sections: For Educators and For Reviewers. Feel free to email us at genderguidelines@gmail.com or email me directly.

You can use the Table of Contents below to navigate to specific sections, or the navigation menu on the right to navigate to major sections.

*Contributors took part in an unofficial workshop organized by authors at the CSCW 2018 conference.
✝Reviewers and editors provided feedback that helped shape this document.

This document has been collectively generated by members of the SIGCHI community whose research addresses gender representation in technology and the activist goal of gender equality. We outline a pragmatic approach to fostering a research community that is inclusive of people with a variety of genders. We are particularly focused on creating space in our research methods, publications, professional gatherings, and pedagogy for people who do not identify with the binary gender designations--men and women--that are pervasive in Western cultures, and for people whose genders change and/or are fluid over time. In this document, we offer guidelines for Writers, for Researchers, and for Organizers.

We humbly recognize that gender is culturally, materially, and temporally situated, and that it is experienced differently by those with intersecting identities. Rather than a set of universal prescriptions, this document is intended to provide inroads to approaching gender in an inclusive way. This document is situated within a specific present, geographically and culturally- influenced (most of the authors work and/or live in the United States). Hence, it does not provide a set of absolute and essential rules for inclusivity, but rather offers opportunities for reflecting on gender in different contexts.

The primary purpose of this document is to encourage people to continue doing this work by providing helpful tools to refer back to. We acknowledge that mistakes happen (and the authors of this document also make mistakes), sentiments change, and cultural concepts and social norms evolve. We also acknowledge that the authors had differing views on certain subjects and concepts throughout the creation of this document, showcasing that gender is a difficult and highly personal subject that needs to be handled with care.

Gender plays a crucial role in all societies, scripting everyday social interactions and our personal narrative identities. The concept of gender is being increasingly discussed as a complex and fluid facet of human identity in numerous fields, ranging from the social sciences-such as feminist and queer studies [7,18,29]-to the medical field [23,24,30], and in computing and HCI (Human-Computer Interaction)(e.g. [1,13,35]). Alongside increased public awareness about transgender rights movement across the globe (e.g. [3,42-44]), the academic conversation around gender increasingly involves transgender identity.

Human-computer interaction researchers have interrogated the experiences of gender in technology design and use (e.g. [39]), as well as feminist orientations towards equitable research and interaction design (e.g. [15]). As a field, through our choice of research topics (e.g. [36]) and professional activities (e.g. SIGCHI's Internationalisation, Diversity and Inclusion events [45]), we are increasingly signaling our collective value of developing more inclusive, critical, and intersectional frameworks and approaches towards gender and other identities.

Yet, this type of cultural change takes concerted leadership efforts to affect "deep" transformation. Along the way, there have been and will continue to be situations in which our community caused harm and subsequently has been called out to reflect and do better (e.g. [11,46]). This document was born of one such reflective effort: a rejected workshop proposal turned informal "lunchshop" hosted during CSCW 2018 by the authors [31]. We hope this document will take a small but practical step-in the tradition of Cavendar, Trewin and Hanson's "Accessible Writing Guide" [10]-in support of a more gender inclusive HCI, that intentionally addresses inclusion for transgender individuals.

While recent movements have led to increased formal recognition for some trans people in modern North America and Europe, more expansive views of gender are not new; there are myriad cultural contexts, both historical and current, where gender is not seen as a binary, biologically-rooted phenomenon (e.g. [40]). Racism and colonialism have often led to their suppression and the associated entrenchment of binary gender norms [26].

The authors, contributors, and editors of this document recognize that we do not mirror the diversity of people across a range of gender identities. Further, we are not the originators of critical gender discourses. Thus, we recognize that our perspectives are incomplete.

We highly encourage your feedback and recommendations for how to continuously improve this document. Please send all comments, questions, and recommendations to genderguidelines@gmail.com.

Language is a powerful tool-for inclusion and exclusion. The words and phrases we choose to describe certain individuals or groups can contribute to increased marginalization of already underrepresented groups. Our language choices may reflect biases and may reinforce hegemonic structures of power that are already in place. Adopting inclusive language practices when discussing identity characteristics like gender ensures equitable representation for people of all genders.

As has been noted by other scholars [2,34,50], the way that we talk and write about gender is encased in powerful mechanisms for changing perceptions, attitudes, and actions. We do not expect researchers to be able to transition to inclusive participant sampling the day after these guidelines are published. But, at a minimum, they should be able to write in a way that indicates (if, for example, they have only included people of binary genders) that they are aware of possible limitations in their sampling and/or gaps in the generalizability of their work.

The following section of this guideline document outlines some ways of respectfully talking and writing about gender, and highlights some common terms surrounding transgender identity. We also highlight some issues about writing and discussing gender appropriately and equitably in current ACM guidelines and ways to best tackle these constraints.

When talking or writing about gender, there are many important steps one can take to make their writing more gender inclusive. Primarily, these guidelines are meant to help authors write about gender as a complex construct rather than a simple binary category, and to avoid positioning some genders as more "normal" than other genders.

The following guidelines summarize some general points we believe can be used to more accurately write about gender:

✪ Guideline A-4: Use gender meaningfully in your writing. Define what you mean by gender in your writing or research question. Tell the reader why it is important or insightful to these contexts. Are you discussing gender as a concept, gendered experiences, or societal notions of gender?

✪ Guideline A-5: Do not refer to cisgender people as "normal." This positions transgender and/or non-binary individuals as unhealthy or abnormal. Similarly, quotes around "transgender" and "non-binary" are to be avoided, as they insinuate they are not real experiences.

✪ Guideline A-6: Do not position cisgender individuals as the default in comparison to trans individuals. For example, using "women and trans women" implies that cisgender women are actually women, but transgender women are not. This invalidates a transgender person's identity. Instead, you can just refer to them as "women." If it is necessary to distinguish between cisgender and transgender women, state "cisgender and transgender women."

✪ Guideline A-7: Avoid binary language. This includes things like "both sexes" or "opposite genders." This language implies that genders exist on an oppositional binary spectrum, although gender is much more complex.

✪ Guideline A-9: Be transparent about your work's limitations. Address gender diversity in your limitations and how it may have impacted your findings.

For different individuals, the following terms may overlap, be used interchangeably, or be consciously avoided or disliked. There is nuance in writing about individuals with diverse gender identities that cannot be encapsulated discretely or concretely in a "How To" guide. We outline some common terms and definitions for those terms to help writers and researchers formulate a starting point.

Transgender (also shortened to trans) refers to an individual whose gender differs from the one which they were assigned at birth. Transgender individuals may use many terms to more granularly define their genders.

Transgender women may refer to themselves as one or more of the following:

AMAB (assigned male at birth)

MTF / M2F (male to female)

Trans female

Trans woman

Trans feminine (trans fem or trans femme)

Female or woman (without any reference to their previously-assigned gender)

Transgender men may refer to themselves as one or more of the following:

AFAB (assigned female at birth)

FTM / F2M (female to male)

Trans male

Trans man

Trans masculine (trans masc)

Male or man (without any reference to their previously-assigned gender)

Furthermore, some of the above terms are not necessarily tied to binary gender; non-binary individuals may refer to themselves as trans fem, trans masc, or other traditionally "feminine" or "masculine" terms.

Non-binary identities do not align with binary conceptions of male and female. Non-binary individuals also do not identify with the gender they are assigned at birth, thus are often considered to fall under the larger "trans umbrella." However, some non-binary individuals do not identify as trans. Non-binary individuals may refer to themselves as one or more of the following:

"Enby"

Trans masc or trans fem

Non-binary butch / non-binary femme

Bigender (identifying with two genders / gender expressions)

Androgyne

Genderless

Gender Neutral

Neutrois

Agender (not subscribing to any gender)

Genderfluid (moving between different genders)

Genderqueer (actively subverting a binary notion of gender)

Non-binary people might additionally or separately identify as any number of different genders.
Some argue that writing "transgender and/or non-binary" positions non-binary individuals outside of the transgender community, which actively erases the identity and belonging of non-binary individuals, and suggest referring to "binary and non-binary trans people," if the difference is relevant. Others feel that this may inaccurately place a trans identity label on some non-binary people who themselves would not claim such an identity, thus going against Guideline A-1. We encourage researchers to carefully consider these distinctions and classifications in research and writing. In this piece, we have decided to use "transgender and/or non-binary" but acknowledge there are differing opinions and experiences on this matter.

The above genders contrast with cisgender, which refers to an individual whose gender reflects the one they were assigned at birth [4].

Intersex people have genetic, chromosomal, anatomic, and hormonal variations that misalign with binary conceptions of male or female characteristics. Often, intersex people are subjected to genital mutilation at an early age to make them fit to a potential binary gender assignment [12].

Intersex individuals may identify as either cisgender or transgender and/or non-binary, dependent upon their alignment with the gender they were assigned through medical or social intervention, if any.

Gender non-conformity describes different actions, mannerisms, presentations, and/or genders that do not necessarily conform to a specific social set of rules for the binary of man or woman. Someone may describe themselves as gender non-conforming, but it is not necessarily used as an identifier. Anyone of any gender identity may be gender non-conforming. A cisgender person may identify as gender non-conforming because of their presentation, while a non-binary person may identify as gender non-conforming because their gender does not align within the binary. Gender non-conforming is a broad and fluid term that can be used by people to describe many aspects of their identity.

Gender non-conformity describes different actions, mannerisms, presentations, and/or genders that do not necessarily conform to a specific social set of rules for the binary of man or woman. Someone may describe themselves as gender non-conforming, but it is not necessarily used as an identifier. Anyone of any gender identity may be gender non-conforming. A cisgender person may identify as gender non-conforming because of their presentation, while a non-binary person may identify as gender non-conforming because their gender does not align within the binary. Gender non-conforming is a broad and fluid term that can be used by people to describe many aspects of their identity.

There are numerous words that are viewed as inappropriate and offensive ways to refer to transgender individuals, many of which are outdated terms once utilized by medical professionals (see the section on Medicalized and Stigmatized Terms for specifically medical terms to avoid). In the following guidelines, we define some of these terms and why they should be avoided unless directly quoted from participants:

✪ Guideline C-1: Transgendered is considered an incorrect and offensive way of referring to a transgender individual, due to its insinuation that being transgender is something that happens to someone. It centers an individual's gender transition (and assumes all trans individuals choose transition), rather than an individual's identity.

✪ Guideline C-2: Transgenders (or "a transgender") is similarly incorrect and offensive. Choosing to use transgender as a noun, rather than an adjective, removes "people" or "individuals," thus dehumanizing transgender people. It would be much like referring to gay or queer individuals as "the gays" or "the queers," which is now also viewed as inappropriate.

✪ Guideline C-3: Transsexual is a term that was once more popularly used in psychological and medical literature to describe people who have physically transitioned. While some individuals may still identify as transsexual, is not considered an umbrella term in the way that transgender is, and should thus be avoided to describe transgender people broadly. Many transgender individuals find this term offensive due to its centering of surgical procedures and binary gender expectations.

✪ Guideline C-4: Transwoman or transman are also terms to broadly avoid save for instances where an individual self identifies. Transgender is viewed as an adjective to describe a person. For example, conflating trans and woman to transwoman insinuates a transgender woman is a separate and new gender. This is seen as insinuating a transgender woman is not actually a woman. Instead, separate "trans" (the adjective) from the individual (the noun). For example: "trans woman," "trans men," "trans people."

✪ Guideline C-5: Transvestite refers to a person who is not necessarily transgender, but rather a trans or cis person who "cross-dresses." Both cross-dresser and transvestite are terms that should be used only if an individual uses them to describe themselves.

The term "preferred pronouns" is being phased out of trans terminology due to the inference that using a person's correct pronouns is a "preference," rather than a matter of respect.

Some terms are considered to be heavily stigmatizing to transgender individuals, particularly terms that have ties to historical medicalization and dehumanization of transgender individuals [28]. It is best to avoid using these terms unless quoted directly from participants. We provide two examples of medicalized and stigmatized terms in the following guidelines:

✪ Guideline C-7: Do not refer to the state of being trans astransgenderism. The ism postfix carries connotations that being transgender is a choice and that trans people can simply avoid being trans. It can also be read as a medicalized or prescriptive term for being trans.

✪ Guideline C-8: Gender Identity Disorder is a now-defunct term for gender dysphoria, the psychological term for the experience of gendered dissonance between one's physical form and how one expects it to be. In the event that you are referring specifically to dysphoria, "gender dysphoria" alone is an acceptable term, but note that being dysphoric is not the same as being trans, and avoid equating the two. Regardless, one should avoid "Gender Identity Disorder," since the term "disorder" carries substantial stigma.

Although many people who identify with the term "masculine" may also identify as men, not all people who are masculine are necessarily male. Masculine people may be non-binary or women as well. Similarly, not everyone who identifies with the term "feminine" may be a woman. Feminine people may be non-binary or men.

Like masculine and feminine, pronouns may not always align with gender in societally expected ways. For example, a trans woman might use they/them, rather than she/her.

There are many different pronouns, including neopronouns. Neopronouns are non-binary pronouns that replace the use of the singular "they," such as ey/em or xe/xir [49]. The non-binary alternative to the gendered honorifics (Mr., Ms., Mrs.,) is Mx.

Discussing the ways people identify can be tricky. While it is appropriate to ask for a participants' gender, we recommend avoiding statements that may position a trans person's gender as inauthentic. For example, "Celine (a trans woman) identifies as a woman"or "Celine is female-identified" may insinuate that Celine is not actually a woman, but simply identifies as one.

People are a certain gender, which is part of their identity. Sometimes, using a term like "gender identity" implies that trans people's genders are less real than cisgender people's genders.

The language surrounding gender and sex is extremely complex, nuanced, and often political. While some view gender and sex as separate ideas (in which gender is internal and sex is biological), many trans people believe that differentiating between the two can be seen as transphobic and genital essentialist. Many trans people do not view their biological sex as separate from their gender identity, regardless of first and secondary sex characteristics. This can also be regarded as a form of intersex erasure.

Another crucial aspect of discussing and writing about gender is the way that gender intersects with other social identities. Racial, ethnic, and cultural identity is often intricately intertwined with gender and the way gender is experienced and discussed. Thus, is it key to address concepts of gender from an intersectional lens to acknowledge the overlapping ways that gender, race, skin color, ethnicity, ability, class, and other marginalizations impact one another [8].

It is also important to consider the ways that gendered terms and concepts may vary by race, skin color, ethnicity, and culture. For example, some non-binary trans people prefer to use terms such as Latine or Latinx, over gendered terms like Latina or Latino. Other cultures also do not necessarily share the same binary views on gender as the dominant Western culture featured in much HCI research [51]. It is always best to familiarize oneself with the gendered culture of a study site to best understand these differences.

Misgendering refers to the (intentional or unintentional) misidentification of a person's gender. A person may misgender a trans person by using the wrong pronouns or the wrong gender for them. For example, a trans masculine person may use he/him but be called she/her. Or a non-binary person may be referred to as a woman.

Although this may seem like a small issue, it is not; because of the ubiquity of the experience, and the way that misgendering invalidates and delegitimizes trans peoples' existences, it can have substantial effects. Research has shown that misgendering decreases self-worth, increases felt stigma and reduces overall wellbeing [25,33].

Some transgender individuals may refer to the concept of "passing": being read as a specific gender by other people (this concept stems from histories of "racial passing" [16]). Some individuals may discuss passing as their correct gender. For example, a transgender woman may discuss passing as a cisgender woman in the eyes of others. Others may talk about passing as the incorrect gender, often to discuss the experiences they have being perceived as that gender. For example, a transgender woman may discuss passing as a cisgender man in her everyday life, and her thoughts and feelings about that experience. This highlights the difference between gender (one's actual gender identity) and being gendered (the way one's gender is perceived).

"Passing Privilege" is a term used to describe the privilege and safety binary trans individuals are awarded when they pass as cisgender (and their actual gender, as in, they are not misgendered). Passing is a disputed concept within trans circles due to the pressure and expectation for trans individuals to fit into binary gender roles [38]. While coveted by some binary trans individuals, passing is often inaccessible to many trans people, particularly non-binary individuals living within binary societies. Meaning, non-binary trans people often cannot "pass" as their true non-binary gender.

Hormone Replacement Therapy is a medical process which some, but not all, transgender and/or non-binary individuals choose to undergo. This process involves the administration of hormonal medications to induce specific secondary sexual characteristics. It is often shortened to HRT.

Some binary and non-binary transgender individuals may choose to undergo gender affirmation surgery, a medical process in which an individual undergoes surgery to align their body more with their gender identity. Some individuals may still use the older term "sex reassignment surgery," but it is less accepted among the spectrum of trans individuals.

The psychological term for the experience of gendered dissonance between one's physical form and how one expects it to be. However, one does not have to have gender dysphoria to be trans.

In contrast to Gender Dysphoria, Gender Euphoria describes the affirmative and often euphoric emotions trans and/or non-binary people experience when adopting markers of their gender. For example, the affirmative feeling when a trans masc person might feel when getting their haircut. The feeling can also occur when others recognize a person's correct gender or use the correct pronouns unprompted.

The concept of transition or gender transition may be discussed in various ways. Some binary and non-binary trans individuals may choose to undergo medical transition, which may involve HRT and/or gender affirmation surgery. This may go hand-in-hand with social transition, transitioning gender in one's social life by adopting different pronouns and/or a different name, and so on. Furthermore, some individuals may have access to legal transition, the process of changing one's gender on legal documentation, such as IDs and birth certificates (this process is often inaccessible to many due to financial and lawful constraints).

Social transition does not necessarily require medical transition. Some binary and non-binary trans individuals choose to never undergo medical transitional procedures, or may opt for only one or a few options.

Some people adopt the term trans feminine if they identify with femininity. However, a trans feminine person may not identify with the label "woman."

Some people adopt the term trans masculine if they identify with masculinity. However, a trans masculine person may not identify with the label "man."

Transphobia describes discrimination and prejudice against transgender people, and may include negative feelings such as dislike, discomfort, disgust, and anger. Transphobia may be internalized by transgender people, leading to expectations of transnormativity-specific, acceptable, and normalized behaviors on the part of trans people. Transphobia may be targeted specifically at certain groups, including specific discrimination against non-binary trans individuals. Transmisogyny describes the specific discrimination and prejudice experienced by transgender women and trans feminine individuals [37]. Transmisogynoir, (built off Dr. Moya Bailey's concept of misogynoir [5]) describes the intersecting discrimination and prejudice experienced by transgender women of color [41].

For a helpful glossary of LGBTQIA* terms, see [27].

Different types of study contexts require asking about and reporting participants' genders in different ways. Several of the factors that influence how to request and report gender in HCI research are research methods, research setting, and research focus.

HCI researchers use many different types of methods, and each of them require different techniques for respectfully asking participants about gender and then reporting gender in the research write-up. In the following sections, we provide guidelines for requesting gender from participants based on different research methods.

In interviews and ethnographic studies, while researchers have close contact with participants and it may seem simple to ask about gender, asking about demographics (including gender) may feel invasive and may break the rapport that the interviewer or ethnographer has built up with participants. If that is the case, consider this guideline.

In social media data analysis, researchers may have no contact with research participants at all, and may instead rely on inferring gender by making assumptions based on people's names or pictures, or even algorithmically. Research has shown that these practices can be particularly harmful for trans and/or non-binary people [14,22].

How to respectfully report gender on surveys has been a tricky question for many HCI researchers [17]. While the specifics of how exactly to do this for every case is beyond the scope of these guidelines, we direct readers to Spiel et al.'s Interactions article which detail best practices in gender inclusive survey design and Stevens' Open Demographics resource. In brief, here are a few guidelines:

This section provides guidance on how to respectfully request gender from research participants also varies depending on the research setting.

In 1:1 settings with researchers and participants (e.g., interviews), it is possible to respectfully ask the participant their gender and what pronouns they use (see Research Methods above for strategies). It can be helpful to build rapport with participants before asking for this information.

In group settings, such as participatory design sessions and focus groups, give people the opportunity to share this information at the beginning of the session and make sure to use and respect people's names and pronouns. At the same time, allow people the option of sharing gender information privately with the researchers rather than publicly with the group. Gender is usually not considered sensitive information, but it may be for those who are in transition.

How to request gender information and report about gender does vary some based on the research project's focus. We place these into four main categories: 1) research projects about gender broadly (e.g., "differences in user behaviors between genders"); 2) Research projects about trans and/or non-binary populations (e.g., "binary and non-binary trans experiences using a system"); 3) Research that requires specific personal health data dependent on "biological" sex characteristics; and 4) Research not focused on gender.

For research projects looking at gender differences, it is imperative to ask participants about gender, using the following guidelines:

For research projects about transgender and/or non-binary populations, it makes sense to ask and report about gender in much more complex ways than for other studies. For studies with a small sample size, allow people to self-identify however they choose, and report genders this way (just as you would for any other study). We recommend using a two-step or multidimensional gender question for trans-focused studies with large sample sizes. A two-step or multidimensional procedure asks the participant their assigned sex at birth, followed by their current gender and/or lived gender. For the latter, use Guideline G-11:

In studies that require specific personal health data dependent on "biological" sex characteristics (prominent in health and medicine fields but relatively rare in HCI studies), it may be necessary to distinguish between cisgender and transgender participants. In these cases, a well-designed two-step survey procedure can enable researchers to identify between cisgender, binary trans, and non-binary trans participants. However, it is important to note that many trans bodies change over time, and a gender question on a survey will not tell you which body parts and hormone levels each person has. If you need that data, it is best to ask those questions directly.

For research not focused on gender, researchers should still carefully evaluate whether and how they should ask participants about gender. We recommend still requesting and reporting participants' genders even if a study is not specifically focused on gender. This allows gender diversity to remain visible and enables readers to evaluate the gender diversity of the study sample. For instance, a study's participants may be 80% men, which should be reported, so that readers and reviewers can assess the limitations of a given study appropriately and note the lack of gender diversity represented.

Gender is complex, personal, and changing. Just because a participant in your study is a certain gender now, does not mean that they will still be that gender during the next phase of your study, or when your paper is published. Thus, consider the following guideline when writing your results:

Disclosure is another important matter when considering how to report trans and non-binary participants' genders. Because you may have relatively few trans participants in your study, even if you give these participants pseudonyms, you risk "outing" participants by reporting their gender along with other characteristics. For example, let's say that in a qualitative study you report that one of your participants is "Sid (pseudonym), a non-binary 27 year old baker from Columbia, Missouri." There may only be one 27 year old non-binary baker in Columbia, so it becomes clear to some readers who your participant is, which compromises their confidentiality as a research participant. Additionally, if Sid has not disclosed their non-binary identity to certain people who end up reading your research paper, this puts them in a precarious and possibly dangerous position.

Another part of gender's complexity is its multiplicity. Some people identify as multiple gender categories (e.g., a non-binary trans woman), or people's identity and gender presentation may differ in different settings. Attempting to contain each person into only one category reduces people's complex experiences, which does not benefit research. The following two guidelines address this:

Finally, gender's complexity beyond the binary is important to consider when visualizing research results:

Note: Many of these guidelines have similarities with other demographic categories, such as race/ethnicity [32].

It is important to consider gender inclusivity at each step of the research process. In this section, we offer guidelines on gender-inclusive practices when initiating HCI research projects and considering gender's role in a project's theoretical underpinnings.

While these guidelines are most relevant to the first two categories of research projects described in the Research Focus section (i.e., research projects about gender broadly and research projects about binary and/or non-binary trans populations), they can also inform interdisciplinary research that is not specifically focused on gender but considers human experiences more broadly in relation to technology.

Thinking about gender equity should begin early on in the research process when research questions are formed, rather than as afterthoughts. It is important for researchers to be aware of the large and dynamic body of research on gender and its different aspects and to ensure that their research both draws on current and relevant understandings and also contributes to this larger discourse by addressing meaningful and relevant questions. One approach is to consult with other researchers and practitioners who work in relevant areas. Additionally, discussing research questions with representative members of a participant community can provide insights into what elements are relevant from their perspectives. An important consideration when consulting others about research questions is to strive to get feedback from people with perspectives other than one's own.

As described in the For Writers and Researchers chapter of this document, gender is multifaceted and dynamic and researchers should not assume a common, simplified understanding when discussing it. Current ways of thinking about gender are the result of many years of gender research and theory across different disciplines. Researchers should be transparent about the theoretical underpinnings of key concepts in relation to gender that they draw on in their research.

Research has shown that many engineering and design projects have historically ignored nuanced theories of gender, leading to harmful outcomes [14,22]. Thus, it is important for HCI researchers whose topic focuses on gender to situate their work in the wider ongoing research discourse beyond technical fields, including fields like Gender Studies, Communication, Design, Media Studies, Psychology, Sociology, Health, Medicine, Education, etc. Currently, efforts are underway to develop resources, such as the Digital Trans Reading List and the Bibliography of Transgender Media Studies.

When consulting previous literature, researchers should be aware that many studies have historically relied on erroneous, outdated or problematic theoretical underpinnings with respect to gender. Relying on these previous work can impair current projects and introduce bias. Given this possibility, researchers should investigate the sometimes implicit, definitions and conceptualizations of gender present in previous work. They should question why these conceptualizations are used, why they are problematic, and how can they be addressed in their own research.

The following chapter addresses how to approach gender inclusively when organizing professional and academic events, gatherings, and conferences.

Codes of conduct are meant to create safer spaces, particularly for marginalized populations attending a conference or professional event. The ACM Policy Against Harassment at ACM Activities as well as the guideline regarding Reporting Unacceptable Behavior at ACM Activities provide basic guidance, but are often not directly referenced on event pages or buried in other documents. Hence, awareness of how to appropriately report harassment tends to be nonexistent. As harassment is mostly targeted at marginalized members of our community, they additionally might fear retribution and, if new to an event, might also have difficulty trusting in organizers that appropriate action will be taken.

Not all authors and volunteers at conferences and other events who create the technical programme share the same understanding of gender, sex, disability, race and further identity structures. For example, technology regarding menstruation is relevant not only to cis women, but also to trans and/or non-binary trans people.

SIGCHI already provides several guidelines for making an event venue gender inclusive. One effort is to provide an all-gender restroom. Below are some guidelines for doing so inclusively.

Once the event ends, if there is a survey for attendees, it should allow for detailed feedback on their accessibility for different marginalized groups.

These guidelines will need to be updated frequently as definitions, theories, identities, and language related to gender change over time. We make the commitment to update these guidelines, or to delegate the updating task to qualified SIGCHI gender researchers, every several years for the foreseeable future.

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May 21, 2020 - added a definition for Gender Dysphoria under the Glossary for Useful Terms section.

May 22, 2019 - removed reference to D'ignazio's piece after its problematic history was pointed out.

May 24, 2019 - changed the description of "intersex people" to "Intersex people have genetic, chromosomal, anatomic and hormonal variations that misalign with binary conceptions of male or female characteristics."

July 28, 2019 - replaced term "gender identity" with "gender" throughout document and added section "Gender Identity"

# data[].attributes.attachment_link.description
Version 1.1 | Date modified: 5/21/2020 Authors: Morgan Klaus Scheuerman, Katta Spiel, Oliver L. Haimson, Foad Hamidi, Stacy M. Branham. Contributors *: Os Keyes, Kate Ringland, Brianna Dym, Leo Stewart, Danielle Lottridge, Jes Feuston, Ashley Marie Walker, Michael Ann DeVito, Emily Q. Wang, Danaë Metaxa, Blake Hallinan, Julia Fernandez.

# data[].attributes.headline
Assumption that post-secondary students are being studied

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Assumption that post-secondary students are being studied

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Many papers discuss participants in abstract without clarifying which student group is included. K-12 papers normally add this to abstract, while those studying post-secondary students rarely do (and sometimes not even in the paper itself).

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Expectations: There are universal issues, but there are also national and regional ones that are often neglected

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Expectations: There are universal issues, but there are also national and regional ones that are often neglected

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Gender much more often studied than other categories

# data[].attributes.subject
Gender much more often studied than other categories

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Particularly in comparison to race/ethnicity, disability

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Professional development resources for researchers on this. These could be freely available and be incorporated as requirements in Masters/ PhD and even undergraduate research modules

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Professional development resources for researchers on this. These could be freely available and be incorporated as requirements in Masters/ PhD and even undergraduate research modules

# data[].attributes.headline
This may be sensitive data for participants to disclose - we need to be mindful of this as researchers

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This may be sensitive data for participants to disclose - we need to be mindful of this as researchers

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Assumptions of ability (vision, hearing, motor-physical control)

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Assumptions of ability (vision, hearing, motor-physical control)

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Have an explicit set of criteria that researchers should strive to meet for reporting - reviewers should confirm that these demographics are given

# data[].attributes.headline
Look outside of US-centric ways to talk about data

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Look outside of US-centric ways to talk about data

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Sometimes if you don't plan to research any differences, it might be considered over-questioning if you need to ask all types of demographics from participants... Is it always necessary to ask for ALL demographics and which are considered to be most important?

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A community in which this kind of issue can be freely discussed. Perhaps have critical friends who could review papers for this type of issue?

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A community in which this kind of issue can be freely discussed. Perhaps have critical friends who could review papers for this type of issue?

# data[].attributes.headline
Is it possible to even get this "right?"

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Is it possible to even get this "right?"

# data[].attributes.body
There are different reasons for reporting demographics and why that information is salient. For example, is race important because of the cultural background that person is likely from? OR is it salient because of how that person is treated? OR is it salient because of how that person perceives themselves?

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Evolvable journal and conference publication standards around demographic reporting

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Evolvable journal and conference publication standards around demographic reporting

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Most papers in the U.S. don't specify the country or even the location of the students.

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Ideally we would allow each participant to fully describe themselves and whether or not each piece of the description can be published. However, this makes comparisons across studies nearly impossible, not to mention that demographics now becomes an appendix to every paper rather than just a section.

# data[].attributes.subject
Ideally we would allow each participant to fully describe themselves and whether or not each piece of the description can be published. However, this makes comparisons across studies nearly impossible, not to mention that demographics now becomes an appendix to every paper rather than just a section.

# data[].attributes.body
It feels as if this is a moving target -- for example some aggregate terms are acceptable right now "global south" but other ones are now taboo

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As a reader, I find many papers include demographic data but don't explain how the demographics influence the work/interpretation.

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Often there is a US centric view of Demographics, but the sociocultural context varies so much from place to place and contex to context. 

# data[].attributes.subject
Often there is a US centric view of Demographics, but the sociocultural context varies so much from place to place and contex to context. 