---
# System prepended metadata

title: Data collection - what are you asking when you ask about gender?
tags: [beyond-the-gender-binary, research-methods, requested, opinions]

---

# Data collection - what are you asking when you ask about gender? 
A question about gender is often included when collecting data in forms, surveys, questionnaire, identity documentation, and so on. Often, a question on gender is included by default, without any consideration (or explanation) for how disclosing a gender identity is relevant or how the information will be used. 

These questions can be difficult to answer for those who don't identity with the default options of man or woman. Even when a non-binary option is included, and a free-text box allows other options to be self-described, it is common practice to collapse the range of gender-identities disclosed into a subset of predefined categories for analysis.  

![Screenshot of table 4 from the Australian Bureau of Statistics 'Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables'(2019)](https://i.imgur.com/EcGNGXB.png)
*Table 4 from the [Australian Bureau of Statistics 'Standard for Sex, Gender, Variations of Sex Characteristics and Sexual Orientation Variables'(2019)](https://www.abs.gov.au/statistics/standards/standard-sex-gender-variations-sex-characteristics-and-sexual-orientation-variables/latest-release)*

While it can be important to collect information about gender in some situations, these are few. Even when relevant, questions about gender should be considered carefully.

The Workplace example is included below to illustrate the value of considering what information about gender is relevant (if any), and why eliciting additional context can help analysts (and those recommending actions based on that analysis) to account for the full range of gender identities disclosed.  

## Asking about Gender in the Workplace 
In the workplace, it may be appropriate to ask staff about their experience of gender when the data is intended to assess how inclusive a workplace feels, justify affirmative hiring practices, and so forth. There are several approaches to collecting this data depending on how it is going to be used.

#### Goal 1: counting genders
One approach is to simply count people based on a simplified list of pre-defined genders (how many options are included in this list depends on the intended use of that data). For example, counting how the ratio of women to men in a workplace may be required to asses [gender equality](https://www.wgea.gov.au/newsroom/gender-equality-in-australia-a-guide-to-gender-equality-in-2020). If so, then it may be enough to ask people an optional question with four non-mutually exclusive options: woman; man; non-binary; other - with a free-text option to provide details. During analysis those respondents who marked the *woman* option would then be compared those who marked *man*, and those who marked only *non-binary*, and any free-text beyond the two analytic categories, would be set aside. In comparison, using these predefined categories to count people across a wider range of gender-identities has limited value for assessing [diversity and inclusion practices](https://www.health.gov.au/about-us/work-with-us/what-we-offer/diversity-and-inclusion).  

#### Goal 2: examining a specific aspect of gendered experiences 
In addition to counting, you may want to analyse participant's responses to other questions in relation to the gender option selected. While tempting to use the default questions about gender identity, this can obscure the aspects of gendered experiences that are actually of interest. For instance, if you're interested in how people who present as feminine are treated at work, using the *women* option on the gender-identity question would be an imprecise proxy (at best). Not all women present as feminine, and lots of people who aren't women express feminine traits. Given this, an additional question about [gender *expression*](https://au.reachout.com/articles/the-difference-between-gender-sex-and-sexuality) might get slightly closer to this goal (this could also include four non-mutually exclusive options: feminine; masculine; androgynous; other - with a free-text option to provide details. Here, the 'feminine' respondents would then be compared to each of the other groups, and any free-text beyond those analytic categories would be ignored). 

#### Goal 3: exploring gender diversity
Another goal may be to improve [gender diversity and inclusion practices](https://www.health.gov.au/about-us/work-with-us/what-we-offer/diversity-and-inclusion). In this context, a free-text box is more appropriate than a list of predefined categories. This will take some participants more time to complete than a check-box selection, yet requires everyone to describe their gender-identity in their own terms - not just those outside the binary default. Likewise, analysing the data from this type of question will take more time but offers the potential for more nuanced analyses and the ability to recommend actions that take into account the range of gender experiences disclosed by participants.  

#### Goal 4: improving data quality
Regardless of whether including a select-an-option for gender-identity or not, consider allowing respondents to describe if/how they consider their experiences of gender to be relevant to the rest of the questions asked. Including these additional questions requires more time from participants as well as analysts. The benefit, in addition to increasing data quality, is that asking for this context can indicate a genuine interest in using the collected data for the stated goals (rather than simply checking-off the gender-diversity criteria for the appropriate number of minority genders employed).

For example, say you're asking about gender to help inform how hiring practices and workplace culture could be more inclusive and equitable in your workplace. In this situation you could provide participants with an opportunity to explicitly tell you about if/how gender impacts their experiences at work (in addition to asking about gender identity in a countable way if also required).

There are many ways to go about this. The following is one example of a set of question for the workplace that include some opening context, a question on gender-identity (select-an-option or free-text), and two questions asking about potential ways gender might be relevant in the workplace:

> The following optional questions are about your gender identity, if any, and about how perceptions of gender expression impact workplace experiences. For each, please include as much detail as you are comfortable sharing in this context.
>  1. What gender(s) do you identify with (if any)?
>  2. How has your gender identity (or lack thereof) been relevant to your workplace experiences? 
>  3. How have others' perceptions of your gender impacted your workplace experiences?


![Image of two flags, one the rainbow pride flag and the other the blue, pink, and white flag for transgender pride](https://i.imgur.com/t7vRtQm.jpg)


## Further Resources
- Scheuerman, Morgan Klaus, Aaron Jiang, Katta Spiel, and Jed R. Brubaker. 2021. ‘Revisiting Gendered Web Forms: An Evaluation of Gender Inputs with (Non-)Binary People’. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, 1–18. CHI ’21. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3411764.3445742.
- Spiel, Katta. 2021. ‘“Why Are They All Obsessed with Gender?”; (Non)Binary Navigations through Technological Infrastructures’. In Designing Interactive Systems Conference 2021, 478–94. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3461778.3462033.
- Spiel, Katta, Os Keyes, and Pınar Barlas. 2019. ‘Patching Gender: Non-Binary Utopias in HCI’. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, 1–11. CHI EA ’19. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3290607.3310425.



---
###### tags: `opinions` `research-methods` `beyond-the-gender-binary` `requested`

Date created: 2021  
Version: *unfinished draft* 1.0   
Attribution: created by [E. T. Smith](https://hackmd.io/@Teq/Bio) on unceded lands of the [Wurundjeri people](https://www.wurundjeri.com.au/).  
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