Gender vs Sex – How Gender Identity affects Data Collection

Since the first Pride march in June of 1970, Pride Month has been a time for affirming, acknowledging, and learning about the LGBTQIA+ community and their struggles. 

As a company and a family, Slingshot believes in equality for all, regardless of gender and sexual orientation. 

This Pride Month, we’d like to discuss how gender identity impacts data collection and the best practices on how to be mindful of the queer community during interviews. 

First, it’s important to differentiate between Sex and Gender. The terms and their definitions are used interchangeably, but have completely different connotations.

A person’s sex refers to “the biological difference between males and females, such as genitalia and genetic differences.” These differences can be both anatomical and physiological. Sex is usually considered as the binary biological gender at birth; your sex is either male or female. 

It’s important to keep in mind that while the societal norm is a binary sex denotation at birth, a person can be born with an anatomy that doesn’t fit the typical definitions of female or male. Known as Intersex, Children can be born with a mix of male and female genitalia; males having an extra X chromosome, and females having a Y chromosome. Intersex individuals account for around 1 in 1,500 births.

While sex is (usually) defined as either male or female, gender is more difficult to pinpoint. Gender refers to the roles a person plays in society, and their concept of themselves. Since a person can land anywhere between the two binary genders in terms of norms and self expression, gender should be seen as a spectrum rather than a finite decision. 

The aspect of someone’s gender that focuses on an individual’s view of themselves is known as their gender identity. Gender identity can only be chosen by an individual person; no one can assign someone a gender identity. Your personality and its connection to being male, female, a combination of both, or neither, is what defines your identity.

We’ve discussed the differences between gender and sex, but what if they don’t match up? A person that has a gender identity that does not match the sex that they were assigned at birth is a Transgender person. While everyone’s journey is personal and unique, someone who is Transgender usually undergoes some form of transitioning: they begin to live according to their gender identity. Some update their name and pronouns, some change their appearance, and others undergo medical procedures to have their body better reflect their gender identity. No matter a person’s outward appearance or level of being ‘out,’ any person can be Transgender. 

We’ve mentioned how the two genders of sex are known as binary: there are two options. However, since gender is a spectrum, there are people whose gender identity doesn’t fall under either binary gender;  Nonbinary refers to anyone whose gender identity is not exclusively male or female. This umbrella term includes all genders that are not female or male, including (but not limited to) agender, gender fluid, and genderqueer. It’s important to note that not all nonbinary people identify as transgender, and not all transgender people identify as nonbinary.

Now that we’ve touched on sex, gender, and identity, we should talk about how these factors can affect data collection. When it comes to gathering research, specifically from interviews, gender is very important; One of the major demographics used to slice data is by gender. Why is correctly identifying gender important? 

The LGBTQIA+ community is a minority group, and because of this they face discrimination and disparities. Affected areas include, but are not limited to, health care, employment, legal rights, housing, and access to services. When collecting data, it’s important to know what a person has gone through to understand their reasoning and responses. Have empathy, and try to learn about their experience. 

When collecting data, you want access to as wide a variety of people as possible. Since each person has their own experiences, accurate reporting only comes when you have a diversified group of interviewees. Gender identity is an important aspect of that diversity. Collecting data on gender helps diversify the individual data as well as the data as a whole. 

When trying to find solutions to a problem via interviews, understanding the reasoning for answers is just as important (if not more) than the answers themselves. By learning about someone’s gender identity, that can help lead to more understanding. 

An example would be figuring out why someone shops in a specific section of a clothing store. In the women’s section, you would see binary females, but what about people who don’t fall under the gender norm? Father’s might be shopping for their family. A nonbinary person could feel more comfortable in women’s clothing. Having an understanding of all factors can help you decipher the reasoning for answers. 

Everyone is different; individualism is a part of our society. Gender identity is a huge aspect of how we see ourselves. A person’s opinions and daily experience is more based on how they identify versus how they appear. You might accidentally be skewing your demographic data if you focus on sex rather than gender.

How do you go about ensuring you get accurate data, while keeping your interviewees safe and comfortable? With the knowledge we’ve gained on gender, let’s apply it to some data collection practices.

If you think back to a few minutes ago, we talked about the difference between sex and gender. Since both of these data points are important, it makes sense to collect both of them. In previous research, you might have asked directly someone’s gender, and they responded with a binary answer (male/female). It’s a good idea to ask about gender identity, and possibly even sex if you need a differentiation. 

Your first question could ask which binary sex they were at birth, followed by a gender identity question. Focus more on how the person describes themselves rather than how society sees them. ‘How do you describe yourself?’ is better than ‘what is your gender?’ This second question should have lots of options for answers, but not an overwhelming amount. Include an ‘other’ option to allow for personalization. 

Did you catch it in the previous question? Focus more on how the person describes themselves rather than how society sees them. There are many people who identity as a gender different than their birth sex, but cannot openly express themselves. No matter the reason why, it’s important to protect the identity of those who are not comfortable with being outed as a member of the LGBTQ+ community. 

There are several ways to ensure a respondent is both comfortable and safe when submitting data on gender identity. One way is to keep all survey data anonymous, either by assigning numbers or creating false names. This way, every piece of data you collect can’t be tied to names or individual records.

Another option you should consider is allowing users to skip any question they don’t feel comfortable answering. This could be done by skipping the question all together, or adding the ‘prefer not to say’ option. While you might lose data points, keeping your interviewees safe is more important. 

Before any data is collected, it might be a good idea to let your respondents know what they’re getting into. A quick, brief disclaimer either at the very beginning or right before asking the question can be an easy way to let your interviews know what’s going on. 

Touch on why you’re collecting the data, and how their contribution will help. Let them know that they should answer as honestly to themselves as possible. It’s also important to remind them how their responses will be used, and that their information will be kept anonymous and secure. 

Pride month is about honoring the LGBTQ+ community. They are proud to identify as they see fit, and we should celebrate along with them. 

By understanding a person’s gender identity, we can better appreciate their different opinions and experiences. When collecting data, it’s important to recognize a person’s differences to better both the project you’re working on and your connections. 

Happy pride month!