Lots of orgs report data differently. So we're on the same page about the data reported, here's how we categorize things.
In the gender section of the site, you can expect to see data about how people in your organization identify with respect to gender. All answers are provided as percentages and we’ve included a few charts that aggregate the data from every survey response we’ve received.
In this section, you’ll see gendered terms like male, female, agender, cisgender, etc and you may see accompanying pronouns like he/him, she/her, ze/they/them, in many cases.
We’ve indicated when the data provided is at the org/company, leadership, board, or technical level. And because it’s not standard across companies, we’ve asked org’s to share if their data represents the US or Global. Take me to the data ->
In the race section of the site, you’ll see data about the racial and ethnic composition of organizations. How companies categorize racial terms isn’t standard across companies, so we’ve done our best to put some parameters around how it's defined here.
We define underrepresented minorities (URMs) as anyone who identifies as Black or African American, Native American or Alaskan Native, Native Pacific Islander, Hispanic or Latinx, two or more URMs.
We define non-white as anyone who identifies as either East Asian, Southeast Asian, Middle Eastern, or two or more non-URM minorities. Take me to the data ->
In the section of the site dedicated to sexual orientation, you can expect to see data about the percentage of people who identify as LGBTQ+ at an organization.
We define LGBTQ+ as anyone who identifies as lesbian, gay, bisexual, transgender, or queer. Essentially, anyone at your organization that does not consider themselves to be cis-heterosexual. Take me to the data ->
In this section, we'll focus on where people work, where they’re from, and where they were born. You can expect to see data about the percentage of people who work remotely, are US-based, and more. Take me to the data ->
This section of the site contains data on a ton of different topics, including: age, education levels, visas, ability and veteran status.
When we mention temporary visas, we’re talking about H1-Bs, F1s, etc.
When it comes to age, we focused on collecting data for people in underrepresented categories, so you can assume anyone not named falls into the majority. The same holds true for ability and veteran status.
Education data focuses on people who are first-generation college students or don’t have bachelor’s degrees.
Ability data reflects folks who self identify as living with a disability and as you might expect, veteran status refers to folks who served in the military, navy, or air service. Take me to the data ->