Diversity statistics

I decided to put my money where my mouth is. I’ve said I’m committed to diverse characters in my fiction. Am I doing it?

I analyzed all of my published and circulating stories. I tracked six attributes:

1. Gender
2. Race
3. Sexual orientation
4. Age
5. Class
6. Ability/disability

I looked at 133 characters. Some of the classifications were tough. What class is a human girl trapped in a deer’s body? Is an alien in the bathroom faucet part of the working class? Are deities fully able, by definition?

Anyway. I did my best to sort it out, and here are the results.


42.9% female
51.8% male
5.3% other (aliens, machines, divine beings)

Pretty straightforward.


The trouble here is that race is often not mentioned, especially if the protagonist is the narrator. I went solely with what’s written on the page (not what was in my head as the author). Very few racial indicators are explicitly mentioned, but sometimes they can be inferred from context and story. For example, a Polish Christian is reasonably likely to be Caucasian; an 11th century Islamic ceramics merchant is pretty likely to be Arab. “Unknown” means that there are no clues whatsoever about race in the text.

33.8% Caucasian
6.0% Asian/Asian-American
6.0% Divine
5.3% Alien
4.5% Native American
3.8% Arab/Arab-American
3.8% Hispanic
3.0% African/African-American
1.5% Machine
32.3% Unknown

Given that “white is the default” and many readers assume white characters unless told otherwise, here’s another way to look at those numbers:

66.1% white, actual or implied/defaulted
21.1% people of color
12.8% unclassifiable

I’m not saying that any character whose race goes unmentioned must be white. However, it’s worth noting that some readers will perceive the numbers this way.


While sexual orientation isn’t always explicit either, I found it easier to infer a character’s identity based on their thoughts. At least that’s true in my stories, which might be because I write about love and romance a lot. So here I have two kinds of straight: Straight which is “quite likely heterosexual”, and straight* which is “the character shows interest in the opposite sex, but we can’t rule out bisexuality.” Unknown means there’s no indication in any direction.

17.3% straight
31.6% straight* (could be bisexual)
9.0% GLBT
57.9% unknown

By the same logic as above (that many readers assume heterosexuality unless told otherwise) it looks like this:

91.0% straight
9.0% GLBT

If you’re curious, it’s 4 bisexual, 4 gay, 3 lesbian, and 1 transgendered character.

4. AGE

I thought I’d see if I was defaulting to young heroes and heroines, or representing a wider part of the population. Most ages were possible to infer from the text.

12.8% ages 0-17
42.1% ages 18-35
24.1% ages 36-65
5.3% ages 66+
6.8% n/a (mostly divine beings and machines)
6.0% unknown
2.9% varies (the story covers full lifetimes)

The number categories are somewhat arbitrary.


I was surprised at how easy this was to infer from characters’ access to resources, regardless of what the story was about.

0.8% ruling class
21.8% upper class
17.3% middle class
44.2% working class
8.3% n/a (mostly divine beings and machines)
5.3% unknown
2.3% varies (the story covers full lifetimes)

These categories are nebulous. I just did my best to sort characters based on their jobs, living conditions, histories, and so on.


This category was tricky, because you can’t really say a character is fully able without knowing a lot about them. So there’s only two categories here.

88.0% able or implied able
12.0% disabled

The disabilities included cerebral palsy, deafness, mental illness, chronic pain, depression, social anxiety, limited movement, speech impediments, epilepsy, and others.


I’ll let you draw your own.

But here’s what I learned. Diversity matters. Reflecting the real world matters. Just the act of sorting all my characters increased my awareness of these issues. It brought up questions and assumptions in my mind. Is class a matter of income, lifestyle, or both? If I write sexual orientation clearly in my fiction and race not so often, does that reflect my own experience as a queer white writer or does it reflect inherent differences in the nature of those two “isms”? And on a side note, where the heck are all my Jewish characters? Maybe that’s just chance…

Anyway, I was surprised at how many working-class and disabled characters appeared in my fiction. I was also surprised at how few people of color and older characters populated my stories.

Overall, the number-crunching didn’t take very long (perhaps five hours), and it was well worth it for the learning experience.

I certainly don’t think writers should shove diversity in people’s faces. But there’s plenty of ways to give subtle cues that work very well. Like these:

Blatant bad example: “Johnny looked in the mirror. Yep. Still Mexican.”
Better example: “Johnny smelled home when he entered the kitchen. Only his mother’s cooking smelled like roast turkey, enchiladas, and horchata on Thanksgiving Day.”

I’ve heard the arguments that class/race/whatever is often irrelevant to a character in a story. Sure, that’s true sometimes. I hate stories where a character “needs” to be female (for example) simply because she must fall in love or get pregnant, and heaven help us if we have a female starship captain just for the heck of it.

But really, all these social elements influence a character’s outlook and interaction with the world. And while sometimes they aren’t explicit, they do influence the character’s experience. They’re part of that character and they deserve our respect as writers and readers.

Effectively, here’s what this means for writers: If you know your character’s background, you have a tool for making that character come to life in your story. If you don’t, that character will tend to reflect your own experience–and that’s often why characters come out flat or indistinguishable, rather than as individuals that readers love as real people. And for readers: Question your assumptions. Are you assuming that character is just like you? Did you stop to think about it?

Comments? Questions? Other stats I should try to pull from these numbers?

7 thoughts on “Diversity statistics

  1. Pingback: Aliette de Bodard » Blog Archive » Diversity Statistics

  2. I typed it in manually. I’d be happy to send it, but how would it help? I basically listed the characters, then sorted the columns one at a time, then checked the chart of what percent that was. I’m sure Excel could have done this for me, but I’m not skilled with it, so I didn’t know how.


  3. TV shows and movies often dodge the issue of gender and/or race by making a female or minority character the one in charge of, say a police precinct or a military unit. But that character is minor in the context of the story itself, often leaving the white male characters the focus of the story.


  4. Pingback: ISBW #239 – Vylar Kaftan Interview | The Murverse

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.