Representation tests for writing are tools that you can use to assess how your novel represents characters. It helps you avoid stereotyping and tokenism in your writing. Here are some common tests to get you started.
The Bechdel test
The Bechdel test is a broad-strokes look at how women are represented in a work of fiction. Named for accidental creator Alison Bechdel, your novel or short story gets a passing grade on the Bechdel test if your story has:
- Two named female characters…
- Who talk to each other…
- About something other than a man.
Critics of the test complain it says nothing about the actual quality (or equality) of female representation in the work, but it’s a simple starting point.
The Mako Mori test
The Mako Mori test is also about female representation, but goes deeper than the Bechdel test, demanding more for a passing grade. Named for the character in Pacific Rim who exemplifies the principle, is passed if your story has:
- At least one female character…
- Who gets her own narrative arc…
- That is not about supporting a man’s story.
The Mako Mori test examines narrative arcs rather than simple conversation and dialogue. This makes it a stronger way to judge the quality of representation in a story.
The Pivotal Character test
On the same lines as the Bechdel and Mako Mori test, this one comes from the science fiction genre. Historically, the pivotal action in almost all science fiction novels is driven by male characters. This test examines that and shines a light on who has agency in your book, and who doesn’t.
Here’s how to run the Pivotal Character test. Draw up a table of all the pivotal decisions and actions in your book, including the minor ones. Now list the character who drives or causes that action.
There’s no “threshold” you need to cross to pass this test. However, it’s useful to critically examine your work and the agency of your characters. I ran this test on my work-in-progress sci-fi novel Kine. Although there was a balance of male and female characters driving the crucial action, I realised that my protagonist was almost completely passive for the majority of the book. She was simply going along with what other people were driving and deciding. She had no agency herself. That wasn’t what I wanted for her character and that gave me a clear direction for my next draft.
I wrote this test down a couple of years ago, but I didn’t record where it came from. I can’t find the original source now, so if you know, let me know.
Kelly Sue DeConnick’s Sexy Lamp test
The Sexy Lamp test is perhaps the most basic representation test. But sometimes basic is illuminating (see what I did there?)!
The Sexy Lamp test is failed if you can remove a female character from your story, replace her with a sexy lamp, and the story still works.
The DuVernay test
Similar to the Mako Mori test, the DeVernay test looks at representation of African-Americans and other minorities. It was first outlined by Manohla Dargis in the New York Times in 2016 and comes from the film industry. Others have since added more criteria for the test, so a work is considered to pass if it has:
- At least two named characters of colour…
- Who are not in a romantic relationship together…
- Who have complex lives rather than existing only in relation to white characters…
- Who have dialogue / conversations that are not about supporting a white character.
The key idea with passing the DeVernay test is that characters of colour have fully realised lives. Instead of serving as scenery or in support of white characters’ stories, they are full characters. Although it’s based on film, it can equally be applied to written fiction.
The Beige Index
Another concept from the film industry, The Beige Index is created by author Siang Lu and data-designer Jonathan O’Brien. Through painstakingly watching over 530 hours of movies, they classified the ethnic representation of the top 250 films on IMDb. Described as “the Bechdel test for race,” the Index classifies each film based on its Beige Score, from “Creamy” to “Welcome to Beigewatch.”
This is not a test in the same sense that the others I’ve listed here are. If you read the methodology of how Lu and O’Brien created the dataset (it’s really interesting), you’ll see why this doesn’t work as a direct test for fictional worlds. However, there’s no reason why you can’t create your own “Cast” grid like the one shown above – and use that to make an estimate of your story’s Beige Index.
Adapting representation tests for writing diverse characters
The representation tests for writing that I’ve listed here were first described for female characters, and those for characters of colour are more recent additions. However, they can be adapted to look at how your novel stacks up for non-binary and characters of different genders, LGBTIQA+ characters, characters of different ethnicities, neurodiverse characters, and characters with disabilities.
All characters deserve to be more than just a lamp in your story. (Pixar mascot excepted.)
Have I missed a representation test for writing diverse characters? Let me know if I have!