“Film Dialogue from 2,000 screenplays, Broken Down by Gender and Age”
“Across thousands of films in our dataset, it was hard to find a subset that didn’t over-index male. Even romantic comedies have dialogue that is, on average, 58% male. For example, Pretty Woman and 10 Things I Hate About You both have lead women (i.e., characters with the most lines). But the overall dialogue for both films is 52% male, due to the number of male supporting characters…
In 22% of our films, actresses had the most number of lines (i.e., they were the lead). Women are more likely to be in the second place for most number of lines, which occurs in 34% of films. The most abysmal stat is when women occupy at least 2 of the top 3 roles in a film, which occurs in 18% of our films. That same scenario for men occurs in about 82% of films.”
I always sigh when I see projects like this, because it feels like we are trying to use the tools of the master to tear down the master’s house: a huge amount of effort for potentially little impact.
What I mean is that women have been reporting discrimination, viewers have been reporting dissatisfaction, this problem isn’t exactly under-exposed. But somehow, this isn’t sufficient for industry and society to admit that gender representation matters and is currently both flawed and harmful. Apparently it needs to be “proven” in order to be real, proven using quantitative data points, and communicated in dispassionate graphs.
And what data can you really collect on these phenomena? Honestly, it’s not possible to quantify most of what goes on with representation and bias and stereotype and the resulting prejudices (violent, benevolent, internalized, etc…). The things that we can measure tend to be incidental — neither the route of the problem nor the ultimate harmful outcome (such that either linearly exists) — but once we measure them, they become the important indicators and the aspects that can’t be measured seem less valid.
We don’t live in a rational, logical world; our structures did not come about intentionally, they contradict each other and are subject to untold variables and are in many ways chaotic. When I see data like these, I fear that we are collapsing whole processes that really need to be seen and described qualitatively and addressed using the very human tools of empathy and growth and creativity.
I believe in the informative power of data — I am a scientist — and I think this was important and useful work. But data has no power on its own and, in a society that is so disinterested, I don’t know that the right people will be particular motivated by this information. Even if they do take action, I worry that the primary reaction would be to blindly increase the number of lines spoken by women — without the complementary focus on building strong characters and stories and casting actors who break our currently narrow expectations of female appearance.
