Project description

There’s been a lot of attention given to women in Hollywood this year. Several organization
attempt to compile data for the general public. The work is certainly commendable but I found
it rather focused. I wanted to know if there was industry-wide discrimination. I wanted
the big-picture. The individual stories of sexual harassement and abuse were very disturbing.
I was shocked by some of the stories. Could all these men, several I admired, be that callous
and without empathy. Was there something about Hollywood that encouraged this. Many think so.
Small sets of data presented in the press and in the reports I read indicated that women were not
as well represented as men in the production of movies. The most common explanation given was that
men hired men. That made sense to me. So I wanted to focus on that. It is also said that women
don’t make profitable movies so I wanted to look at the top earners. The graphic is interactive
so viewers can check the data for themselves. Move your mouse over the image for details.

This single-image shows at a glance the distribution of women across the top jobs in the making
of the highest 100 grossing films for 2017, ranked left to right. Each column represents a movie.
Each row a job title.

I just included two observations 1). The uniform color in the rows reflects the small pool of
talent in some jobs. That is true for some jobs like Music. 2). It also shows that some
jobs behind the camera are associated with one gender or the other. Costume for example. The chart
also answers the initial claim I read about men hiring men. The answer is no. With some exceptions
like Star Wars, the columns are not a uniform color.

Each job is shown as a percentage because some are shared by more than one person. The increments
from a pale red to dark red show that 1-25% of the job is credited to women, then 26-50%, 51-75%
and 76-100%. Blue means there were no women. White means either none (0), or data missing ( ).

What makes this project innovative?

As I indicated above the approach here is different in that we stepped back and took
the broad perspective. A lot of opinions are expressed and a lot has been written about the dearth
of women behind the camera but I could not find anyone who took the time to distil the data
to question what many believe to be the case.

What was the impact of your project? How did you measure it?

I really don't know what the impact of this work has been. It was our most popular interactive product for the week following
it's release. But I have not heard back from any about it other than internally.

Source and methodology

There was a bit of rush on this. Never the less, I was able to obtain copies of the classic texts
on the subject. It was not difficult finding out who are the leading authorities since the industry
keeps a close watch and even funds much of research. I spoke with a few dozen people in the business.
So, once I had an idea of how the project should look I emailed below a mockup and a description to the best authors.

I believe the dearth of women in the film industry can be shown with greatest impact visually
so that the proportions are not lost in the details. For this reason I want to propose to my editors
that we display the findings as a chart. One chart, that would be large but would show at a glance
the issue and invite readers to explore for themselves the data.

Attached is a mockup of what I had in mind. You might find it rather confusing and I am happy
to talk about it on the telephone. I am open to suggestions.

So, I would need the gender of those categories of work listed below for 100 top grossing movies for 2017.

Director Writers Producer Executive Producer Lead Cast Supporting Cast Director of Photography Production Designer
Editor Associate Producers Costume Designer Music Composer Casting Director

The beauty of this kind of presentation is that it would very convenient for news services to insert
into their stories in all formats.

I was going to research the top 25 movies myself, however, if Dr. Smith and her colleagues are willing,
it would considerable more accurate to present a larger number of movies. This is why I am making the request.

Feel free to call or write with any questions. I would like to offer it for the week before the Oscars.


Here are the principal sources I approached in addition to individuals:

The biggest difficulty was compliling that data. I used two sources.
And where there were questions I went to the movie sites themselves.

I used Nexis reports and voter registration to identify the individuals where needed. Unfortunatly you can't tell the sex of a person just by the name. This took me an entire
week to do.

Technologies Used

I used Javascript, html, Css and D3 to build the interactive. My colleague Nicky Forster help me with D3. The data was all compiled in excel.

Project members

My colleague Nicky Forster help me with D3. He should get credit.


Project owner administration

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