The “Gender Offender” analysis: How and Why We Did It (Part One)


Deb Verhoeven

Statistics describing the parlous conditions for women in the Australian film industry have been gathered and circulated for more than 30 years. As long as I have worked in and reported on the industry these statistics have barely deviated. In some cases they’ve become marginally worse. Furthermore, their repeated release has given the industry’s structural misogyny an air of inevitability.

Statistics themselves have consequences. Reiterating the longstanding bias against women in the industry can be a disincentive for attempting change. Why bother when so many attempts to create better conditions for women have failed over and over again.

We need new forms of data in order to develop new strategies for redressing the systemic and frequently personal bias against women in the film industry.

The Gender Offender project stems from my own personal aspiration to use data to directly propose ways to improve the conditions for women in the Australian film industry rather than just (re)describe an industry that is historically intransigent to change. And as with all the Kinomatics projects its realization was a collaborative exercise. Both Vejune Zemaityte and Stuart Palmer were integral to the design and analytic aspects of the study.

This project rests on two inter-related manoeuvres. Firstly, it flips the object of analysis. If we are going to make the film industry a better place for women and other minorities then we need to understand the operations of gatekeeping that ensure the dominance of white, cis men. In this case, we focussed on the ways in which male film producers, and the “creative teams” (producers, writers, directors) they choose to work with, have reiterated male domination of the industry over a very long period of time. The second aspect of the project is to use the data we have collected on male control to propose an innovative course of action.

To achieve these outcomes we undertook a detailed series of steps from the initial data collection to developing network visualizations, which we outline below.

PART 1. Gendering Creative Teams

This aspect of the project was undertaken by Vejune Zemaityte.

Because there is no detailed, standardized, accessible collection of longitudinal data for the Australian film industry we established our own parameters and dataset.

We collected data on film titles and their associated creative teams for every drama feature submitted to the Australian Film Institute (AFI, later AACTA) Awards for a ten-year period from 2006 to 2015 (inclusive). We excluded documentary and short film categories.

There were several advantages to curating the dataset on this basis. By gathering data on feature films nominated for the national film awards we were not restricted to titles that had received government funding (as with lists provided by Screen Australia for instance) but could also include commercially financed films as well. We were also able to rely on broadly agreed definitions of what constituted an “Australian” film without the need for further evaluation. And finally, due to the long development times required to realize feature films in Australia, the extended period of ten years enabled us to capture repeated employment patterns across multiple projects.

This resulted in a dataset of 205 film titles which employed 1439 person roles made up of 930 unique people:

Unique Roles (includes multiple roles in multiple films)
1439 person roles
234 director roles
444 producer roles
319 writer roles
Unique People (might have other roles)
930 unique people
200 unique directors
344 unique producers
282 unique writers

Data was organised in the form of a database with a record for each creative role associated with the films contained in the data set. Fields in each record included: name of person, their gender, their role on the film, and the title of the film.

Although the Kinomatics project is committed to the principles of Open Data and although the data used to create this dataset was sourced from publicly available information, we also recognise the need for sensitivity around the release of data that includes personal names and this reason we have not made the source data for this project fully available.

The “Gender Offender” analysis: How We Did It

To collect the initial data on creative roles for the films nominated for AFI/AACTA we first consulted the AFI Web Archive

From there we were able to retrieve full information on award nominee films (including the names of the creatives involved in making the films) for the years 2008, 2009 and 2010 in the form of a Judge’s Handbook.

Unfortunately, there was no information for the years 2006 and 2007 at the archive.

To collect data for the later years after the AFI changed its name to the Australian Academy of Cinema and Television Arts we checked the AACTA website. There we were able to find information for the years 2012 – 2015 again in a format of a Judge’s Handbook.

Again, there was missing data with no information for the year 2011.

The first challenge then was to locate the missing information for the years 2006, 2007 and 2011. To address this we contacted the AFI Research Collection located at RMIT. Although we were unable to retrieve the actual Judge’s Handbooks from those years we were able to locate a list of the nominated films from each year. We then had to retrieve information from other sources about the people employed in creative roles for those films. To retrieve the names for director, writer and producer roles we primarily used The Screen Guide on Screen Australia’s website ( and IMDb.

It was difficult to confirm which people undertook which producer roles as some sources simply list producers as a single category while others distinguish between producers and executive producers. As a rule, we always tried to keep the producer list as short as possible and would only list the names of those who were nominated as producers (and not executive producers) in all sources (for the years 2006, 2007 and 2011).

Finally, it was difficult to determine a person’s gender based on their name alone, so we googled almost every creative team member to see how they self-nominated their gender (for all years).

Part Two available here.