Quantified Feminism and the Bechdel Test

Project Summary

Selen Berkman (ECE, CompSci), Sammy Garland (Math), and Aaron VanSteinberg (CompSci, English) spent ten weeks undertaking a data-driven analysis of the representation of women in film and in the film industry, with special attention to a metric called the Bechdel Test. They worked with data from a number of sources, including fivethirtyeight.com and the-numbers.com.

Themes and Categories
Computational Humanities, Data+, Social Sciences
Year
2017
Contact
Paul Bendich
Mathematics
bendich@math.duke.edu

Project Results: The team showed that movies which pass the Bechdel test, which requires that a movie have at least two female named characters who talk to each other about something other than a man, have a statistically significant higher return on investment when compared to films that do not.

They also demonstrated a clear positive relationship between the number of women working on the production of a film and the percentage of female dialogue. Finally, the team expanded the binary Bechdel test into a continuous score called the Bechdel score, and they demonstrated a clear positive correlation between this score and the percentage of overall film dialogue spoken by female characters. 

Click here for the Executive Summary

Faculty Lead & Project Manager: Stefan Waldschmidt

Room 351: Sharing Project Space and Coding

"I gained valuable program management experience. Given that after the program was over I got hired as a consultant manager at CollegeVine, I'd say it paid off." — Stefan Waldschmidt, Faculty Lead, Project Manager and PhD Candidate, English at Duke University

Related People

Related News

Sizing Up Hollywood’s Gender Gap
Tuesday, August 8, 2017
Analyzing data on women’s roles in American film, a Data+ team showed that 40 percent of female ro ...

Related Videos

Visit our YouTube Channel
Who is Data+

Related Projects

Farm to Fork (Year 2)

A team of students collaborating with Duke School of Medicine's Root Causes Fresh Produce Program, community members, and physicians throughout the Duke Health network will help integrate data from food deliveries to Duke Health patients with patient health record data and other available data sources to create a dashboard that can analyze, predict, and manage the Root Causes' "Food as Medicine" program. Specific outcomes will contribute to improving the Program's quantitative evaluation of its health impact as well as efficiency and satisfaction for its patients. Students will be assisted with IRB approval and mentorship from faculty and community advisors.

Project Leads: Esko Brummel, Willis Wong

Melting Ice, Shifting Krill

A team of students led by researchers at the Duke Marine Lab will explore the changing distribution of krill around the Antarctic Peninsula. Krill are a key prey species in this ecosystem, supporting a number of animals including whales, seals, and penguins, but they are dependent on winter sea ice and may be in trouble as climate change progresses. Using data from acoustic zooplankton surveys, students will create maps and other products to visualize the spatial distribution of krill over the past 20 summers, then create metrics that allow us to quantify the way that krill distribution around the Antarctic Peninsula is changing as the climate shifts and ice melts. These results will be key to our understanding of the impacts of climate change on this polar ecosystem.

 

Project Lead: Douglas Nowacek

Project Manager: Amanda Lohmann

 

Data Science for Community Safety in Durham

A team of students will partner closely with the City of Durham's newly formed Community Safety Department.  The Community Safety Department's mission is to identify, implement, and evaluate new approaches to enhance public safety that may not involve a law enforcement response or the criminal justice system. The student team will (1) analyze and identify geographic and temporal patterns in 911 calls for service, (2) conceptualize and build an abstracted data pipeline and tools that would enrich currently available 911 data with other social, economic, and health-related data, (3) explore associations between areas of high call volume, indicators of mental health distress, and histories of dispossession; and (4) identify methods by which future researchers could examine connections between varied 911 incident responses (e.g. police response, unarmed response, joint police, and mental health response) and life trajectories (e.g. arrest, jail time, hospitalization, unemployment, etc.).

 

Project Lead: Greg Herschlag, Anise Van, City of Durham

 

 

See all Research