Analysing the Bechdel Test and Dialogic Gender Bias in Film Through Social Network Analysis
September 2016-September 2019
The PhD project aims to research representation in film through the analysis of dialogue in relation to the increasingly popular yet scarcely-researched ‘Bechdel test’ of gender bias in film. To pass this test, a film must feature two named female characters who talk to each other about something other than a man. The strength of this idea is that it configures gender bias in film as a relational concept, existing in the ways that characters relate to one another on screen. However, it is inherently simplistic, producing an overall rating of films based on a single conversation. This has perhaps contributed to the lack of serious research on the subject, but all the while it has become arguably the dominant paradigm of popular gender bias discourse in relation to the movie industry.
My research is aimed at building understanding of the underlying factors which predict Bechdel test success, as a first step in analysing the usefulness of the concept. Moving beyond the Bechdel test, I am using the statistical tools of social network analysis to configure films as character networks in order to explore relational gender bias in film in more detail than is possible when limited to the criteria of the test. In doing so, I aim to uncover what information is lost when reducing films to a binary pass/fail rating, while developing more robust measures of gender bias within character networks. This is a cross-disciplinary research project with co-supervision from the School of Arts, Languages and Cultures.
I obtained my BA Social Sciences degree at the University of Manchester, using my dissertation to explore the usefulness of Donna Haraway’s cyborg metaphor of identity in understanding the complex experiences people report of using digital media such as online games to engage in identity play. I went on to complete the MSc in Social Research Methods and Statistics, also at the University of Manchester. My masters thesis analysed selective nonresponse bias in longitudinal surveys of older populations. More specifically, it explored the link between nonresponse rates and nonresponse bias in longitudinal surveys and whether patterns of wave-to-wave nonresponse bias affect certain types of variables differently. I am continuing to work on this research project with Dr. Joseph Sakshaug. During my undergraduate degree I participated in the first cohort of the University of Manchester Q-Step Centre’s summer internship programme, working with Manchester City Council’s Age-friendly Manchester Team on a project to develop an indicator-based approach to monitoring age-friendliness within Manchester.
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