Over the past several years, social media campaigns such as #OscarsSoWhite (2015-2016) and #TimesUp (2017-present) have pressured the media industry to become more diverse and equitable in their hiring (including casting) practices, and to offer more and better representations of women, BIPOC, and LGBTQ+ characters.
In response to the industry’s heightened focus on improving its diversity and inclusivity, the Media Metadata Research Lab (mmrl — pronounced “merl”) has developed an original method for assigning “diversity scores” to films and television series. Unlike existing diversity reports that target industry or academic audiences, the mmrl Diversity Scoring system aims to be legible to a wide audience (i.e., the “ordinary viewer”); to be comprehensive and intersectional (accounting for the ethnicity, age, gender, sexuality, and nationality of the main characters in every media text); and to attend to both quantity and quality of representation (i.e., to highlight when representations of women or minorities are stereotypical or otherwise problematic).
In this presentation, we will present our Diversity Scores for 30 media properties that originally aired on major streaming platforms (Netflix, Disney+, and HBO Max) during the COVID-19 pandemic period, between January 2020 and April 2021. We opted to select texts from this period of time because, during the pandemic, streaming viewership has constituted the majority of media entertainment for millions of households, as cinemas have had to close for public health reasons. For the 30 texts we have chosen, we will share “glyphs” that we have designed to visualize our scores. We will show scores for individual media properties, scores for platforms, and scores for both actors and characters (as actors frequently play characters with different identities than their own). We will discuss how we hope to use Diversity Scores to support media literacy education and to provide a common vocabulary for discussing and debating representation.