- March 23, 2018
Turning content into data is neither straightforward nor easy, but the .txtLAB at McGill University has been doing just this to better understand what’s going on between the covers of books and how we’re representing the world to readers. By focusing on one particular feature — character gender in contemporary fiction — Andrew and Eve will reveal a discouraging trend of female under-representation that remains constant across time and genre, providing the data necessary to self-assess the content we’re publishing and, more importantly, self-correct.
More resources related to this session
Using Data to Reveal Gender Bias in Contemporary Fiction
What do you know about the characters in your lists? Using data to reveal biases in contemporary fiction
Tech Forum speakers Andrew Piper and Eve Kraicer are asking questions about diversity and representation in fiction and answering them with data.