{"id":19055,"date":"2014-08-30T06:00:39","date_gmt":"2014-08-30T10:00:39","guid":{"rendered":"http:\/\/thesocietypages.org\/cyborgology\/?p=19055"},"modified":"2014-08-29T18:15:24","modified_gmt":"2014-08-29T22:15:24","slug":"on-twitters-gender-metric","status":"publish","type":"post","link":"https:\/\/thesocietypages.org\/cyborgology\/2014\/08\/30\/on-twitters-gender-metric\/","title":{"rendered":"On Twitter’s Gender Metric"},"content":{"rendered":"

\"Screen<\/a><\/p>\n

 <\/p>\n

Twitter recently made analytics available for free to all users. One of the free metrics is the gender distribution of your followers. This metric is flawed in a lot of ways (most obviously because it\u2019s binary: there are only men and women). Most puzzling, however, is how Twitter determines a an account-holder\u2019s gender. Users don\u2019t have to self-identify–in fact, there\u2019s not even an option to do this.<\/p>\n

As both this post<\/a> about the gender metric and this post<\/a> from Twitter about its gender-targeted marketing show, Twitter treats gender as an emergent pattern of behavior<\/i>. As the latter explains, users are thought to send \u201csignals\u201d–such as \u201cuser profile names or the accounts she or he follows\u201d–that \u201chave proven effective in inferring gender.\u201d<\/p>\n

Classically, one\u2019s body (physiology, phenotype) was the \u2018signal\u2019 from which one inferred gendered (or raced) behavior: vagina = nurturing, scrotum = likes video games. In this model, gender is a fixed characteristic inherent in sexed bodies. The kind of body you had determined the patterns of behavior you exhibited.<\/p>\n

Twitter\u2019s approach to gender is an example of a broader shift in our understanding of gender (and social identities more generally): genders are not fixed characteristics, but emergent properties. This understanding of gender is different than the traditional one, but it\u2019s not clear that it\u2019s any better. For example, we only recognize something as<\/i> a pattern if it resonates with other patterns we\u2019ve been habituated to recognize as such (what Reich describes here<\/a> as \u201crational\u201d moments). Twitter isn\u2019t crunching numbers to figure out what different kinds of gender patterns people follow; rather, they\u2019re listening for users who fall in phase with already-set \u201cmasculine\u201d and \u201cfeminine\u201d vibes. (As they say, \u201cwhere we can\u2019t predict gender reliably, we don\u2019t.\u201d) To count and be treated as a full person\/user, you have to exhibit legibly gendered patterns of behavior. Otherwise, you\u2019re effectively non-existent, just irrational noise.
\nTo close with an aside: Has anyone written about the relationship between these gender-predicting algorithms and the parlour game on which Turing based his test? The game was about determining whether or not one\u2019s interlocutor was a woman.<\/p>\n","protected":false},"excerpt":{"rendered":"

  Twitter recently made analytics available for free to all users. One of the free metrics is the gender distribution of your followers. This metric is flawed in a lot of ways (most obviously because it\u2019s binary: there are only men and women). Most puzzling, however, is how Twitter determines a an account-holder\u2019s gender. Users […]<\/p>\n","protected":false},"author":1929,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[9967],"tags":[],"class_list":["post-19055","post","type-post","status-publish","format-standard","hentry","category-commentary"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/posts\/19055","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/users\/1929"}],"replies":[{"embeddable":true,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/comments?post=19055"}],"version-history":[{"count":1,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/posts\/19055\/revisions"}],"predecessor-version":[{"id":19057,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/posts\/19055\/revisions\/19057"}],"wp:attachment":[{"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/media?parent=19055"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/categories?post=19055"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thesocietypages.org\/cyborgology\/wp-json\/wp\/v2\/tags?post=19055"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}