{"id":161,"date":"2015-11-24T00:55:21","date_gmt":"2015-11-24T00:55:21","guid":{"rendered":"http:\/\/scottleut.com\/portfolio1\/?page_id=161"},"modified":"2015-11-24T19:36:42","modified_gmt":"2015-11-24T19:36:42","slug":"installation","status":"publish","type":"page","link":"https:\/\/scottleut.com\/portfolio1\/installation","title":{"rendered":"Installation"},"content":{"rendered":"
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He\/She<\/strong>
\nt-shirt yarn, window blind fabric, ink, wood, and paint
\n144\u201dx48\u201dx50\u201d, 2015<\/p>\n

His\/Her<\/strong>
\ncomputed image on photo paper
\n2 images – 44″x55″ each<\/p>\n

One indication of the value of women versus men in our social landscape is how often each appears in the news. For this work approximately 500,000 words were extracted from the NY Times website on January 20, 2015 by web-scraping eight levels deep. Considering the number of occurrences of the words \u201che\u201d and \u201cshe\u201d reveals textual gender bias. There are approximately two \u201ches” for every \u201cshe\u201d present. How does this reflect societal values? Without data collection and analysis this bias is invisible given the limited amount of text we see at one time while reading a news site page. This work makes this bias tangible, where \u201che\u201d and \u201cshe\u201d occur in direct proportion to that found on the website.<\/p>\n

The portraits are composed\u00a0from text. The female\u00a0portrait is made up of the most 40 most common words that follow “her” that do not occur in the 40 most common words that follow “his”. \u00a0The male portrait is made up of the most 40 most common words that follow “his” that do not occur in the 40 most common words that follow “her”.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n

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He\/She t-shirt yarn, window blind fabric, ink, wood, and paint 144\u201dx48\u201dx50\u201d, 2015 His\/Her computed image on photo paper 2 images – 44″x55″ each One indication of the value of women versus men in our social landscape is how often each appears in the news. For this work approximately 500,000 words were extracted from the NY …<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-builder.php","meta":{"nf_dc_page":"","footnotes":""},"class_list":["post-161","page","type-page","status-publish","hentry","has-author-avatar"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/pages\/161","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/comments?post=161"}],"version-history":[{"count":9,"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/pages\/161\/revisions"}],"predecessor-version":[{"id":284,"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/pages\/161\/revisions\/284"}],"wp:attachment":[{"href":"https:\/\/scottleut.com\/portfolio1\/wp-json\/wp\/v2\/media?parent=161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}