{"id":933,"date":"2016-10-17T10:59:33","date_gmt":"2016-10-17T17:59:33","guid":{"rendered":"http:\/\/miriamposner.com\/classes\/dh101f16\/?p=933"},"modified":"2016-10-17T10:59:33","modified_gmt":"2016-10-17T17:59:33","slug":"gender-breakdown-of-city-workers-by-department","status":"publish","type":"post","link":"https:\/\/miriamposner.com\/classes\/dh101f16\/2016\/10\/17\/gender-breakdown-of-city-workers-by-department\/","title":{"rendered":"Gender Breakdown of City Workers by Department"},"content":{"rendered":"

The datatypes available in the gender breakdown of city workers by department<\/a>\u00a0consist of year, department title, number of employees, numbers and percentage of male and female employees, their total salaries and averages, divided by gender, and a breakdown of the percentage of the payroll that was paid out to each.<\/p>\n

The dataset’s ontology is a primarily gendered one, with an economically oriented epistemology, as it looks primarily at earnings and participation in the workforce, and uses gender to draw divisions within each department. It can function in a few different ways, but the clear overarching purpose is one of examining the role of gender in the workplace. Feminists, particularly, will find useful information here.<\/p>\n

As far as the phenomenon described by the dataset, there are a couple of interesting points. Within many departments, more of the total payroll is distributed to women, but it’s only in Recreation and Parks that women actually show a higher average earning than men, and by a margin of less than $1000. This means that, in many cases, greater numbers of women are working than men, but that they tend to earn less on an individual basis.<\/p>\n

As far as what’s left out, the dataset does insist on a binary categorization of male\/female, which makes it incapable of accounting for intersex, genderqueer, and transgender identities, and the ways that those might affect one’s workplace participation and earnings. Studying this would require an ontology capable of accounting for a spectrum of identities rather than a binary.<\/p>\n","protected":false},"excerpt":{"rendered":"

The datatypes available in the gender breakdown of city workers by department\u00a0consist of year, department title, number of employees, numbers and percentage of male and female employees, their total salaries … Continue reading “Gender Breakdown of City Workers by Department”<\/span><\/a><\/p>\n","protected":false},"author":75,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_eb_attr":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-933","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/posts\/933","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/users\/75"}],"replies":[{"embeddable":true,"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/comments?post=933"}],"version-history":[{"count":0,"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/posts\/933\/revisions"}],"wp:attachment":[{"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/media?parent=933"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/categories?post=933"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/miriamposner.com\/classes\/dh101f16\/wp-json\/wp\/v2\/tags?post=933"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}