Invisible in Data

Although government surveys collect significant amounts of data about the U.S. population, these surveys have historically excluded demographic questions about the LGBTQ population. As a result, official population data may misrepresent the LGBTQ community, resulting in biased or inefficient policies. The Invisible in Data series will explore policies such as voter identification and election law, voter engagement, and LGBTQ diversity in the workforce by empirically testing the reliability of existing statistical models that exclude sexual orientation variables.

Invisible in Data: The typical volunteer is white, female, and married. Are they straight, too?

Research agrees that “the typical volunteer is white, female, married with children, middle-aged, with higher levels of education and socioeconomic status.” But are they straight, too? This first article in the Invisible in Data series about LGBTQ communities explores that question. This article is excepted from a larger work that may be accessed by contacting the author at chw47@georgetown.edu. […]

Invisible in data: The lack of LGBTQ data collection

Although government surveys collect significant amounts of data about the U.S. population, these surveys have historically excluded demographic questions about the LGBTQ population. As a result, official population data may misrepresent the LGBTQ community, resulting in biased or insufficient policies. This article is the first in a series on citizen engagement and the LGBTQ community. The series will consider policies such as voter identification and election law, voter engagement, bipartisan LGBT policymakers and policies, and LGBTQ diversity in the workforce.