Data for queer lives: How LGBTQ gender and sexuality identities challenge norms of demographics
Data for queer lives: How LGBTQ gender and sexuality identities challenge norms of demographics
复制标题
DOI：
10.1177/2053951720933286
复制
发表时间：
2020-01-01
影响因子：
8.5
通讯作者：
Ruelos, Spencer
中科院分区：
文献类型：
--
作者：
Ruberg, Bonnie;Ruelos, Spencer
在这篇文章中，我们认为，占主导地位的人口统计数据的规范是不足以解释的复杂性，许多女同性恋，男同性恋，双性恋，变性人，和酷儿（LGBTQ，或广义上的“酷儿”）的生活。在这里，我们从178人谁确定为非异性恋或非顺性的回答，我们开发的人口统计学问题，关于性别和性取向。人口统计数据通常将身份想象为固定的，单一的和离散的。然而，我们的研究结果表明，对于LGBTQ人群来说，性别和性身份往往是多重的，而且是不断变化的。绝大多数受访者表示，随着时间的推移，他们对自己性身份的理解发生了变化。此外，对于我们的许多受访者来说，性别认同是由重叠的因素组成的，包括性别和跨性别认同之间的关系。这些发现促使研究人员重新考虑如何通过数据来理解身份。从批判性数据研究、女权主义和酷儿数字媒体研究，以及像“黑人生活数据”这样的社会正义倡议中，我们呼吁将基于身份的数据重新想象为“酷儿数据”或“酷儿生活数据”。“我们还建议研究人员开发更具包容性的调查问题。与此同时，我们解决了酷儿观点通过抵制分类和“捕获”来破坏数据的潜在逻辑的方式。对于边缘化的人来说，这项工作的利害关系超出了学术界，特别是在算法和大数据时代，当谁是或不是“计数”的问题深刻影响了数字领域的可见性，访问和权力。
In this article, we argue that dominant norms of demographic data are insufficient for accounting for the complexities that characterize many lesbian, gay, bisexual, transgender, and queer (LGBTQ, or broadly "queer") lives. Here, we draw from the responses of 178 people who identified as non-heterosexual or non-cisgender to demographic questions we developed regarding gender and sexual orientation. Demographic data commonly imagines identity as fixed, singular, and discrete. However, our findings suggest that, for LGBTQ people, gender and sexual identities are often multiple and in flux. An overwhelming majority of our respondents reported shifting in their understandings of their sexual identities over time. In addition, for many of our respondents, gender identity was made up of overlapping factors, including the relationship between gender and transgender identities. These findings challenge researchers to reconsider how identity is understood as and through data. Drawing from critical data studies, feminist and queer digital media studies, and social justice initiatives like Data for Black Lives, we call for a reimagining of identity-based data as "queer data" or "data for queer lives." We offer also recommendations for researchers to develop more inclusive survey questions. At the same time, we address the ways that queer perspectives destabilize the underlying logics of data by resisting classification and "capture." For marginalized people, the stakes of this work extend beyond academia, especially in the era of algorithms and big data when the issue of who is or is not "counted" profoundly affects visibility, access, and power in the digital realm.