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美国人的政党从属关系可预测其使用婚外情网站的情况。

American Political-Party Affiliation as a Predictor of Usage of an Adultery Website.

机构信息

Global Center for Children and Families, University of California Los Angeles, Los Angeles, CA, 90024, USA.

Department of Sociology, Stony Brook University, Stony Brook, NY, USA.

出版信息

Arch Sex Behav. 2019 Apr;48(3):715-723. doi: 10.1007/s10508-018-1244-1. Epub 2018 Jul 12.

DOI:10.1007/s10508-018-1244-1
PMID:30003437
Abstract

The more politically conservative Americans are, the more restrictive their sexual attitudes are. A natural follow-up question is how this difference in attitudes relates to actual behavior. But self-reports of sexual behavior may be compromised by a social desirability bias that is influenced by the very sexual attitudes at issue. We employed a non-self-reported measure of sexual behavior: usage of the adultery-focused dating website Ashley Madison. Linking an August 2015 leak of user data from Ashley Madison to 2012 voter registration rolls from five U.S. states, we found 80,000 matches between 200,000 Ashley Madison user accounts and 50 million voters. According to simple rates in the sample, and also to predictively validated regression models controlling for state, gender, and age, we found that Democrats were least likely to use Ashley Madison, Libertarians were most likely, and Republicans, Greens, and unaffiliated voters were in between. Our results provide support for theories arguing that people with stricter sexual attitudes are paradoxically more likely to engage in deviant sexual behavior.

摘要

美国人的政治观念越保守,他们的性态度就越保守。一个自然而然的后续问题是,这种态度上的差异与实际行为有何关系。但性行为的自我报告可能会受到社会期望偏差的影响,而这种偏差又受到所涉及的性态度的影响。我们采用了一种非自我报告的性行为衡量标准:使用以通奸为重点的约会网站 Ashley Madison。我们将 2015 年 8 月 Ashley Madison 用户数据泄露与五个美国州的 2012 年选民登记名单相联系,发现 200000 个 Ashley Madison 用户账户与 5000 万选民之间有 80000 次匹配。根据样本中的简单比率,以及控制州、性别和年龄的预测验证回归模型,我们发现民主党人最不可能使用 Ashley Madison,自由党人最有可能,而共和党人、绿党人和无党派选民则处于中间位置。我们的研究结果支持了这样一种理论,即性观念越严格的人反而更有可能从事越轨的性行为。

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Residential Mobility and Lung Cancer Risk: Data-Driven Exploration Using Internet Sources.居住流动性与肺癌风险:利用互联网资源进行数据驱动的探索
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