Alex J. Bates, Claire M. Kamp Dush, Wendy D. Manning
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Manning","doi":"10.1007/s11113-024-09907-1","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Objectives</h3><p>To quantify the role of state-level lesbian, gay, bisexual, transgender, and queer (LGBTQ+)-related policies on experiences of discrimination in a population-representative sample of partnered individuals.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>An adjusted multilevel random-intercept logistic regression model with individuals (level-1) nested within states (level-2) and a cross-level interaction term between gender/sexual identity and policy score was used to estimate the predicted probability of any experiences of discrimination for cisgender heterosexual, transgender and non-binary, and cisgender sexual minority respondents.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Experiences of discrimination in the past month were more common amongst transgender and non-binary (90.2%) respondents compared to their cisgender sexual minority (74.0%) or cisgender heterosexual (73.2%) counterparts. 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引用次数: 0
摘要
目的 量化州级女同性恋、男同性恋、双性恋、跨性别者和同性恋者（LGBTQ+）相关政策对有伴侣者歧视经历的影响。方法采用调整后的多层次随机截距逻辑回归模型，将个人（层次-1）嵌套在州（层次-2）中，并在性别/性身份和政策得分之间加入跨层次交互项，以估计顺性别异性恋、跨性别和非二元性以及顺性别少数性受访者遭受歧视的预测概率。结果变性和非二元性受访者（90.2%）在过去一个月中遭受歧视的经历比同性别的性少数群体受访者（74.0%）或同性别的异性恋受访者（73.2%）更常见。与顺性别异性恋受访者相比，交互项仅对跨性别和非二元性受访者具有统计意义（OR = 0.93，95% CI [0.88，0.98]），而对顺性别少数性受访者不具有统计意义（OR = 0.99，95% CI [0.97，1.01]）。这表明，随着各州的政策环境变得更具保护性，变性人和非二元性受访者遭受歧视的几率与顺性别性少数群体受访者或顺性别异性恋受访者相比有了更大幅度的下降。州一级的 LGBTQ + 政策保护扩大了性别认同与歧视经历之间的关系。
State-Level LGBTQ + Policies and Experiences of Interpersonal Discrimination among Sexual and Gender Minority People
Objectives
To quantify the role of state-level lesbian, gay, bisexual, transgender, and queer (LGBTQ+)-related policies on experiences of discrimination in a population-representative sample of partnered individuals.
Methods
An adjusted multilevel random-intercept logistic regression model with individuals (level-1) nested within states (level-2) and a cross-level interaction term between gender/sexual identity and policy score was used to estimate the predicted probability of any experiences of discrimination for cisgender heterosexual, transgender and non-binary, and cisgender sexual minority respondents.
Results
Experiences of discrimination in the past month were more common amongst transgender and non-binary (90.2%) respondents compared to their cisgender sexual minority (74.0%) or cisgender heterosexual (73.2%) counterparts. When compared to cisgender heterosexual respondents, the interaction term was found to be statistically significant for only transgender and non-binary (OR = 0.93, 95% CI [0.88, 0.98]) but not cisgender sexual minority respondents (OR = 0.99, 95% CI [0.97, 1.01]). Indicating that as state policy environments became more protective the odds of experiencing discrimination decreased at a more substantial rate for transgender and non-binary respondents when compared to cisgender sexual minority or cisgender heterosexual respondents.
Conclusions
Transgender and non-binary individuals experience more discrimination compared to their cisgender sexual minority or cisgender heterosexual counterparts. State-level LGBTQ + policy protections amplified the relationship between gender identity and experiences of discrimination.
期刊介绍：
Now accepted in JSTOR! Population Research and Policy Review has a twofold goal: it provides a convenient source for government officials and scholars in which they can learn about the policy implications of recent research relevant to the causes and consequences of changing population size and composition; and it provides a broad, interdisciplinary coverage of population research.
Population Research and Policy Review seeks to publish quality material of interest to professionals working in the fields of population, and those fields which intersect and overlap with population studies. The publication includes demographic, economic, social, political and health research papers and related contributions which are based on either the direct scientific evaluation of particular policies or programs, or general contributions intended to advance knowledge that informs policy and program development.
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