Niederdeppe Jeff, Porticella Norman, Liu Jiawei, Michener Jamila, Franklin Fowler Erika, Nagler Rebekah H, Taylor Teairah, Barry Colleen L, Lewis Neil A
Department of Communication, Cornell University, Ithaca, NY 14853, USA.
Cornell Jeb E. Brooks School of Public Policy, Cornell University, Ithaca, NY 14853, USA.
PNAS Nexus. 2025 Jan 3;4(1):pgae588. doi: 10.1093/pnasnexus/pgae588. eCollection 2025 Jan.
Researchers have raised concerns that messages describing racial disparities in social outcomes can reduce or polarize support for public policies to address inequality. We questioned this assumption by testing the impact of carefully crafted messages about child tax credit (CTC) expansion. We conducted two randomized message trials, study 1 using Prolific's nonprobability panel ( = 1,402) and study 2 using SSRS's Opinion Panel, a web-based probability sample of US adults ( = 4,483). Each study included comparably sized subsamples of Black, Hispanic, and White respondents from across the political spectrum. Study 1 compared six candidate messages to a control message and identified promising message strategies for replication. Study 2 compared two messages advocating for CTC expansion-one emphasizing policy benefits to all children (universalist) and the other describing benefits to all but even greater benefits to Black and Hispanic children (targeted universalist)-to a control message simply describing the policy. Primary outcomes were policy support and policy advocacy intentions. Study 2 tested preregistered hypotheses and conducted additional exploratory analyses using linear models. Both treatment messages produced greater policy support and advocacy intentions than the control message among Black and Hispanic respondents (Cohen's 0.12 to 0.28). The universalist message also produced greater policy support than the control message among White respondents (Cohen's = 0.16). The targeted universalist message did not reduce policy support or advocacy intentions among White and Republican respondents. Well-designed messages emphasizing policy efficacy can promote support for a redistributive tax policy across racial, ethnic, and political identities.
研究人员担心，描述社会结果中种族差异的信息可能会减少或使对解决不平等问题的公共政策的支持两极分化。我们通过测试精心设计的关于扩大儿童税收抵免（CTC）的信息的影响，对这一假设提出了质疑。我们进行了两项随机信息试验，研究1使用Prolific的非概率样本（n = 1402），研究2使用SSRS的意见样本，这是一个基于网络的美国成年人概率样本（n = 4483）。每项研究都包括来自不同政治派别的黑、西班牙裔和白人受访者的规模相当的子样本。研究1将六条候选信息与一条对照信息进行了比较，并确定了有前景的信息策略以供复制。研究2将两条倡导扩大CTC的信息——一条强调对所有儿童的政策好处（普遍主义），另一条描述对所有儿童的好处，但对黑人和西班牙裔儿童的好处更大（有针对性的普遍主义）——与一条简单描述该政策的对照信息进行了比较。主要结果是政策支持和政策倡导意图。研究2检验了预先登记的假设，并使用线性模型进行了额外的探索性分析。在黑人和西班牙裔受访者中，两条处理信息都比对照信息产生了更大的政策支持和倡导意图（科恩d值为0.12至0.28）。在白人受访者中，普遍主义信息也比对照信息产生了更大的政策支持（科恩d值 = 0.16）。有针对性的普遍主义信息并没有降低白人和共和党受访者的政策支持或倡导意图。精心设计的强调政策效力的信息可以促进不同种族、族裔和政治身份的人对再分配税收政策的支持。
