AI 中文总结
研究探讨种族歧视实证研究中种族影响的问题，通过分离种族研究应针对的影响及其设计能否得出该影响这两个主张，得出更宽松的可信估计和推断条件，重新分析实验发现西班牙裔选民在不同影响下的同民族偏好情况。
AI 中文摘要
关于种族歧视的实证研究在保持非种族特征不变的同时改变种族，文献将这种设计作为可信推断的必要条件。这种辩护包含两个主张：一项研究应针对种族的何种影响，以及其设计是否能得出该影响。本文将二者分开探讨。确保可信估计和推断的相同随机化过程能得出一系列种族估计量，从所有其他因素相同情况下的影响到种族内部影响（允许相关特征随种族变化）。该系列中的每个成员都是因果性而非描述性的，成员间的选择是关于种族类别是什么的一种主张——这一主张延伸到民族、宗教和其他索引相关特征的身份类别。本文得出了比文献中更宽松的可信估计和推断条件。通过重新分析一个西班牙语竞选实验，发现西班牙裔选民在种族内部影响下存在同民族偏好，而在所有其他因素相同的影响下则不存在。
英文摘要
Empirical studies of racial discrimination vary race while holding nonracial traits fixed, a design the literature defends as what credible inference requires. This defense bundles two claims: which effect of race a study should target, and whether its design can recover that effect. I separate them. The same randomization that secures credible estimation and inference recovers a family of race estimands, from the all-else-equal effect to a within-race effect that lets associated traits vary with race. Every member of that family is causal rather than descriptive, and the choice among members is a claim about what a racial category is -- a claim extending to ethnicity, religion, and other identity categories that index associated traits. I derive conditions, weaker than the literature's, for credible estimation and inference. Reanalyzing a Spanish-language campaign experiment, I find coethnic preference among Hispanic voters under the within-race effect and none under the all-else-equal effect.
