RAPID: Understanding increased social bias during the COVID-19 crisis in the United States

研究发现，破坏性的社会事件会导致对群体外成员的社会偏见增加。本研究在美国COVID-19危机的背景下考察了这种关系，这场危机对数百万美国人的健康和经济福祉产生了不利影响。尽管自疫情爆发以来，已经报道了许多针对移民和亚洲后裔的偏见事件，但需要进行研究，以了解这种偏见的程度及其产生因素。随着危机的出现和继续发展，本研究将通过分析在2020年大部分时间收集的具有全国代表性的美国人样本的现有和新的调查数据来解决这一需求。研究结果将深入了解COVID-19如何影响美国的社会态度，更广泛地说，了解不同社会应对威胁其生活方式的大规模破坏的方式。这项研究将检验这样一个假设，即COVID-19风险认知与社会偏见之间的关系可能不像现有理论和研究所表明的那样直接，而且这种关系可能会随着当地威胁条件、感知风险类型（健康vs经济）和个人特征的变化而变化。研究小组分析了主要调查机构的民意调查数据，以验证这一假设。在研究的一个组成部分中，该团队从美国公众的代表性样本中收集新数据，以衡量对移民和不同种族和族裔群体成员的态度，以及对COVID-19的态度。他们在2020年的春季、夏季和秋季重复这项调查，以研究这些态度及其关系如何实时变化。在研究的第二个部分，他们分析了自2020年2月以来收集的关于COVID-19态度的现有调查数据。通过将新数据与现有数据相结合，他们正在建立一个全面的数据集，其中包括2020年大部分时间内关于COVID-19态度和社会偏见的数千次调查访谈。随着危机的继续发展，这项研究将对COVID-19的态度和社会偏见及其稳定与变化的程度做出强有力的估计。通过揭示社会偏见在何时何地最普遍，这项研究将有助于美国等不同社会保护其居民在下一次类似危机出现时免受负面对待，以及在不太严重的破坏和不安全事件中。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Research has found that disruptive social events can lead to increased social bias toward outgroup members. This research examines this relationship in the context of the COVID-19 crisis in the United States, which has adversely affected the health and economic well-being of millions of Americans. Although numerous incidents of bias directed toward immigrants and people of Asian descent have been reported since the outbreak began, research is needed to understand the extent of this bias and the factors that produce it. This research will address this need, by analyzing both existing as well as new survey data from nationally representative samples of Americans collected throughout much of 2020, as the crisis emerged and continues to evolve. The results will provide insights into how COVID-19 is affecting social attitudes in the United States, and more generally, into the ways that diverse societies respond to large-scale disruptions that threaten their way of life. This research will test the hypothesis that the relationship between COVID-19 risk perceptions and social bias may be less straightforward than existing theory and research suggest, and that this relationship may vary as a function of local threat conditions, type of perceived risk (health vs. economic), and personal characteristics. The research team analyzes public opinion data from leading survey organizations to test this hypothesis. In one component of the research, the team collects new data from a representative sample of the United States public to measure attitudes toward immigration and toward members of different racial and ethnic groups, alongside attitudes about COVID-19. They repeat this survey throughout the spring, summer, and fall of 2020 to study how these attitudes and their relationship may change in real time. In a second component of the research, they analyze existing survey data on COVID-19 attitudes that have been collected since February 2020. By combining new data with existing data, they are building a comprehensive dataset featuring thousands of survey interviews on COVID-19 attitudes and social bias spanning most of 2020. This research will generate robust estimates of COVID-19 attitudes and social bias, and their degree of stability versus change, as the crisis continues to unfold. By revealing where and when social bias is most prevalent, this research will help diverse societies such as the United States protect their residents against negative treatment the next time a similar crisis emerges, as well as during less severe incidents of disruption and insecurity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.