Tan Xiao, Lee Rennie, Ruppanner Leah
University of Melbourne Parkville VIC Australia.
University of Queensland, Institute for Social Science Research Indooroopilly QLD Australia.
Aust J Soc Issues. 2021 Dec;56(4):464-484. doi: 10.1002/ajs4.176. Epub 2021 Aug 22.
Following the COVID-19 outbreak, anti-Asian racism increased around the world, as exhibited through greater instances of abuse and hate crimes. To better understand the scale of anti-Asian racism and the characteristics of people who may be expressing racial prejudice, we sampled respondents in Australia and the United States over 31 August-9 September 2020 (1375 Australians and 1060 Americans aged 18 or above; source YouGov). To address potential social desirability bias, we use both direct and indirect (list experiment) questions to measure anti-Asian sentiment and link these variables to key socioeconomic factors. We find that, instead of being universal among general populations, anti-Asian sentiment is patterned differently across country contexts and socioeconomic groups. In the United States, the most significant predictor of anti-Asian bias is political affiliation. By contrast, in Australia, anti-Asian bias is closely linked to a wide range of socioeconomic factors including political affiliation, age, gender, employment status and income.
在新冠疫情爆发后,反亚裔种族主义在全球范围内有所增加,表现为更多的虐待和仇恨犯罪事件。为了更好地了解反亚裔种族主义的规模以及可能表现出种族偏见的人群特征,我们在2020年8月31日至9月9日期间对澳大利亚和美国的受访者进行了抽样(1375名澳大利亚人和1060名18岁及以上的美国人;来源:舆观调查网)。为了应对潜在的社会期望偏差,我们使用直接和间接(列表实验)问题来衡量反亚裔情绪,并将这些变量与关键的社会经济因素联系起来。我们发现,反亚裔情绪并非在普通人群中普遍存在,而是在不同国家背景和社会经济群体中呈现出不同的模式。在美国,反亚裔偏见的最重要预测因素是政治派别。相比之下,在澳大利亚,反亚裔偏见与广泛的社会经济因素密切相关,包括政治派别、年龄、性别、就业状况和收入。