Collecting and Reporting Race and Ethnicity Data in HCI

被引：0

作者：

Chen, Yiqun T. ^{[1
]}

Smith, Angela D. R. ^{[2
]}

Reinecke, Katharina ^{[1
]}

To, Alexandra ^{[3
]}

机构：

[1] Univ Washington, Seattle, WA 98195 USA

[2] Univ Texas Austin, Austin, TX 78712 USA

[3] Northeastern Univ, Boston, MA 02115 USA

来源：

EXTENDED ABSTRACTS OF THE 2022 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2022 | 2022年

关键词：

race; ethnicity; systematic literature review; HCI research; survey;

D O I：

10.1145/3491101.3519685

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Engaging racially and ethnically diverse participants in Human-Computer Interaction (HCI) research is critical for creating safe, inclusive, and equitable technology. However, it remains unclear why and how HCI researchers collect study participants' race and ethnicity. Through a systematic literature analysis of 2016-2021 CHI proceedings and a survey with 15 authors who published in these proceedings, we found that reporting race and ethnicity of participants is uncommon and that HCI researchers are far from consensus on the collection and analysis of this data. Because a majority (>90%) of the articles that report participants' race and ethnicity are conducted in the United States, we focused our discussion on race and ethnicity accordingly. In future work, we plan to investigate considerations and best practices for collecting and analyzing race and ethnicity data in a global context.

引用

页数：8

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