Intersectional HCI: Engaging Identity through Gender, Race, and Class

By Ari Schlesinger, W. Keith Edwards, Rebecca E. Grinter. International Conference on Human Factors in Computing Systems, 2017

477 citations recorded by the source corpus.

Understanding users becomes increasingly complicated when we grapple with various overlapping attributes of an individual's identity. In this paper we introduce intersectionality as a framework for engaging with the complexity of users' "and authors" "identities", and situating these identities in relation to their contextual surroundings. We conducted a meta-review of identity representation in the CHI proceedings, collecting a corpus of 140 manuscripts on gender, ethnicity, race, class, and sexuality published between 1982-2016. Drawing on this corpus, we analyze how identity is constructed and represented in CHI research to examine intersectionality in a human-computer interaction (HCI) context. We find that previous identity-focused research tends to analyze one facet of identity at a time. Further, research on ethnicity and race lags behind research on gender and socio-economic class. We conclude this paper with recommendations for incorporating intersectionality in HCI research broadly, encouraging clear reporting of context and demographic information, inclusion of author disclosures, and deeper engagement with identity complexities.

Subfields: Sociology and Political Science, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/27b49a706d907c5d6858068ba97bbe873fcf687f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Sociology and Political Science

1. Margaret Drouhard
2. Josephine Hoy
3. Cynthia L. Bennett
4. Morgan Klaus Scheuerman
5. Jed R. Brubaker
6. Jeffrey P. Bigham
7. Anne Marie Piper
8. Oliver L. Haimson

In Human-Computer Interaction

1. Morgan Klaus Scheuerman
2. Margaret Drouhard
3. Josephine Hoy
4. Nithya Sambasivan
5. Cynthia L. Bennett
6. Jed R. Brubaker
7. Marco Turchi
8. Marco Gaido

Citations in the corpus

• Gender Bias in Machine Translation (2021, background): “, race and gender) (Crenshaw, 1989) which are not additive and cannot always be detected in isolation (Schlesinger et al., 2017).”
• Gender Recognition or Gender Reductionism?: The Social Implications of Embedded Gender Recognition Systems (2018, background): “A recent survey of the last thirty-five years of CHI proceedings found only three papers that included input from trans technology users [43].”
• Human-Computer Insurrection: Notes on an Anarchist HCI (2019, background): “An anarchist HCI requires an intersectional lens to avoid flattening the experiences of marginalized peoples [37, 123].”
• Revisiting Gendered Web Forms: An Evaluation of Gender Inputs with (Non-)Binary People (2021, background): “The ACM Digital Li-brary itself refects this bias: at the time of this paper’s writing, the keyword ”transgender” yields 27 results and ”non-binary” only an estimated 5 (though a marked improvement since the publication of Schlesinger et al.’s work on intersectional HCI [83]).”
• Deconstructing Community-Based Collaborative Design (2019, background): “Scholarly discourse in feminist and intersectional HCI highlights the importance of reflexivity of researchers [15, 88].”
• The Unexpected Entry and Exodus of Women in Computing and HCI in India (2018, background): “In this work, we seek to broaden feminist HCI scholarship to the Indian context with an intersectional lens [58].”
• HCI Guidelines for Gender Equity and Inclusivity (2020, background): “As a field, through our choice of research topics (e.g. [36 ]) and professional activities (e.g. SIGCHI’s Internationalisation, Diversity and Inclusion events [45]), we are increasingly signaling our collective value of developing more inclusive, critical, and intersectional frameworks and…”
• “It’s Complicated”: Negotiating Accessibility and (Mis)Representation in Image Descriptions of Race, Gender, and Disability (2021, background): “When researching the impact of technology, with few exceptions like [29], HCI and accessibility scholars tend to inquire populations that occupy one axis of marginalization [88, 98].”
• Critical Race Theory for HCI (2020, background): “Reflexivity – being selfaware and conscious of one’s own station and biases as they might affect research and writing – is something that most HCI researchers acknowledge as important [15, 109].”