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Cited by 76Gender and Feminist StudiesLGBTQ Health, Identity, and PolicyBioethics and Human Rights Issues

”Why are they all obsessed with Gender?” — (Non)binary Navigations through Technological Infrastructures

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Spiel, Katta·2021·Designing Interactive Systems Conference 2021
DOI 10.1145/3461778.3462033
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Abstract

Gender is encoded in multiple technological infrastructures, most prominently in digital forms across educational, commercial, medical and governmental contexts. To illustrate the pervasiveness of (binary) gender ideologies and the impact this can have on non-binary individuals – like me – encountering them, I conducted an autoethnography. For more than a year, starting with me receiving a legal non-binary status, I documented systems that did not allow me to register my gender correctly. The findings indicate how technological infrastructures predominantly encode gender as a fixed, immutable and static binary variable with limited options for non-binary people to adequately register self-determined choices for gender and/or (gendered) titles. I further analyse the range of reactions that I received when pro-actively asking for workarounds, fixes and updates, indicating how pointing towards those issues can trouble the status quo, identities and power hierarchies in unintended ways. I close on suggestions for the refactoring of existing and design of new technological infrastructures around gender and reflect on the value of lived experience in knowledge production – as well as the cost it comes with for those doing this research.

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  • Digital footprints have varying levels of mutability, which is of particular importance when trans people change their names.

    “Digital footprints have varying levels of mutability, which is of particular importance when trans people change their names [100].”

    From Paradoxes of Openness: Trans Experiences in Open Source Software (2024) · cites this paper as [100]

    Section 4.3 reports that changes to gendered digital records had differing outcomes: some were systemic, some incomplete, and many were not made. Section 6.1 also discusses updating databases and their backwards compatibility. These passages support the point that digital records differ in how readily they can be changed, but our copy does not connect that point to digital footprints left when trans people change their names. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

  • First-person approaches demonstrate value in giving insights into personal experience.

    “We were inspired by first-person approaches [52,66] across HCI such as collaborative pieces [62,91], autoethnographies [61,65,76,87] and vignettes [5,24], demonstrating the value of first-person approaches in giving insights into personal experience.”

    From Reflection Across AI-based Music Composition (2024) · cites this paper as [87]

  • The method contrasts other methods such as diary studies or autoethnography, where more commitment is typically required from participants.

    “Our method contrasts other methods such as diary studies [8,31] or autoethnography [61,65,76,87], where more commitment is typically required from participants.”

    From Reflection Across AI-based Music Composition (2024) · cites this paper as [87]

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References 82 · Cited by 76

Research works printed but not linked: 48

  1. Sara Ahmed. 2019. A complaint biography. Biography 42, 3 (2019), 514-523.
  2. Samuel E Bartos. 2008. Letting Privates Be Private: Toward a Right of Gender Self-Determination. Cardozo JL & Gender 15 (2008), 67.
  3. Kevin G Behrens. 2020. A principled ethical approach to intersex paediatric surgeries. BMC Medical Ethics 21, 1 (2020), 1-9.
  4. Ruha Benjamin. 2019. Race After Technology: Abolitionist Tools for the New Jim Code. John Wiley & Sons.
  5. Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Martin Potthast, Francisco Rangel, Paolo Rosso, Günther Specht, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, and Eva Zangerle. 2020. Shared Tasks on Authorship Analysis at PAN 2020. In Advances in Information Retrieval, Joemon M. Jose, Emine Yilmaz, João Magalhães, Pablo Castells, Nicola Ferro, Mário J. Silva, and Flávio Martins (Eds.). Springer International Publishing, Cham, 508-516.
  6. Rena Bivens. 2017. The gender binary will not be deprogrammed: Ten years of coding gender on Facebook. New Media & Society 19, 6 (2017), 880-898. https://doi.org/10.1177/1461444815621527 · DOI
  7. Geoffrey C Bowker and Susan Leigh Star. 2000. Sorting things out: Classification and its consequences. MIT press.
  8. Meredith Broussard. 2018. Artificial unintelligence: How computers misunderstand the world. Mit Press.
  9. Joy Buolamwini and Timnit Gebru. 2018. Gender Shades: Intersectional Accu- racy Disparities in Commercial Gender Classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (Proceedings of Machine Learning Research, Vol. 81), Sorelle A. Friedler and Christo Wilson (Eds.). PMLR, New York, NY, USA, 77-91. http://proceedings.mlr.press/v81/buolamwini18a. html
  10. Sabrina Burtscher and Katta Spiel. 2020. "But Where Would I Even Start?": Developing (Gender) Sensitivity in HCI Research and Practice. In Proceedings of the Conference on Mensch Und Computer (Magdeburg, Germany) (MuC '20). Association for Computing Machinery, New York, NY, USA, 431-441. https: //doi.org/10.1145/3404983.3405510 · DOI
  11. Judith Butler. 1993. Bodies that Matter: On the Discursive Limits of" sex". Psy- chology Press.
  12. Curtis C. Cain and Eileen Trauth. 2017. Black Men in IT: Theorizing an Au- toethnography of a Black Man's Journey into IT within the United States of America. SIGMIS Database 48, 2 (April 2017), 35-51. https://doi.org/10.1145/ 3084179.3084184 · DOI
  13. Alan Chamberlain, Mads Bødker, and Konstantinos Papangelis. 2017. Mapping Media and Meaning: Autoethnography as an Approach to Designing Personal Heritage Soundscapes. In Proceedings of the 12th International Audio Mostly Con- ference on Augmented and Participatory Sound and Music Experiences (London, United Kingdom) (AM '17). Association for Computing Machinery, New York, NY, USA, Article 32, 4 pages. https://doi.org/10.1145/3123514.3123536 · DOI
  14. Heewon Chang. 2016. Autoethnography as method. Vol. 1. Routledge.
  15. Sally Jo Cunningham and Matt Jones. 2005. Autoethnography: A Tool for Practice and Education. In Proceedings of the 6th ACM SIGCHI New Zealand Chapter's International Conference on Computer-Human Interaction: Making CHI Natural (Auckland, New Zealand) (CHINZ '05). Association for Computing Machinery, New York, NY, USA, 1-8. https://doi.org/10.1145/1073943.1073944 · DOI
  16. Eric John Ramos David. 2013. Internalized oppression: The psychology of marginal- ized groups. Springer Publishing Company.
  17. Catherine D'Ignazio and Lauren Klein. 2020. Chapter Three: "What Gets Counted Counts". In Data Feminism. PubPub.
  18. Julia R. Fernandez and Jeremy Birnholtz. 2019. "I Don't Want Them to Not Know": Investigating Decisions to Disclose Transgender Identity on Dating Platforms. Proc. ACM Hum.-Comput. Interact. 3, CSCW, Article 226 (Nov. 2019), 21 pages. https://doi.org/10.1145/3359328 · DOI
  19. Miranda Fricker. 2007. Epistemic injustice: Power and the ethics of knowing. Oxford University Press.
  20. Pauline Gourlet. 2018. Children's Conversation with Experience: Making Emo- tional Imprints. In Proceedings of the 17th ACM Conference on Interaction Design and Children (Trondheim, Norway) (IDC '18). Association for Computing Ma- chinery, New York, NY, USA, 313-324. https://doi.org/10.1145/3202185.3202734 · DOI
  21. Terry Halpin and Tony Morgan. 2010. Information modeling and relational databases. Morgan Kaufmann.
  22. Foad Hamidi, Morgan Klaus Scheuerman, and Stacy M. Branham. 2018. Gen- der Recognition or Gender Reductionism? The Social Implications of Embed- ded Gender Recognition Systems. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1-13. https: //doi.org/10.1145/3173574.3173582 · DOI
  23. Donna Haraway. 1988. Situated knowledges: The science question in feminism and the privilege of partial perspective. Feminist studies 14, 3 (1988), 575-599.
  24. Donna J Haraway. 2016. Staying with the trouble: Making kin in the Chthulucene. Duke University Press.
  25. Alison M Jaggar. 1989. Love and knowledge: Emotion in feminist epistemology. Inquiry 32, 2 (1989), 151-176.
  26. Fariba Karimi, Claudia Wagner, Florian Lemmerich, Mohsen Jadidi, and Markus Strohmaier. 2016. Inferring Gender from Names on the Web: A Compara- tive Evaluation of Gender Detection Methods. In Proceedings of the 25th In- ternational Conference Companion on World Wide Web (Montréal, Québec, Canada) (WWW '16 Companion). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, CHE, 53-54. https: //doi.org/10.1145/2872518.2889385 · DOI
  27. Os Keyes, Chandler May, and Annabelle Carrell. 2021. You Keep Using That Word: Ways of Thinking about Gender in Computing Research (CSCW '21). Association for Computing Machinery, New York, NY, USA, Article 39, 23 pages. https://doi.org/10.1145/3449113 · DOI
  28. Matthias Korn and Susann Wagenknecht. 2017. Friction in Arenas of Repair: Hacking, Security Research, and Mobile Phone Infrastructure. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (Portland, Oregon, USA) (CSCW '17). Association for Computing Machinery, New York, NY, USA, 2475-2488. https://doi.org/10.1145/2998181. 2998308 · DOI
  29. Susan Leavy. 2018. Gender Bias in Artificial Intelligence: The Need for Diversity and Gender Theory in Machine Learning. In Proceedings of the 1st International Workshop on Gender Equality in Software Engineering (Gothenburg, Sweden) (GE '18). Association for Computing Machinery, New York, NY, USA, 14-16. https://doi.org/10.1145/3195570.3195580 · DOI
  30. Dan Lockton, Tammar Zea-Wolfson, Jackie Chou, Yuhan (Antonio) Song, Erin Ryan, and CJ Walsh. 2020. Sleep Ecologies: Tools for Snoozy Autoethnography. Association for Computing Machinery, New York, NY, USA, 1579-1591. https: //doi.org/10.1145/3357236.3395482 · DOI
  31. Linda Nicholson. 1994. Interpreting gender. Signs: Journal of Women in Culture and Society 20, 1 (1994), 79-105.
  32. Cale J. Passmore, Max V. Birk, and Regan L. Mandryk. 2018. The Privilege of Immersion: Racial and Ethnic Experiences, Perceptions, and Beliefs in Digital Gaming. In Proceedings of the 2018 CHI Conference on Human Factors in Com- puting Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1-19. https://doi.org/10.1145/3173574.3173957 · DOI
  33. Kenneth A Pettersen, Nick McDonald, and Ole Andreas Engen. 2010. Rethinking the role of social theory in socio-technical analysis: a critical realist approach to aircraft maintenance. Cognition, technology & work 12, 3 (2010), 181-191.
  34. Barbara J Risman. 2004. Gender as a social structure: Theory wrestling with activism. Gender & society 18, 4 (2004), 429-450.
  35. Michelle Rodino. 1997. Breaking out of Binaries: Reconceptualizing Gender and its Relationship to Language in Computer-Mediated Communication. Journal of Computer-Mediated Communication 3, 3 (12 1997). https://doi.org/10.1111/j. 1083-6101.1997.tb00074.x JCMC333. · DOI
  36. Gina Miranda Samuels and Fariyal Ross-Sheriff. 2008. Identity, Oppression, and Power: Feminisms and Intersectionality Theory. Affilia 23, 1 (2008), 5-9. https://doi.org/10.1177/0886109907310475 · DOI
  37. Aliya Saperstein. 2006. Double-checking the race box: Examining inconsistency between survey measures of observed and self-reported race. Social Forces 85, 1 (2006), 57-74.
  38. Erika Shehan and W. Keith Edwards. 2007. Home Networking and HCI: What Hath God Wrought?. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '07). Association for Computing Machinery, New York, NY, USA, 547-556. https://doi.org/10.1145/ 1240624.1240712 · DOI
  39. Stef M. Shuster and Ellen Lamont. 2020. Sticks and stones break our bones, and words are damaging: how language erases non-binary people. In The Emergence of Trans -Cultures, Politics and Everyday Lives, Ruth Pearce, Igi Moon, Kat Gupta, and Deborah Lynn Steinberg (Eds.). Routledge, New York, NY, USA, 103-115.
  40. Katta Spiel, Oliver L. Haimson, and Danielle Lottridge. 2019. How to Do Better with Gender on Surveys: A Guide for HCI Researchers. Interactions 26, 4 (June 2019), 62-65. https://doi.org/10.1145/3338283 · DOI
  41. Katta Spiel, Os Keyes, and Pınar Barlas. 2019. Patching Gender: Non-Binary Utopias in HCI. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI EA '19). Association for Computing Machinery, New York, NY, USA, 1-11. https://doi.org/10.1145/ 3290607.3310425 · DOI
  42. Eric A Stanley. 2014. Gender self-determination. Transgender Studies Quarterly 1, 1-2 (2014), 89-91.
  43. Susan Leigh Star. 2002. Got infrastructure? How standards, categories, and other aspects of infrastructure influence communication. In 2 ND SOCIAL STUDY OF IT WORKSHOP AT THE LSE ICT AND GLOBALIZATION. 22-23.
  44. Susan Leigh Star. 2002. Infrastructure and Ethnographic Practice. Scand. J. Inf. Syst. 14, 2 (2002), 6. http://aisel.aisnet.org/sjis/vol14/iss2/6
  45. Allucquère Rosanne Stone. 1996. The war of desire and technology at the close of the mechanical age. MIT press.
  46. Derald Wing Sue, Christina M Capodilupo, Gina C Torino, Jennifer M Bucceri, Aisha Holder, Kevin L Nadal, and Marta Esquilin. 2007. Racial microaggressions in everyday life: implications for clinical practice. American psychologist 62, 4 (2007), 271.
  47. Stephanie S Turner. 1999. Intersex identities: Locating new intersections of sex and gender. Gender & society 13, 4 (1999), 457-479.
  48. Andrea L. Wirtz, Tonia C. Poteat, Mannat Malik, and Nancy Glass. 2020. Gender- Based Violence Against Transgender People in the United States: A Call for Research and Programming. Trauma, Violence, & Abuse 21, 2 (2020), 227-241. https://doi.org/10.1177/1524838018757749 · DOI

Authors
Spiel, K.
Affiliations
TU Wien (AT)
Corresponding author
Spiel, Katta
ORCID
Spiel, Katta
Venue
Designing Interactive Systems Conference 2021
Publisher
ACM
Published
2021-06-28
Pages
478-494
DOI
10.1145/3461778.3462033
OpenAlex
W3175775456
Cited by
76
References
82
Citations by year
2026: 13 · 2025: 23 · 2024: 19 · 2023: 16 · 2022: 3 · 2021: 2
FWCI
74.97
Type
conference paper
Language
en
Open access
Licence
Locations
Designing Interactive Systems Conference (publishedVersion, other-oa)
Funders
Austrian Science Fund (T1146-G, T 1146)
Topics
  • Social Sciences › Gender Studies › Gender and Feminist Studies
  • Social Sciences › Psychology › Social Psychology › LGBTQ Health, Identity, and Policy
  • Physical Sciences › Computer Science › Information Systems › Bioethics and Human Rights Issues
Keywords
non-binary people, gender binary, technological infrastructure, digital systems, gendered titles, power hierarchies, autoethnography, lived experience, legal gender recognition

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