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A lack of mess? On navigating becoming an online ethnographer

Publikation: KonferencebidragPaperForskning

  • Ea Høg Utoft
  • ,
  • Anna-Kathrine Bendtsen
  • ,
  • Mie Kusk Soendergaard
Given the Covid-19 pandemic, ‘traditional’ ethnographers have found themselves becoming virtual ethnographers, as research projects are moved online. In this paper, we discuss our ongoing struggles while learning-by-doing online observations with an ambition of aiding fellow novice virtual ethnographers. Based on our experiences of constantly adapting while trying to not let the set-backs produced by the pandemic prevent our research, we ask the question of whether the mediation of our observations through in particular the application Zoom, risks preventing the ‘mess’ with which face-to-face observations are so ripe. We anchor our methodology in the premise that ‘messiness’ is desirable as it is an inevitable consequence of the embodied field relationships we build, filled with emotions and politics. In this paper, we highlight three encountered challenges pertaining to this possible lack of mess, namely, how 1) online observations shift our focus from actions and context to dialogue; 2) hybrid-formats (i.e., research participants are physically co-located, while the ethnographer observes via Zoom) present their own set of limitations; and 3) ongoing access negotiations require much more proactivity and persistence on the researcher’s part than in physical observations. Once unfolded, these experienced challenges show that virtual formats for observations do not prevent embodiment, however, we are only just beginning to understand how they change our experiences of embodiment in ethnographic research. In conclusion, the mess may not have disappeared entirely, however, as ethnographers, we have to work hard to incite as well as expose it.
Udgivelsesårmaj 2021
StatusUdgivet - maj 2021
BegivenhedCHI Conference on Human Factors in Computing Systems - Online, Japan
Varighed: 8 maj 202113 maj 2021


KonferenceCHI Conference on Human Factors in Computing Systems

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