This week we’ll hear from two PhD Candidates about their CSCW papers!

Location: IRB 4105 and Zoom

 

Talk Title: Disability Meets Modality: A Sociotechnical Approach to Team Meetings

Speaker: Connie Siebold, PhD Candidate, College of Information, University of Maryland

Abstract: Team meetings are a key part of professional life which are experienced as sociotechnical, interpersonal phenomena. This interview study examines the intersection of modality, disability, and technology in the team meeting setting. Persistent concerns emerged across meeting modalities: participation as a sociotechnical challenge; social/teamwork considerations; stigma, disclosure, and expectations regarding professionalism; a lack of information regarding meetings; productivity problems; and dueling accommodations between disabled individuals. These themes represent challenges about taskwork, teamwork and social perception, and sociotechnical aspects. Findings suggest that flexibility to choose the modality of attendance based on individual context, along with flexibility to choose in-meeting supports, can help with dynamic needs. The accessibility interventions most desired by participants are both readily available and benefit all workers regardless of disability status, but require simultaneous infrastructural, technological, and process interventions to address.

Bio: Connie is a PhD candidate in the INFO College. Her primary dissertation research focuses on interpersonal connectivity and how information flows through people and systems – the study of ‘knowing a guy who knows a guy’. She also teaches in the INFO college and moonlights as a researcher or assistant on projects ranging from disability and accessibility to sociolinguistic identity and English language education. As a former librarian and bartender, she is happy to answer strange questions at strange hours and probably ‘knows a guy’ if you need one.

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Talk Title: Survival of the Notable: Gender Asymmetry in Wikipedia Collective Deliberations

Speaker: Khandaker “Swad” Tasnim Huq , PhD Candidate, College of Information, University of Maryland

Abstract: Communities on the web rely on open conversation forums for a number of tasks, including governance, information sharing, and decision making. However these forms of collective deliberation can often result in biased outcomes. A prime example are Articles for Deletion (AfD) discussions on Wikipedia, which allow editors to gauge the notability of existing articles, and that, as prior work has suggested, may play a role in perpetuating the notorious gender gap of Wikipedia. Prior attempts to address this question have been hampered by access to narrow observation windows, reliance on limited subsets of both biographies and editorial outcomes, and by potential confounding factors. To address these limitations, here we adopt a competing risk survival framework to fully situate biographical AfD discussions within the full editorial cycle of Wikipedia content. We find that biographies of women are nominated for deletion faster than those of men, despite editors taking longer to reach a consensus for deletion of women, even after controlling for the size of the discussion. Furthermore, we find that AfDs about historical figures show a strong tendency to result into the redirecting or merging of the biography under discussion into other encyclopedic entries, and that there is a striking gender asymmetry: biographies of women are redirected or merged into biographies of men more often than the other way round. Our study provides a more complete picture of the role of AfD in the gender gap of Wikipedia, with implications for the governance of the open knowledge infrastructure of the web.

Bio: I am a PhD Candidate at College of Information (iSchool) under the supervision of Dr. Giovanni Luca Ciampaglia (glciampaglia.com), at University of Maryland, College Park. I completed my M.Sc. in University of South Florida. I am from Bangladesh, located at South Asia on the Bay of Bengal. I am interested in computational social science and feminist platform governance. My research explores how digital knowledge infrastructures like Wikipedia shape and reflect systemic biases, particularly regarding gender, representation, and notability. My current work investigates how editorial decisions—such as article deletions—are made on Wikipedia, using a mix of survival analysis and natural language processing. My dissertation examines how gender bias manifests in the collective deliberation process of Articles for Deletion (AfD) and explores whether there is a solution to close the gender gap in Wikipedia coverage.