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And the Rest is History: Measuring the Scope and Recall of Wikipedia’s Coverage of Three Women’s Movement Subgroups

Event Type
Ceremony/Service
Sponsor
Department of Sociology
Location
https://illinois.zoom.us/j/87103866226?pwd=R1h0VERuQ2htcXhtQVpuMnBXM1oyUT09
Virtual
wifi event
Date
Oct 25, 2021   11:00 am  
Speaker
Laura Nelson, Assistant Professor at University of British Columbia
Views
12

Bio: "Dr. Laura Nelson uses computational methods -principally text analysis,natural language processing, machine learning, and network analysis techniques -to study social movements, culture, gender, and organizations and institutions. Substantively, her research has examined processes around the formation of collective identities and social movement strategy in feminist and environmental movements, continuities between cycles of activism and the role of place in shaping social movement activity, intersectionality in women's movements and in the lived experiences during the 19th century in the U.S. South, gender inequality in startups and entrepreneurship, the translation of academic ideas to practice in the National Science Foundation's ADVANCE program (a program aimed at promoting women in STEM field in higher education), and gender inequality in emergency medicine departments. Methodologically, she has proposed frameworks to combine computational methods and machine learning with qualitative methods, including the computational grounded theory framework and leveraging the alignment between machine learning and the intersectionality research paradigm. She has developed and taught courses introducing social science and humanities students to computational methods and the scripting languages Python and R, data science courses, and graduate-level sociological theory. She is currently a co-PI on a million-dollar grant through the National Science Foundation to study the spread of gender-equity ideas related to STEM fields through higher education networks, primarily in the United States."

Abstract: Narrating history is perpetually contested, shaping and reshaping how nations and people understand both their pasts and the current moment. Measuring and evaluating the scope of histories is methodologically challenging. In this paper we provide a general approach and a specific method to measure historical recall. Operationalizing historical information as one or more word phrases, we use the phrase-mining RAKE algorithm on a collection of primary historical documents to extract first-person historical evidence, and then measure recall via phrases present on contemporary Wikipedia, taken to represent a publicly-accessible summary of existing knowledge on virtually any historical topic. We demonstrate this method using women’smovements in the United States as a case study of a debated historical field. We found that issues important to working-class elements of the movement were less likely to be covered on Wikipedia compared to other subsections of the movement. Combining this method with a qualitative analysis of select articles, we identified a typology of mechanisms leading to historical omissions: paucity, restrictive paradigms, and categorical narrowness. Our approach, we conclude, can be used to both evaluate the recall of a body of history and to actively intervene in enlarging the scope of our histories and historical knowledge.
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