Laura K. Nelson
Laura K. Nelson
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Updating 'The Future of Coding': Qualitative Coding with Generative Large Language Models
This article tests the ability of generative LLMs to replicate and augment traditional qualitative coding, experimenting with multiple prompt structures across four closed- and open-source generative LLMs and proposing a workflow for conducting qualitative coding with generative LLMs.
Nga Than
,
Leanne Fan
,
Tina Law
,
Laura K. Nelson
,
Leslie McCall
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From Funding Equity Initiatives to Research Productivity: Quantifying the Impact of NSF ADVANCE Awards on Recipients’ Publication Trajectories
Service work in academia, including organizational change efforts, often competes with time for research, potentially affecting academic careers (tenure, promotion, and pay) through slowed publication productivity. The authors examine changes in publication trajectories among academics participating in the National Science Foundation ADVANCE program, finding that scholars involved in ADVANCE awards published significantly more articles within the first four years after receiving funding.
Alexander J. Gates
,
Laura K. Nelson
,
Rachael Grudt
,
Kathrin Zippel
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Translating Interdisciplinary Knowledge for Gender Equity: Quantifying the Impact of NSF ADVANCE
Interdisciplinarity is often hailed as a necessity for tackling real-world challenges. We examine the prevalence and impact of interdisciplinarity in the NSF ADVANCE program, finding ADVANCE publications exhibit higher levels of interdisciplinarity across three dimensions of knowledge integration. These findings emphasize the significance of interdisciplinarity in problem-oriented knowledge production, indicating that specific forms of interdisciplinarity can lead to broader impact.
Alexander J. Gates
,
Jessica R. Gold
,
Laura K. Nelson
,
Kathrin Zippel
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Gender and Inconsistent Evaluations: A Mixed-methods Analysis of Feedback for Emergency Medicine Residents
Prior research has demonstrated that men and women emergency medicine (EM) residents receive similar numerical evaluations at the beginning of residency, but that women receive significantly lower scores than men in their final year. To better understand the emergence of this gender gap in evaluations we examined discrepancies between numerical scores and the sentiment of attached textual comments.
Alexandra Brewer
,
Laura K. Nelson
,
Anna S. Mueller
,
Rebecca Ewert
,
Daniel M. O'Connor
,
Arjun Dayal
,
Vineet M. Arora
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Taking the Time: The Implications of Workplace Assessment for Organizational Gender Inequality
This paper examines gendered differences in workplace assessment in eight U.S. hospitals, finding that, compared to men, women attendings wrote more words in their comments to residents, used more job-related terms, and were more likely to provide helpful feedback, particularly when residents were struggling, while women residents were less likely to receive substantive evaluations.
Laura K. Nelson
,
Alexandra Brewer
,
Anna S. Mueller
,
Daniel M. O'Connor
,
Arjun Dayal
,
Vineet M. Arora
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Beyond Protests: Using Computational Text Analysis to Explore a Greater Variety of Social Movement Activities
In this paper, we use the environmental movement as a case study, analyzing data from a wide range of local, regional, and national newspapers in the United States to quantify multiple facets of social movements.
Brayden G King
,
Laura K. Nelson
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Formally comparing topic models and human-generated qualitative coding of physician mothers’ experiences of workplace discrimination
Differences between computationally generated and human-generated themes in unstructured text are important to understand yet difficult to assess formally. In this study, we bridge these approaches, comparing topic models to hand-generated categories and comparing two different topic modelling solutions.
Adam S. Miner
,
Sheridan A. Stewart
,
Meghan C. Halley
,
Laura K. Nelson
,
Eleni Linos
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From Ends to Means: The Promise of Computational Text Analysis for Theoretically Driven Sociological Research
In presenting the contributions to a special issue, we discuss several insights that emerge from this work, which hold relevance not only for current and aspiring practitioners of computational text analysis, but also for its skeptics.
Bart Bonikowski
,
Laura K. Nelson
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Situated Knowledges and Partial Perspectives: A Framework for Radical Objectivity in Computational Social Science and Computational Humanities
Starting from the premise that objectivity in knowledge creation is a worthy—even utopian—pursuit, this essay argues that computational methods are aligned with embodied objectivity and the situated knowledges and partial perspectives framework proposed by Donna Haraway.
Laura K. Nelson
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The Inequality of Intersectionalities in Chicago’s First-Wave Women’s Movement
This article uses network and text analyses methods to reexamine the intersections of race, class, gender, and ethnicity in first-wave feminist organizations in Chicago during the Progressive Era, from 1860 to 1920.
Laura K. Nelson
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