Different Politics, Different Realities? A Case Study of Students’ Partisan Sensemaking About COVID-19
The COVID-19 pandemic has been a source of conflict between liberals and conservatives in the U.S., with many politicized debates focusing on college students and universities. To understand this partisan conflict and how it might be mitigated, one useful approach is to examine how collective sense making about the virus and virus response, as reflected in language use, has differed between different political groups. Using semantic network analysis of a corpus of college students’ descriptions of their worries about COVID-19, we found that there were many similarities in sense making across the political spectrum, but also important differences between ideological groups. In particular, collective sensemaking for conservative students (more so than for liberal and moderate students) was organized around words related to anxiety and close personal relationships. These results have implications for addressing partisan inter group conflict about COVID-19.
Interdisciplinary Collaborations in Academia: Modeling the Roles of Perceived Contextual Norms and Motivation to Collaborate
In this manuscript, we provide a step toward understanding how interdisciplinary collaborations form within academic contexts. Specifically, we propose a model in which the effect of organizational norms on collaborative outcomes are mediated by departmental norms and motivation, sequentially.
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