Academic Status Hierarchies
U.S. Academia is characterized by deep status hierarchies. I investigate these inequalities in several contexts.
In the first, I demonstrate that cultural and stratifying mechanisms underlying faculty hiring contribute both to the consolidation of status hierarchies in academia.
Conceptualizing the exchange of PhDs as a form of deferential interaction between departments, I created a network dataset of inter-departmental hiring relations, faculty ranks and gender, as well as departmental specializations in sociology. In a paper published at Social Networks I draw on cutting-edge statistical network models to show that departments that share prestigious specializations, which I conceptualize as Weberian ‘lifestyles,’ are more likely to hire from one another leading to the reproduction of cultural distance between high- and low-ranked programs.
In another paper (under review), I show that the process of the social construction of rankings entails its own logics of stratification such that evaluations tend to be more unequal than faculty exchange relationships. The implication is that the sheer creation of formal rankings exacerbates status hierarchies.
In a third paper published in Social Networks, I investigate a citation network in an emerging research area. Using bipartite exponential random graph models, I show that uncertainty and centralized influence typical of an emerging area of research leads to the creation of a densely interconnecting core that acts to cohere the network. Moreover, eclecticism and innovativeness, also characteristic of a developing area, lead to a diffusely connected structure. The data, comprising 2200 authors and 76 papers have been manually coded from articles on the feminization of the labor force in Asia.
I am collaborating with Randall Ellis and other colleagues to BU to investigate the effects of race and gender homophily in collaboration in the field of economics on inequalities including hiring, tenure, and promotion. We are also implementing an intervention to test if exposure to information on such inequalities generates long-term changes in co-authorship, hiring, and tenure outcomes for women and racial minorities.