Aristocracy or Meritocracy? The Role of Elite Pedigree and Research Performance in New Accounting Faculty Placements

This paper investigates the influences of elitism and merit in new accounting faculty. Building on research showing that search committees value pedigree in hiring new faculty, we theorize both aristocratic (e.g., accessing or reinforcing elite networks) and meritocratic (e.g., signaling stronger future research potential) influences on the hiring of new accounting faculty. Using curriculum vitae from 381 Accounting Ph.D. Rookie Recruiting and Research Camps, we examine whether candidates graduating from elite accounting institutions place disproportionately higher than do their non-elite peers. Results suggest that elite pedigree predicts placement rank among candidates without favorable publication outcomes at top journals (e.g. acceptance or invitation to resubmit) but not among candidates with favorable publication outcomes. The results suggest joint and complex aristocratic (elite-based) and meritocratic (productivity-based) influences in new accounting faculty hiring.

The dynamics of faculty hiring networks

Faculty hiring networks—who hires whose graduates as faculty—exhibit steep hierarchies, which can reinforce both social and epistemic inequalities in academia. Understanding the mechanisms driving these patterns would inform efforts to diversify the academy and shed new light on the role of hiring in shaping which scientific discoveries are made. Here, we investigate the degree to which structural mechanisms can explain hierarchy and other network characteristics observed in empirical faculty hiring networks. We study a family of adaptive rewiring network models, which reinforce institutional prestige within the hierarchy in five distinct ways. Each mechanism determines the probability that a new hire comes from a particular institution according to that institution’s prestige score, which is inferred from the hiring network’s existing structure. We find that structural inequalities and centrality patterns in real hiring networks are best reproduced by a mechanism of global placement power, in which a new hire is drawn from a particular institution in proportion to the number of previously drawn hires anywhere. On the other hand, network measures of biased visibility are better recapitulated by a mechanism of local placement power, in which a new hire is drawn from a particular institution in proportion to the number of its previous hires already present at the hiring institution. These contrasting results suggest that the underlying structural mechanism reinforcing hierarchies in faculty hiring networks is a mixture of global and local preference for institutional prestige. Under these dynamics, we show that each institution’s position in the hierarchy is remarkably stable, due to a dynamic competition that overwhelmingly favors more prestigious institutions. These results highlight the reinforcing effects of a prestige-based faculty hiring system, and the importance of understanding its ramifications on diversity and innovation in academia.

A Statistical Model for the Analysis of Mobility Tables as Weighted Networks with an Application to Faculty Hiring Networks

Mobility of individuals between a wide variety of geographic locations, social positions, or roles is frequently analysed in the social sciences. In recent research, mobility has increasingly been conceptualised as a network. For example, residential mobility, when individuals move between neighbourhoods of a city, can be understood as a network in which neighbourhoods are nodes that are tied by counts of mobile individuals that move from one neighbourhood to another. Understanding mobility as a network allows to apply concepts and methods from the network analyst's toolbox. However, the statistical modelling of such weighted networks in which ties can have individual attributes remains difficult. In this article we propose a statistical model for the analysis of mobility tables conceptualised as networks, combining properties from log-linear models and exponential random graph models (ERGMs). When no endogenous patterns are modelled, it reduces to a classic log-linear model for mobility tables. When modelling endogenous patterns but ignoring individual attributes, the model can be understood as an ERGM for weighted networks in which tie weights denote counts. Making use of special constraints of mobility networks, the model offers a parsimonious way to deal with weighted ties. Going beyond classical ERG modelling, the proposed approach can additionally incorporate tie characteristics that represent individual attributes of mobile people. The model is applied to two cases of faculty hiring networks---linking current departments of faculty members with their PhD granting institution---in history and computer science in the US.

Gender bias in reference letters for residency and academic medicine: a systematic review

Reference letters play an important role for both postgraduate residency applications and medical faculty hiring processes. This study seeks to characterise the ways in which gender bias may manifest in the language of reference letters in academic medicine. In particular, we conducted a systematic review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched Embase, MEDLINE and PsycINFO from database inception to July 2020 for original studies that assessed gendered language in medical reference letters for residency applications and medical faculty hiring. A total of 16 studies, involving 12 738 letters of recommendation written for 7074 applicants, were included. A total of 32% of applicants were women. There were significant differences in how women were described in reference letters. A total of 64% (7/11) studies found a significant difference in gendered adjectives between men and women. Among the 7 studies, a total of 86% (6/7) noted that women applicants were more likely to be described using communal adjectives, such as “delightful” or “compassionate”, while men applicants were more likely to be described using agentic adjectives, such as “leader” or “exceptional”. Several studies noted that reference letters for women applicants had more frequent use of doubt raisers and mentions of applicant personal life and/or physical appearance. Only one study assessed the outcome of gendered language on application success, noting a higher residency match rate for men applicants. Reference letters within medicine and medical education exhibit language discrepancies between men and women applicants, which may contribute to gender bias against women in medicine.

Methodology of the Repressed in Faculty Hiring

This essay documents forms in which repressed supremacy—with the purpose to ultimately push out and exclude people of color professors—is enacted. My endurance within toxic spaces is the result of channeling Tlazolteotl and putting my Coyolxauhqui together, referring to the act of constantly reinventing myself by turning excrement into life and rejoining the pieces of my experience. I also share a successful teaching, research, and service agenda of resistance that fulfills requirements as it is simultaneously defiant. By referring to covert acts of violence as the methodology of the repressed, my goal is to expose and promote their collective eradication.