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This article explores the contingent role that social ties play in the emergence of status hierarchies. We argue that, while status is formed based on actors’ perception and understanding of social cues, network structure, and position influence this process by influencing the attention and legitimacy given to the focal actor in accordance with social cues that signal an actor’s identity. Using a large data set from an open-source software development community, we find that a broker linking diverse network members is less likely to receive status ratings from others and that the rating is more likely to be low when a broker receives a rating. Furthermore, we find evidence that the effects of brokerage are contingent upon certain factors that may affect the attention and legitimacy given to actors in the process of status evaluation, such as the actor’s prior status. An actor’s prior status was found to weaken the negative effect of brokerage. The importance of this study for theories of status, social networks, and attention is discussed.

The COVID-19 pandemic stressed the health care sector's longstanding pain points, including the poor quality of frontline work and the staffing challenges that result from it. This has renewed interest in technology-centered approaches to achieving not only the “Triple Aim” of reducing costs while raising access and quality but also the “Quadruple Aim” of doing so without further squeezing wages and abrading job quality for frontline workers.

How can we leverage technology toward the achievement of the Quadruple Aim? I view this as a “grand challenge” for health care managers and policymakers. Those looking for guidance will find that most analyses of the workforce impact of technological change consider broad classes of technology such as computers or robots outside of any particular industry context. Further, they typically predict changes in work or labor market outcomes will come about at some ill-defined point in the medium to long run. This decontextualization and detemporization proves markedly problematic in the health care sector: the nonmarket, institutional factors driving technology adoption and implementation loom especially large in frontline care delivery, and managers and policymakers understandably must consider a well-defined, near-term, i.e., 5–10-year, time horizon.

This study is predicated on interviews with hospital and home health agency administrators, union representatives, health care information technology (IT) experts and consultants, and technology developers. I detail the near-term drivers and anticipated workforce impact of technological changes in frontline care delivery. With my emergent prescriptions for managers and policymakers, I hope to guide sectoral actors in using technology to address the “grand challenge” inherent to achieving the Quadruple Aim.