Ryan Light

Racial Discrimination, Interpretation, and Legitimation at Work

Research on race stratification and employment usually implies discrimination as a key mechanism in race stratification, although few if any analyses bring attitudes, employee-employer interpretations, and established discriminatory behavior into a singular analysis. In this article, the authors do so and offer a relational account of how discrimination operates, drawing on a large sample of verified racial discrimination cases. Building on racial stratification literature and theory on “color-blind” racism, the analyses focus on employee and employer interpretations and then use dyadic analyses coupled with qualitative case immersion to shed light on the relational nature of discrimination and how employers justify such conduct. Findings highlight significant interpersonal disjunctures in descriptions of common events as well as the ways in which employers evoke broad organizational and societal ideals of meritocracy— ideals that often fall by the wayside in concrete decision-making pertaining to and in evaluation of minority employees.

From Words to Networks and Back: Digital Text, Computational Social Science, and the Case of Presidential Inaugural Addresses

Digital text has revolutionized how we consume and produce information, and also provides seemingly limitless sources of data from Twitter feeds to online historical archives. Such new data challenge traditional boundaries between quantitative and qualitative research, and exciting horizons have emerged. New analytic approaches are warranted, however, given the typically unstructured, respondent-generated format of such data. In this article, I examine how sociologists have handled text data prior to digitization. Building on recent advancements in computational linguistics and computational social science, I then offer a network-based model and approach for analyzing similarities and locating emergent, general themes in digitized text. I provide a case in point by analyzing the United States’ presidential inaugural addresses. This analysis illustrates how sociologists can take advantage of both the breadth of new digital sources of data and the richness that such qualitative material provides. Indeed, the digitization of texts represents a possible and stimulating sea change in how we tell socio-cultural and historical stories. The greatest potential in these regards rests at the nexus of new computational methods and in-depth, qualitative strategies.

Mapping interdisciplinary fields: efficiencies, gaps and redundancies in HIV/AIDS research.

While interdisciplinarity continues to increase in popularity among funders and other scientific organizations, its potential to promote scientific advances remains under-examined. For HIV/AIDS research, we examine the dynamics of disciplinary integration (or lack thereof) providing insight into a fields knowledge base and those questions that remain unresolved. Drawing on the complete histories of two interdisciplinary journals, we construct bibliographic coupling networks based on overlapping citations to identify segregation into research clusters and estimate topic models of research content. We then compare how readily those bibliographic coupling clusters account for the structuring of topics covered within the field as it evolves over two decades. These comparisons challenge one-dimensional and/or cross-sectional approaches to interdisciplinarity. Some topics are increasingly coordinated across disciplinary boundaries (e.g., vaccine development); others remain relatively segmented into disconnected disciplinary domains for the full period (e.g., drug resistance). This divergence indicates heterogeneity in interdisciplinarity and emphasizes the need for critical approaches to studying the organization of science.

Knowledge in motion: the evolution of HIV/AIDS research

Many contemporary social and public health problems do not fit neatly into the research fields typically found in universities. With this in mind, researchers and funding agencies have devoted increasing attention to projects that span multiple disciplines. However, comparatively little attention has been paid to how these projects evolve over time. This relative neglect is in part attributable to a lack of theory on the dynamic nature of such projects. In this paper, we describe how research programs can move through various states of integration including disciplinarity, multidisciplinarity, interdisciplinarity and transdisciplinarity. We link this insight to computational techniques—topic models—to explore one of the most vibrant and pressing contemporary research areas—research on HIV/AIDS. Topic models of over 9000 abstracts from two prominent journals illustrate how research on HIV/AIDS has evolved from a high to a lower level of integration. The topic models motivate a more detailed historical analysis of HIV/AIDS research and, together, they highlight the dynamic nature of knowledge production. We conclude by discussing the role of computational social science in dynamic models of interdisciplinarity.

Disparate foundations of scientists’ policy positions on contentious biomedical research

Significance What drives scientists’ public support for contentious policy issues? We examined associations between peer exposure and academic specialization on public declarations about research involving potentially pandemic pathogens. Although we found significant peer associations for everyone, they are strongest among the opposition. Conversely, specializing in fields directly related to gain-of-function research predicts support better than specializing in fields related to epidemic risks predicts opposition. These findings suggest that different social processes, rooted in differing social networks and expertise, underlie support or opposition. Identifying the sources of policy support might help parties better understand the different, but legitimate, foundations of each other’s positions, providing additional information to inform decision making and thereby help to maintain science’s role as an objective arbiter for policy. What drives scientists’ position taking on matters where empirical answers are unavailable or contradictory? We examined the contentious debate on whether to limit experiments involving the creation of potentially pandemic pathogens. Hundreds of scientists, including Nobel laureates, have signed petitions on the debate, providing unique insights into how scientists take a public stand on important scientific policies. Using 19,257 papers published by participants, we reconstructed their collaboration networks and research specializations. Although we found significant peer associations overall, those opposing “gain-of-function” research are more sensitive to peers than are proponents. Conversely, specializing in fields directly related to gain-of-function research (immunology, virology) predicts public support better than specializing in fields related to potential pathogenic risks (such as public health) predicts opposition. These findings suggest that different social processes might drive support compared with opposition. Supporters are embedded in a tight-knit scholarly community that is likely both more familiar with and trusting of the relevant risk mitigation practices. Opponents, on the other hand, are embedded in a looser federation of widely varying academic specializations with cognate knowledge of disease and epidemics that seems to draw more heavily on peers. Understanding how scientists’ social embeddedness shapes the policy actions they take is important for helping sides interpret each other’s position accurately, avoiding echo-chamber effects, and protecting the role of scientific expertise in social policy.

Gender Inequality and the Structure of Occupational Identity: The Case of Elite Sociological Publication

Purpose – While important changes have been made in the American workplace, gender inequality persists. Contemporary analyses of occupational segregation suggest that gendered roles and identities may be playing a role, yet few studies explicitly tackle the effects of occupational identity on female disadvantage at work. Moreover, most previous research ignores the structured, multidimensionality of occupational identity focusing on more overt one-dimensional forms of status differentiation. Using sociological work as a case, these analyses delineate how occupational identities contribute to and differentiate publication success – and thus status hierarchies – for men and women in the sociological field.Findings – Net of human capital, results demonstrate the pronounced effect of the structure of occupational identity on publication: An often hidden form of job-queuing, occupational identities are gendered and influence the publication process. Differential rewards based on subtly gendered distinctions prove an important source of persistent inequalities.Social implications – While gender alone may not directly influence publication in premier research journals for more recent cohorts of sociologists, the gendered nature of research specialization and the distribution of rewards based, in part, on specialization present a troubling, more subtle stratifying mechanism.Originality/value of the chapter – This chapter contributes to our understanding of the puzzling pertinence of gender inequality in the academy by pinpointing how the organization of research into specialties is gendered and how this gendering of research affects important outcomes, such as publication. The paper also contributes to our broader understanding of inequality at work as an example of how occupational identity is multidimensional and networked.

Like Strangers We Trust: Identity and Generic Affiliation Networks

Sociological research on collective behavior provides strong evidence for the sources of collective action and shared attitudes based on overlapping experience. We know, for example, that members of social movement organizations are likely to share similar beliefs. However, a significant portion of the prior research on shared behaviors or attitudes analyzes individuals who do not know one another. This research using large surveys often infers overlapping experience based on generic connections: People in unions generally or church groups generally are likely to hold similar beliefs or engage in similar behaviors as if they were in the same unions or church groups. In this paper, I challenge this simple inference by arguing that the generic affiliations we hold contribute to our identity. Specifically, our identities can, in part, be seen as a network of overlapping roles based on generic affiliations. Findings indicate the importance of considering generic affiliation networks when modeling trust and political partisanship. Individuals who share multiple affiliations often appear to be similar to one another along a number of socio-demographic dimensions and report similar attitudes. Conclusions highlight the promise and challenge of relational approaches to social life.