Working Papers

How do scientists cope with experimental failures? (with John P. Walsh)

How do scientists address failures when producing experimental data? While the social dynamics of failures at the epistemological level – such as questioning or defending well-established experiments and theories upon failures – are well examined, how scientists engage with difficulties in producing experimental data at day-to-day bench work has been less understood. Moreover, such failures from mundane bench work can precede the much-studied epistemological interplays involving evaluation and readjustment of theories and hypotheses. We explore these “low-level data generation” processes based on ethnographic observations from material science labs to understand the work of scientists addressing failures in data production. Analyzing these failures provides a strategic site for the sociology of science as it not only addresses potential bottlenecks in production of science but also reveals problem-solving processes, skills, and the interplay between epistemological and material dimensions and the degree to which the knowledge is situated. We find that scientists’ situational knowledge of empirical data production work is essential in identifying and searching for causes and solutions to failures. Secondly, due to the situated nature of data production, we find that necessary information for addressing these failures is primarily communicated and shared among lab members who are engaged in similar tasks. Thirdly, despite the aforementioned benefit of knowledge spillover, we find that much of the failure-coping process is carried out in isolation, both physically and cognitively. Lastly, our findings reveal an interesting aspect of how scientists attribute causes to failures. Scientists tend to internalize failures initially, blaming themselves before attributing these failures to external factors. Based on our in-depth observations and conceptualizations, we introduce the “Cycle of Doubt,” a model that generalizes the failure-coping process. We provide a detailed discussion of the theoretical and practical implications of our findings. Download Paper

Gender and Attrition in the Changing Organization of Scientific Work (with You-na Lee)

Despite longstanding concerns about the under-representation of women in science, few studies have approached this issue from the perspective of the changing organization of work in science. Past studies have documented a trend toward increased bureaucratization of scientific work, marked by the growing number of scientists specialized in supporting roles. Using data on publishing careers of scientists from 1951 to 2012 from selected natural and social science fields, we show that these “supporting” career-type scientists have been traditionally associated with women. While we find that the gender difference in career types has converged over the past few decades, this convergence has been largely driven by an increasing share of male scientists taking on supporting roles. We also find that historical gender inequality in career attrition in science is largely attributable to women traditionally occupying “supporting” roles, which suggests that examining work organization is crucial for understanding gender inequality in science. Lastly, using survival analysis, we find that both female “lead” and “supporting” career types face higher attrition rates than their male counterparts. Meanwhile, we find that “lead” career types yield fewer advantages for women compared to men in natural sciences, whereas “supporting” career types are particularly disadvantageous for women in social sciences. Our findings provide science policymakers with insights necessary to tailor support for women scientists by considering the nuances of their career types. Download Paper