Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty.

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

Disparate foundations of scientists' policy positions on contentious biomedical research.

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 differential effect of college on political orientation over the last 40 years in the U.S.-A propensity score weighting approach.

It is well-known that the more educated people are, the more liberal views they tend to express. However, it is unclear whether this is due to college attendance itself or because those who go to college differ from those who do not in ways (directly or indirectly) related to their later political identification. In this paper, we therefore attempt to estimate the effect of college on political identification net of people's tendencies to select into college using an inverse probability of treatment weighting approach. Based on data from the General Social Survey, we analyze how this effect has changed over time and whether college affects the political identification of women in the same ways as that of men. We find evidence consistent with the argument that college attendance politicizes both men and women. Moreover, we show that not only the general, but also the gender specific effects change markedly across the decades. This raises questions about the different mechanisms at play in how college mobilizes men and women politically.

Computational Social Science and Sociology.

The integration of social science with computer science and engineering fields has produced a new area of study: computational social science. This field applies computational methods to novel sources of digital data such as social media, administrative records, and historical archives to develop theories of human behavior. We review the evolution of this field within sociology via bibliometric analysis and in-depth analysis of the following subfields where this new work is appearing most rapidly: (a) social network analysis and group formation; (b) collective behavior and political sociology; (c) the sociology of knowledge; (d) cultural sociology, social psychology, and emotions; (e) the production of culture; (f) economic sociology and organizations; and (g) demography and population studies. Our review reveals that sociologists are not only at the center of cutting-edge research that addresses longstanding questions about human behavior but also developing new lines of inquiry about digital spaces as well. We conclude by discussing challenging new obstacles in the field, calling for increased attention to sociological theory, and identifying new areas where computational social science might be further integrated into mainstream sociology.

Boundary violations and adolescent drinking: Observational evidence that symbolic boundaries moderate social influence.

Scholars of social influence can benefit from attending to symbolic boundaries. A common and influential way to understand symbolic boundaries is as widely shared understandings of what types of behaviors, tastes, and opinions are appropriate for different kinds of people. Scholars following this understanding have mostly focused on how people judge others and how symbolic boundaries align with and thus reproduce social differences. Although this work has been impressive, I argue that it might miss important ways in which symbolic boundaries become effective in everyday social life. I therefore develop an understanding of how symbolic boundaries affect people's ideas and decisions about themselves and their own behavior. Based on this, I argue that focusing on boundary violations-that is, what happens if people express opinions or enact behavior that contravenes what is considered (in)appropriate for people like them-might offer an important way to understand how symbolic boundaries initiate and shape cultural and social change. Using data from Add Health, I demonstrate the utility of this line of argument and show that boundary violations play an important role in channeling social influence. Conservative/Evangelical Protestants and to a lesser degree Catholics, but not Mainline Protestants are highly influenced by the drinking of co-religionists. I consider the implications for cultural sociology.