Televised Exposure to Politics: New Measures for a Fragmented Media Environment

For many research purposes, scholars need reliable and valid survey measures of the extent to which people have been exposed to various kinds of political content in mass media. Nonetheless, good measures of media exposure, and of exposure to political television in particular, have proven elusive. Increasingly fragmented audiences for political television have only made this problem more severe. To address these concerns, we propose a new way of measuring exposure to political television and evaluate its reliability and predictive validity using three waves of nationally representative panel data collected during the 2008 presidential campaign. We find that people can reliably report the specific television programs they watch regularly, and that these measures predict change over time in knowledge of candidate issue positions, a much higher standard of predictive validity than any other measure has met to date.     

The Power Dynamics of Mandated Network Administrative Organizations

In understanding what drives the development of network administrative organizations (NAOs) in mandated networks, power bargaining is central. The authors execute a comparative longitudinal case study of NAOs in two policy‐mandated networks. The article focuses specifically on the role of power in these developments and concludes that differences in NAO development arise from power dependencies, which are attributable in part to sector characteristics. It is proposed that mandated network members’ greater interdependence and greater dependence on external nonmembers, as well as whole network dependence on external actors, partly determine mandated networks’ NAO design. These networks will have larger and more capable NAOs (with more staff), accept sharing control of the NAO executive with the mandating party, and have broader responsibilities.     

Connections Matter: How Interactive Peers Affect Students in Online College Courses

Peers affect individual's productivity in the workforce, in education, and in other team‐based tasks. Using large‐scale language data from an online college course, we measure the impacts of peer interactions on student learning outcomes and persistence. In our setting, students are quasi‐randomly assigned to peers, and as such, we are able to overcome selection biases stemming from endogenous peer grouping. We also mitigate reflection bias by utilizing rich student interaction data. We find that females and older students are more likely to engage in student interactions. Students are also more likely to interact with peers of the same gender and with peers from roughly the same geographic region. For students who are relatively less likely to be engaged in online discussion, exposure to more interactive peers increases their probabilities of passing the course, improves their grade in the course, and increases their likelihood of enrolling in the following academic term. This study demonstrates how the use of large‐scale, text‐based data can provide insights into students’ learning processes.