Replication Data for: Improving Content Analysis: Tools for Working with Undergraduate Research Assistants

Undergraduate research assistants (URAs) play an important role in many political scientists’ research projects. They serve as co-authors, survey respondents, and data collectors. Despite this, there is relatively little discussion about how best to train and manage URAs working on a common task: content coding. Drawing on insights from psychology, text analysis, and business management, as well as my own experience managing a team of nine URAs, I argue that supervisors ought to train URAs by pushing them to engage with their own mistakes. Via a series of simulation exercises, I also argue that supervisors—especially supervisors of small teams—should be concerned about the effects of errant post-training coding on data quality. As such, I contend that supervisors ought to utilize computational tools to monitor URA reliability in real time. I provide researchers with a new R package, ura, and a web-based application to implement these suggestions.