ABSTRACT
This chapter focuses on learning. It creates three experiments with student, adult, and Amazon's Mechanical Turk samples to test how Google searches affect learning about ballot measures. The chapter shows that Google access and research positively affect learning about ballot measures in American politics. For the charter school amendment, the results indicate difficulty of learning about ballot measures. Ballot measures are typically low salience, and they use obscure language. The salient nature of our ballot measures may have created conditions in which public generally had high levels of knowledge, which could obscure significant differences between treatment and control groups. The ballot measure in question was a "transportation special purpose local option sales tax" (T-SPLOST) referendum. For minimum wage ballot measure, screenshots subjects submitted make it clear that many subjects were logged into Google and thus were not only allowing cookies but also information from their various Google accounts such as Maps, Drive, and Plus.
