Examining Priming in State Legislative Elections

Meyer-Gutbrod Joshua L, Goleta CA

Investigators

Abstract

This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program and supported by SBE's Political Science program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Bruce Bimber at the University of California, Santa Barbara this postdoctoral fellowship award supports an early career scientist investigating the role of implicit and explicit racial priming within American state legislative campaigns. Both conservative and liberal social movements have increasingly integrated race-based identity claims into their agendas. While existing literature has examined the impact of racial rhetoric within national politics, little work has been done to assess the impact on state politics. This project will explore how this growing racial divide has impacted policy conversation within the American States by developing an expansive data set that catalogues state legislative campaign content by issue arena and rhetorical frame. In doing so, this project aims to inform efforts to counteract racial rhetorical frames and improve democratic engagement for all citizens. This dataset will also provide a critical data source for developing projects for future research on state politics, public policy, political campaigns, and race. Finally, by processing campaign statements into issue coverage summaries for state legislative matchups, this project aims to provide accessible information to better inform voters in lower information elections of a candidate's willingness to engage with salient issues. In order to fully investigate racial rhetoric, this project will employ web-scraping techniques to preserve state legislative candidate campaign websites from 2014-2018. Websites provide a holistic approach to the analysis of campaign rhetoric as candidates possess extensive control over the content of a website while space and costs issues are at a minimum. A random sample of candidate issue statements and self-reported legislative records will be catalogued and coded by trained coders according to issue arena and content. This will provide a critical training dataset that will be used to classify the remaining statements according to issue arena using machine learning classification algorithms. The final dataset will provide an unprecedented account of state legislative campaign rhetoric by providing: 1) Character-counts that measure dedicated issue space by topic and provide a critical metric for issue salience and priming; 2) A comprehensive list of issue statements relevant to a particular policy arena that will be used to examine statements for implicit and explicit racially driven framing; 3) A complete collection of website images that provide evidence for visual priming. This data will provide evidence for variation in issue selection as a product of candidate qualities and constituent demographics, specifically racial heterogeneity of district constituents and neighboring districts. In addition, specific policy arenas, including welfare/public assistance, criminal justice, and immigration, can be examined for variation in implicit and explicit racial rhetoric across states and districts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.