Should We Measure Professionalism with an Index? A Note on Theory and Practice in State Legislative Professionalism Research. (September 2014)

• Record Type: Journal Article
• Authors: Bowen, Daniel C.; Greene, Zachary
• Is Part Of: State politics & policy quarterly. Volume 14:Number 3(2014:Sep.)
• Page Start: 277
• Page End: 296
• Publication Date: 2014-09
• Subjects: legislative professionalism -- legislative politics -- state legislatures -- measurement theory -- indices -- multidimensional scaling; State governments -- United States -- Periodicals; Political planning -- United States -- States -- Periodicals; Gouvernements d'États fédérés -- États-Unis -- Périodiques; Politique publique -- États-Unis -- États -- Périodiques; 320.97305
• DOI: 10.1177/1532440014536407
• Languages: English
• ISSNs: 1532-4400

Abstract

Abstract: Legislative professionalism has played a prominent role in state politics research for decades. Despite the attention paid to its causes and consequences, recent research has largely set aside questions about professionalism's conceptualization and operationalization. Usually measuring it as an aggregate index, scholars theoretically and empirically treat professionalism as a unidimensional concept. In this article, we argue that exclusive use of aggregate indices can limit state politics research. Using a new dataset with almost 40 years of data on state legislative resources, salary, and session length, we reconsider the validity of using an index to study professionalism across the states. We evaluate the internal consistency of professionalism components over time, the relationship between components and the Squire Index, and the degree to which professionalism components are unidimensional using classical multidimensional scaling. We find enough commonality and enough variation between professionalism components to support a range of measurement strategies like the use of unidimensional indices (such as the Squire Index), disaggregating the components and analyzing their effects individually, or formulating multidimensional measures. Scholars should take care to choose the appropriate measure of the concept that best fits the causal relationships under examination.