Most people usually think of emotion as a subjective feeling of a certain kind, the kind for which labels like happy, sad, and frightened are appropriate. However, there is much evidence to suggest that this is too narrow a way to define emotions, and that a different and broader conceptualization is needed. If we examine the history of theories of emotion we find a great diversity of views. For example, Darwin, in his 1872 book ‘The Expression of the Emotions in Man and Animals’, conceived of emotions as expressive behaviors that had the function of communicating intentions from one animal to another in the presence of conflicts or emergencies. Emotional expressions, from this point of view, regulated interpersonal relations and increased the chances of individual survival.

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.