Servants of two (or more) masters: Accounting for the complexity of intraparty candidate selection methods

Intraparty candidate selection methods are the drivers of many topics of interest to political scientists. Their operationalization, however, is made complicated because they tend to involve multiple selectorates that differ in their levels of inclusiveness and centralization and that play various roles within the process. This complexity poses a challenge for large-n comparative studies. Drawing on the Political Parties DataBase Round Two to analyze candidate selection methods in 184 parties from 35 democracies, we highlight the inadequacy of the currently available measures to correctly account for this complexity in large-n studies and offer improvements on this front. Specifically, we propose a continuous measure of inclusiveness that better captures the complexity of candidate selection methods and a new measure of complexity to facilitate future analyses into this feature. We recommend that scholars in other cross-national projects consider adopting similar or improved coding strategies in order to better capture these complexities.