Court restructuring has become a salient national political issue, with proposals to increase the number of justices on the US Supreme Court gaining traction in response to various Court controversies. However, relatively little attention has been paid to state-level efforts, some successful, to increase the number of justices on state supreme courts. Although the number of justices on the US Supreme Court has not been changed since 1869, the size of most state supreme courts has been less stable. To place recent state supreme court expansions into context, this article analyzes the historical dynamics of state supreme court expansion. Analyzing an original dataset that includes every change made to the size of a state supreme court since 1789, it finds that court expansion has been more likely when the political competitiveness of a state is low and when state judicial selection and retention systems provide for lower levels of judicial independence.

In this research, we update the measure of case salience for state supreme courts originally developed by Vining and Wilhelm (2011). The original measure was compatible with the Brace-Hall State Supreme Court Data Project (SSCDP) and covered 1995 through 1998. Our updated measure is now compatible with the Hall–Windett Data on State Supreme Court Outcomes (2013), a more contemporary source for state supreme court information. Here we discuss the new dataset of salient cases from 1995 to 2019 and provide descriptive statistics.

Many studies of policy diffusion focus on what factors affect a policy’s adoption. Few studies specifically test the mechanism and two of the most common explanations – learning and emulation – have not been tested outside of legislatures. While judicial scholars have applied policy diffusion to several types of laws, we know little about the motivation behind why policies spread from court to court. One unexplored area is the relationship between courts. This short article analyzes the two mechanisms most likely to affect peer institutions: learning and emulation. Using network analysis methods on an original dataset of state supreme court citations from 1960 to 2010, I provide evidence that courts are learning from and not emulating each other, but the mechanism is policy-specific.

The examination of the interaction between the institutions in American state politics has long suffered from a dearth of data. This is the case despite the importance of understanding the separation of powers in the states and the specific effects on policy making and policy outcomes. In this article, I introduce a new, original dataset of court-curbing introductions by state legislators. The data include information on more than 1,200 state legislative bills that would restrict the power of the courts. In this article, I provide descriptive statistics for the data, employ the data to test hypotheses, and explain how this data may be used in future scholarly research on the interactions between state legislators and state courts.

The state courts of last resort are vital components of American judicial system, disposing of many important legal matters. The chief justices of these courts serve consequential roles in these institutions. Although scholars have examined the selection and duties of states' chief justices, their interactions with the elected branches are understudied. We focus on how chief justices on state high courts use their roles to encourage judicial reform. Specifically, we examine the determinants of chief justices' successes or failures as advocates for their justice systems. To analyze why chief justices succeed or fail as reform advocates, we analyze the fate of reform proposals offered in state of the judiciary addresses. Our results indicate that greater ideological similarity between the state legislature and chief justice or state supreme court median increases the odds of an agenda item being enacted. We also find that the scope of a policy request influences the likelihood it will be granted.