As IG scholarship continues to flourish, scholars increasingly explore the use of the IG in measuring concepts linked to various models, theories, and frameworks, often drawing on the assessment of features of institutional design. Researchers are continuing to explore the IG-based measurement of such concepts, relative to extant approaches. They are additionally exploring whether IG-based conceptual measurement supports, advances, or otherwise modifies understanding of phenomena that specific models, theories, and frameworks are designed to address. In doing so, such work is intended to support the development and testing of existing and novel models, theories, and frameworks that can be applied to evaluate the governance of social systems. Researchers in this theme often draw on approaches and methods that cut across different disciplines. Some are particularly interested in using the IG for the study of institutional diversity, both within and across cases. Comparative assessments of institutional diversity further enable the testing and development of models, theories, and frameworks used to understand governance.

Behavioral scientists are increasingly using the IG to connect analyses of institutions-in-form with institutions-in-use. This theme draws insights into the nature of institutions in behavioral settings; it works toward establishing a rich empirical basis of the processes by which institutions emerge, change, and evolve, as well as their interplay with institutions-in-form. 

Behavioral IG studies methodologically target physical, digital, and artificial and engineered social systems. They explore institutional arrangements, their emergence, and their underlying dynamics, usually by means of surveys and questionnaires, experimental settings, or more generative methods (e.g., simulating artificial societies). Where the former emphasize the understanding and explanation of institutional phenomena in real world settings, the latter enable alternative methods to perform feasibility, or to test theory and hypotheses whose exploration might otherwise be challenging (e.g., on economic grounds) or prohibitive (e.g., on ethical grounds). 

This theme aims to develop a cognitive infrastructure capable of representing complex processes necessary to study institutions. Contemporary behavioral studies use a range of approaches rooted in different disciplinary traditions (e.g., ethnographic research, utilitarian models). The development of this cognitive infrastructure aims to support social behavioral researchers in leveraging new opportunities to study and analyze institutions (e.g., by affording disciplinary integration).

There remains little to no information on the current institutional design and structure of most governance instruments. This theme addresses institutional analyses that (1) are comparative/non-comparative and/or (2) assess single/meta case studies exploring institutional performance issues–such as coding and comparing the structure of institutions to determine which institutional characteristics may foster or hinder the interplay among rules-in-form and rules-in-use (e.g., exploring the relationship among institutional design, implementation/operationalization, conformance, and desired outcomes of key policies). 

Research under this theme also explores institutional performance within institutions over time to better understand how social and environmental change may motivate institutional change and performance.

Researchers aim to develop a library of open-access coded policies and legislation, along with policy briefs that are useful to researchers and practitioners interested in policy performance, implementation, and design.

While application of the IG has increased significantly in the past decade, its broader application and usefulness may be improved through the development of rigorous qualitative, quantitative, experimental, computational, mixed, and other methods aimed at answering particular research questions. This theme works to advance the knowledge and application of methods designed to better analyze IG-coded data. Researchers working under this theme are interested in showcasing novel methodological approaches, augmenting existing approaches, or developing IG guidelines for the coding of formal institutions sourced from policy documents or informal institutions (e.g., taken from surveys, interviews, and other sources).

Complementing methodological efforts, this theme aims to automate the IG research process, both at specific stages and the entire process itself. These aspects include the collection or generation of data, their pre-processing, the facilitation of their analysis, and the interpretation of outcomes based on computational approaches. Efforts in this area variably focus on (1) supporting specific methodological and disciplinary pathways (e.g., automated statistical processing, computational models), (2) improving existing/creating novel technology more broadly applicable to IG studies (e.g., machine learning, natural language processing), or (3) developing purpose-built software and technological infrastructure that supports the research process (e.g., IG data management, high-performance processing for large-scale analyses). This theme especially applies to scholars and practitioners with technological backgrounds or interest therein.