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Since Crawford and Ostrom proposed the Institutional Grammar (IG), a conceptual tool for breaking down and organizing institutional statements, a burgeoning literature has used it to study institutions contained in single documents and to conduct comparative institutional analysis across multiple countries and time periods. Moreover, rapid advances in text analysis and computational methods are creating new analytic opportunities to study rules, norms and strategies by leveraging the IG syntax. At this stage, it is important to assess the existing literature to understand how the IG has supported institutional analysis across a variety of contexts, including commons governance. Based on a corpus of 48 empirical articles published between 2010 and 2021, we explore how analysts have operationalized institutional statements using the IG. We also synthesize the IG-based metrics and theoretical concepts developed in these articles to illustrate the contributions of IG for measurement of challenging concepts such as polycentricity, discretion, and compliance, among others. Our findings indicate that the IG is a flexible and adaptable tool for institutional analysis, especially for making empirical contributions from text-based data, and it holds promise toward building a potentially new emerging subfield we call Computational Institutional Analysis.
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The Institutional Grammar: A Method for Coding Institutions and its Potential for Advancing Third Sector Research
Institutions—defined as strategies, norms and rules (Ostrom Understanding institutional diversity, Princeton University Press, Princeton, 2005)—are omnipresent in third sector contexts. In this paper, we present the Institutional Grammar (IG) as a theoretically informed approach to support institutional analysis in third sector research. More specifically, the IG coding syntax allows the researcher to systematically wade through rich text and (transcribed) spoken language to identify and dissect institutional statements into finer syntactical segments of interest to the researcher. It is a versatile method that can generate data for small- or large-N research projects and can be integrated with mixed-method research designs. After first introducing and describing the IG, we present a case study to illustrate how a IG-based syntactic analysis can be leveraged to inform third sector research. In the case, we ask: Do the rules embedded in regulatory text addressing the involuntary dissolution of charity organizations differ between bifurcated and unitary jurisdictions in the United States? Using IG’s ABDICO 2.0 syntax, we identify eleven “Activation Condition” (AC) categories that trigger action and assess variation among the 46 jurisdictions. We ultimately conclude that the rules do not differ between bifurcated and unitary jurisdictions, but that finding is not the primary concern. The case demonstrates IG as an important methodological advance that yields granular, structured analyses of rules, norms and strategies in third sector settings that may be difficult to identify with other methods. We then emphasize four areas of third sector research that could benefit from the addition of IG-based methods: analysis of (1) rule compliance, (2) inter-organizational collaboration, (3) comparative study of institutional design, and (4) the study of institutional change. We close the paper with some reflections on where IG-based analysis is headed.
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- Award ID(s):
- 2020900
- PAR ID:
- 10351333
- Date Published:
- Journal Name:
- Voluntas
- ISSN:
- 1573-7888
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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The Institutional Grammar (IG) is used to analyze the syntactic structure of statements constituting institutions (e.g., public policy and social norms) that indicate behavioral constraints. Significant progress has been made in methodologically developing the IG in recent years. Scholars have offered increasingly clear guidelines for IG-based coding, identified unique considerations for applying the IG to different types of institutions, and even expanded its syntactic scope. However, while validated as a robust institutional analysis approach, the resource and time commitment associated with its application has precipitated concerns over whether the IG might ever enjoy widespread use. Needed now in the methodological development of the IG are reliable and accessible (i.e., open source) approaches that reduce the costs associated with its application. We propose an automated approach leveraging computational text analysis and natural language processing. We then present results from an evaluation in the context of food system regulations.more » « less
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Abstract The Institutional Grammar (IG) is used to analyse the syntactic structure of statements constituting institutions (e.g., policies, regulations, and norms) that indicate behavioural constraints and parameterize features of institutionally governed domains. Policy and administration scholars have made considerable progress in methodologically developing the IG, offering increasingly clear guidelines for IG‐based coding, identifying unique considerations for applying the IG to different types of institutions, and expanding its syntactic scope. However, while validated as a robust institutional analysis approach, the resource and time commitment associated with its application has precipitated concerns over whether the IG might ever enjoy widespread use. Needed now in the methodological development of the IG are reliable and accessible (i.e., open source) approaches that reduce the costs associated with its application. We propose an automated approach leveraging computational text analysis and natural language processing. We then present results from an evaluation in the context of food system regulations.more » « less
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Abstract The Institutional Grammar (IG) is a rigorous tool for analyzing the laws and policies governing nonprofit organizations; however, its use was limited due to the time-consuming nature of hand-coding. We introduce an advance in Natural Language Processing using a semantic role labeling (SRL) classifier that reliably codes rules governing and guiding nonprofit organizations. This paper provides guidance for how to hand-code using the IG, preprocess text for machine learning, and demonstrates the SRL classifier for automated IG coding. We then compare the hand-coding to the SRL coding to demonstrate its accuracy. The advances in machine learning now make it feasible to utilize the IG for nonprofit research questions focused on inter-organizational collaborations, government contracts, federated nonprofit organizational compliance, and nonprofit governance, among others. An added benefit is that the IG is adaptable for different languages, thus enabling cross-national comparative research. By providing examples throughout the paper, we demonstrate how to use the IG and the SRL classifier to address research questions of interest to nonprofit scholars.more » « less
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Abstract Over the last decade, there has been increased interest in understanding the design (i.e., content) of regulation as a basis for studying regulation formation, implementation, and outcomes. Within this line of research, scholars have been particularly interested in investigating regulatory dynamics relating to features and patterns of regulatory text and have engaged a variety of methodological approaches to support their assessments. One approach featured in this research is the Institutional Grammar (IG). The IG supports syntactic and semantic analyses of institutional statements (e.g., regulatory provisions) that embed within regulatory text. A recently revised version—called the IG 2.0—further supports robust analyses of regulatory text by offering an expanded feature set particularly well‐suited to extracting and classifying content relevant for the study of regulation. This paper (i) provides a brief introduction to the IG 2.0 and (ii) discusses theoretical and analytical advantages of using the IG 2.0 to study regulation.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s11266-021-00423-w
