Machine coding of policy texts with the Institutional Grammar

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.

New opportunities for institutional analysis in public administration research

“…The first paper, authored by Frantz and Siddiki (2021), presents a revised syntactic and semantic specification of the Institutional Grammar called the Institutional Grammar 2.0. The second paper, authored by Rice et al (2021), discusses the use of computational text analysis and natural language processing in Institutional Grammar research. The third article, by Schlager et al (2021) presents a novel mixed methods approach for using Institutional Grammar textual data to empirically test hypotheses grounded in theories of institutional design.…”

“…Second, making the Institutional Grammar more computationally tractable also supports efforts to engage computational methods for automated coding of institutional statements according to the Grammar syntax as a partial or complete substitute for manual coding. This opportunity is discussed in the second article included in this Symposium by Rice et al (2021), the key contributions of which are discussed next.…”

“…Rice et al (2021) seek to address this challenge through the development of a tool for the automated classification of institutional text according to Institutional Grammar syntactic components, leveraging computational text analysis and natural language processing techniques. Their article presents a pilot study in which the authors apply the classification tool to code regulations governing food policy councils, which are diverse stakeholder collaboratives established to advise on local food system governance.…”

“…In this article, the authors describe the tool as well report on the performance of the tool. Given the referenced challenges associated with manual Institutional Grammar coding, the development of Rice et al's (2021) automated classification tool has the potential to substantially change Institutional Grammar research moving forward. Not only will it drastically ease the task of data collection, it opens the door to the possibility of engaging in assessment of large quantities of institutions and thus the related ability to produce generalizable insights relating to institutional design and related factors.…”

The Institutional Grammar: A Method for Coding Institutions and its Potential for Advancing Third Sector Research

“…Second-and even more promising-a team of researchers have recently introduced an automated approach for annotating policy documents into the IG (Rice et al, 2021) and have also released all code necessary for applying the approach in other contexts. The automated approach-which employs deep learning models and contextualized embedding features to learn a classification model based on sets of texts already classified into the IG-overcomes two limitations for the adoption of the IG in most research settings.…”