Machine coding of policy texts with the Institutional Grammar

• 成果类型: Article
• 署名作者: Rice, Douglas; Siddiki, Saba; Frey, Seth; Kwon, Jay H.; Sawyer, Adam
• 署名单位: University of Massachusetts System; University of Massachusetts Amherst; Syracuse University; University of California System; University of California Davis; International Organization for Migration
• 刊物名称: PUBLIC ADMINISTRATION
• ISSN/ISSBN: 0033-3298
• DOI: 10.1111/padm.12711
• 发表日期: 2021
• 页码: 248-262
• 关键词: model

摘要

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.