Gather-Narrow-Extract: A Framework for Studying Local Policy Variation Using Web-Scraping and Natural Language Processing
Kylie L. Anglin
Many education policy decisions are made at the local level. School districts make policies regarding hiring, resource allocation, and day-to-day operations. However, collecting data on local policy decisions has traditionally been expensive and time-consuming, sometimes leading researchers to leave important research questions unanswered.
This paper presents a framework for efficiently identifying and processing local policy documents posted online – documents like staff manuals, union contracts, and school improvement plans – using web-scraping and natural language processing.