CREAT: Census Research Exploration and Analysis Tool

Measuring School Economic Disadvantage

November 2022

Working Paper Number:

CES-22-50R

Abstract

Many educational policies hinge on the valid measurement of student economic disadvantage at the school level. Measures based on free and reduced-price lunch enrollment are used widely. However, recent research raises questions about their reliability, particularly following the introduction of universal free lunch in certain schools and districts. Using unique data linking the universe of students in Oregon public schools to IRS tax records and other data housed at the U.S. Census Bureau, we provide the first examination of how well different measures capture school economic disadvantage. We find that, in Oregon, direct certification provides the best widely-available measure, both over time and across the distribution of school economic disadvantage. By contrast, neighborhood-based measures consistently perform relatively poorly.

Document Tags and Keywords

Keywords Keywords are automatically generated using KeyBERT, a powerful and innovative keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant keywords.

By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the text, highlighting the most significant topics and trends. This approach not only enhances searchability but provides connections that go beyond potentially domain-specific author-defined keywords.
:
recession, economically, segregation, disadvantaged, household, educated, education, student, enrollment, poverty, socioeconomic, disparity, school, enrolled, poor

Tags Tags are automatically generated using a pretrained language model from spaCy, which excels at several tasks, including entity tagging.

The model is able to label words and phrases by part-of-speech, including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are identified to contain references to specific institutions, datasets, and other organizations.
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Internal Revenue Service, Urban Institute, Medical Expenditure Panel Survey, Department of Education, Economic Research Service, American Community Survey, Protected Identification Key, National Center for Health Statistics, Temporary Assistance for Needy Families, National Institutes of Health, Census Bureau Disclosure Review Board, Person Identification Validation System

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