AI Research in Educational Leadership
ISSN (Online): 3023-8420

Research article    |    Open Access
AI Research in Educational Leadership 2026, Vol. 2(2) 1-16

Code for Equity: A Human-AI Process for Reviewing Education Policy Against CARE Frameworks

Rakèta A. Ouédraogo-Thomas, Samantha Rummage-Massey

pp. 1 - 16   |  DOI: https://doi.org/10.5281/zenodo.20609121

Publish Date: June 09, 2026  |   Single/Total View: 0/0   |   Single/Total Download: 0/0

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Abstract

This article presents a methodology combining AI-powered text mining with culturally responsive, antiracist, and equitable (CARE) principles to analyze educational policy. Using sentiment and word-count analyses, we evaluate policies from four U.S. states (North Carolina, California, Oregon, and Washington) and federal legislation. Findings reveal that procedural, compliance-focused language predominates, limiting transformative potential—patterns mirrored in school and district implementation challenges. California demonstrates stronger culturally responsive integration. We offer a replicable rubric that researchers, educators, and policymakers can use to evaluate policy design and identify implementation barriers. This approach provides an accessible method for equity-centered policy review while addressing ethical considerations inherent in AI-assisted analysis, including transparency about tool limitations and the primacy of researcher judgment over automated outputs. This methodology extends a prior qualitative policy analysis (Ouedraogo-Thomas et al., 2025) into a reproducible computational framework applicable across policy contexts.

Keywords: AI-assisted policy analysis, bias, CARE frameworks, critical policy analysis, text analysis

How to Cite this Article?

APA 7th edition
Ouédraogo-Thomas, R.A., & Rummage-Massey, S. (2026). Code for Equity: A Human-AI Process for Reviewing Education Policy Against CARE Frameworks. AI Research in Educational Leadership, 2(2), 1-16. https://doi.org/10.5281/zenodo.20609121

Harvard
Ouédraogo-Thomas, R. and Rummage-Massey, S. (2026). Code for Equity: A Human-AI Process for Reviewing Education Policy Against CARE Frameworks. AI Research in Educational Leadership, 2(2), pp. 1-16.

Chicago 16th edition
Ouédraogo-Thomas, Rakèta A. and Samantha Rummage-Massey (2026). "Code for Equity: A Human-AI Process for Reviewing Education Policy Against CARE Frameworks". AI Research in Educational Leadership 2 (2):1-16. https://doi.org/10.5281/zenodo.20609121

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