Leveraging Critical Race Theory for Meaningful Systemic Change in Community Colleges.
Published In: New Directions for Community Colleges, 2025, v. 2025, n. 209/210. P. 21 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Fisher, Katlynn; Lanford, Michael 3 of 3
Abstract
This paper contends that state bans on Critical Race Theory (CRT) and diversity, equity, and inclusion (DEI) offices are indicative of a broader political agenda to restrict scholarly analyses and practitioner outreach that reveal how societal inequities, policy failures, and racialized deficit framings of marginalized students—not perceived institutional shortcomings—negatively impact the effectiveness of the community college sector. CRT is used to analyze the community college sector at the levels of federal policy and state policy. First, the paper depicts how the eligibility requirements of federal policies, such as the Temporary Assistance for Needy Families (TANF) program, and biases of case officers often conflict with student objectives to earn a viable postsecondary credential and obtain long‐term employment. Second, the paper critically analyzes how state policies, such as performance funding, penalize resource‐starved colleges for the "crimes" of helping underserved student populations while rewarding institutions with selective admissions policies. The conclusion of the article draws inspiration from Antar Tichavakunda's four‐point framework for understanding and engaging with CRT to offer recommendations for community college scholar‐practitioners. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:New Directions for Community Colleges. 2025/03, Vol. 2025, Issue 209/210, p21
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2025
- ISSN:0194-3081
- DOI:10.1002/cc.20661
- Accession Number:188425829
- Copyright Statement:Copyright of New Directions for Community Colleges is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.