Money isn’t Free: A Systematic Content Analysis of Hispanic-Serving Community Colleges Title V Awardees Proposals
Principal Investigator(s): View help for Principal Investigator(s) Erin Doran, The University of Texas at El Paso; Stephanie Aguilar-Smith, University of North Texas
Version: View help for Version V1
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Project Citation:
Doran, Erin, and Aguilar-Smith, Stephanie. Money isn’t Free: A Systematic Content Analysis of Hispanic-Serving Community Colleges Title V Awardees Proposals. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-01-10. https://doi.org/10.3886/E215263V1
Project Description
Summary:
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Amid public divestment in higher
education, grant acquisition is increasingly critical for colleges and
universities, especially Hispanic-serving community colleges (HSCCs). We
conducted a content analysis of 400 HSCC Title V awardee proposal abstracts and
found that these awardees ground their proposals in the needs of their local
communities but often still pitch race-evasive projects. At the same time, we
also discovered that in recent years, these successful applicants began invoking
the language of “servingness,” promisingly suggesting that some HSCCs are
attempting to leverage this money to intentionally support Latine/x students.
However, the Department of Education’s competitive preference priorities, alongside
its race-evasive evaluation criteria, may undercut the extent to which HSIs,
including HSCCs, advance servingness with this funding. Ultimately, the
findings support the need to reform this public program, particularly
considering the ongoing institutional diversification of the HSI population.
Keywords:
Hispanic-Serving Institutions; Community Colleges; Title V; grants
Scope of Project
Subject Terms:
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community colleges;
Hispanic-serving Institutions;
Title V;
grant funding
Time Period(s):
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2009 – 2022
Methodology
Data Source:
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These abstracts will collated from the Department of Education's website for Title V: Developing Hispanic-Serving Institutions grants. Abstracts for years 2009-2022 were downloaded. This database constitutes the data that was collapsed into one document and used in the analysis process.
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