JOURNAL ARTICLE
The Diverse Voices Framework: Re-Imagining HRD Education for Social Justice Beyond the Classroom.
Published In: Advances in Developing Human Resources, 2026, v. 28, n. 1. P. 36 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Scott, Chaunda L.; Byrd, Marilyn Y.; Collins, Joshua C.; Johnson-Bailey, Juanita; Bohonos, Jeremy 3 of 3
Abstract
This article examines the representation and application of diversity education and social justice education within Human Resource Development (HRD) undergraduate and graduate programs, highlighting a notable gap in curricula that prepare future leaders and practitioners for real-world social justice challenges. It introduces the Diverse Voices Framework, a three-part participatory model that integrates student voices, expert perspectives, and creative artistic expressions to foster critical reflection and activism beyond traditional classroom settings, exemplified through the annual Diverse Voices Conference. Keynote presentations emphasize the complexity of diversity, intersectionality, allyship, and the persistent nature of backlash against equity efforts, advocating for curricula that develop moral agency, critical consciousness, and practical skills to address systemic oppression in organizational contexts. The article underscores the need for HRD educators to adopt culturally relevant and responsive pedagogies and calls for expanded research and curriculum development that center social justice as integral to HRD education and practice.
Additional Information
- Source:Advances in Developing Human Resources. 2026/02, Vol. 28, Issue 1, p36
- Document Type:Conference Paper/Materials
- Subject Area:Economics
- Publication Date:2026
- ISSN:1523-4223
- DOI:10.1177/15234223251407886
- Accession Number:190862345
- Copyright Statement:Copyright of Advances in Developing Human Resources is the property of Sage Publications Inc. 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.)
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