JOURNAL ARTICLE
Situational Analysis of Power in Participatory Action Research: Mapping Systemic Frameworks, Discourses, and Principles for Critical Feminist Qualitative Inquiry.
Published In: Affilia: Feminist Inquiry in Social Work, 2025, v. 40, n. 3. P. 377 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Tang Yan 趙嘉蓮, Catalina 3 of 3
Abstract
This article focuses on the application of situational analysis, a critical qualitative methodology developed by sociologist Adele E. Clarke, to examine power differentials within Participatory Action Research (PAR) and Community-Based Participatory Research (CBPR) collaborations among social work faculty and community stakeholders. Drawing from a study involving U.S.-based social work scholars and community partners, the article illustrates how situational analysis—through various mapping techniques—can reveal the complex interplay of human and nonhuman elements, structural barriers, and discourses that shape participatory knowledge production under neoliberal, colonial, and capitalist influences. It highlights tensions between academic institutional demands (e.g., tenure, funding, publication pressures) and community-based experiential knowledge, emphasizing critical feminist principles such as reflexivity, intersectionality, and epistemic justice. The article concludes that situational analysis offers valuable tools for critical feminist social work scholarship and praxis to interrogate and reimagine oppressive knowledge production processes, while acknowledging methodological challenges and the need for further research on dynamic power relations in participatory inquiry.
Additional Information
- Source:Affilia: Feminist Inquiry in Social Work. 2025/08, Vol. 40, Issue 3, p377
- Document Type:Article
- Subject Area:Social Sciences and Humanities
- Publication Date:2025
- ISSN:0886-1099
- DOI:10.1177/08861099241300649
- Accession Number:186601827
- Copyright Statement:Copyright of Affilia: Feminist Inquiry in Social Work 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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