International Development Volunteering as Transformational Feminist Practice for Gender Equality
Bibliographic record
Abstract
International and transnational commitments to gender equality require strategies that tackle root causes and prevailing attitudes that perpetuate disparities. In this article, we examine the role and impact of international development volunteers (IDV) as development actors who are well-placed for feminist transformational change, as they work in transnational spaces to influence, support, or reinforce changes in attitudes and behaviors towards gender equality and women’s empowerment (GEWE). This qualitative study analyses data collected from 45 interviews in three countries (Malawi, Kenya and Uganda) to document partner organization perspectives on relational dynamics emerging from interactions with IDVs. Partner organization staff highlighted several notable positive and negative contributions to GEWE outcomes arising from day-to-day interactions with IDVs. These interactions shaped their understandings of GEWE, enhanced confidence for GEWE programming, and provided exposure to role models who can shape alternative attitudes and behaviors to gender equality. While the study revealed varying degrees of challenges and benefits for partner organizations working with volunteers specifically on gender equality, partner organization staff highlighted contributions made by IDVs to transnational spatial relations, as well as the transformational interactions that shaped these relations. Insights provided by partner country staff members offer subaltern perspectives and rich insights into the contributions of IDVs in gender equality programming and shed new light on the challenges and opportunities for fostering transnational feminist spaces of knowledge sharing, relationship building, and alternative practices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.028 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".