The First Mile of Global Value Chain Governance: Empowering Women and Reducing Gender-Based Violence through Third-Party Interventions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Global value chains (GVCs) often reinforce gender inequality and violence, particularly in fragile contexts. This dissertation examines when third-party interventions enhance women’s empowerment and reduce gender-based violence in the first mile of GVCs. Using unique primary data from artisanal mining communities in three African countries, we find that women’s inclusion is driven by economic incentives, while empowerment increases through female leadership and hybrid governance. Crucially, reducing intimate partner violence requires educational and socially inclusive interventions, as economic strategies alone are insufficient. The findings offer theoretical insights and practical guidance for NGOs, policymakers, and multinationals seeking to foster more equitable GVCs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it