Bibliographic record
Abstract
Small hydropower has widely been considered a renewable energy source with minimum adverse social and environmental impacts. However, the expansion of small hydropower in the northwest uplands of Vietnam over the last two decades has created and even normalized persistent and multidimensional water injustice for ethnic minority groups in the region. For some, this expansion has meant persistent, but silent, generational, and cumulative experiences of marginalization and impoverishment as well as the erosion of a way of life. Extractive activities reconstruct identities and redistribute resources and decision-making power, but not without igniting resistance. Local ethnic minority households struggle in negotiating their everyday realities, which are occupied with livelihood maintenance, social interactions, and fights over their use and control of resources. This paper unravels the particular gendered workings in responding to slow violence, drawing on photovoice and over a decade of fieldwork in the northwest uplands where hundreds of small hydrodevelopment projects have been planned and implemented since the early 2000s. The paper argues that the seemingly mundane tasks that women carry out, including cooking, weaving and dyeing fabrics, and growing crops, which are revealed through a gendered perspective to be foundational in cultivating community resilience, self-help, solidarity, resistance, and reworking in the face of ongoing structural injustices and hardships brought about by small hydropower development in Vietnam’s northwest uplands.
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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 | 0.002 | 0.001 |
| 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 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".