Remembering the Mun: engendering local geographies of resistance to the Pak Mun Dam
Bibliographic record
Abstract
The Pak Mun Dam remains one of north-eastern Thailand’s most disputed infrastructure projects. Local livelihoods, particularly those of women, have been negatively impacted, leading many to participate in the resistance movement against the dam. While the fight continues, protests have waned in frequency and vigour. Many in the resistance movement have grown older and passed on, while others have accepted their fate brought on, in part, by the Electricity Generating Authority of Thailand’s use of resources to foment division among villagers. In the place of mass protests, local actors have turned to organising memorial events, in which resistance is expressed through local practices. This article explores the roles of women, particularly Mae Sompong, in shaping new geographies of resistance through the embodied performances of two memorial events—the Liang Luang Liang Wang and the Boon Mot ceremonies. While the annual Liang Luang Liang Wang ceremony commemorates the migration of fish upriver from the Mekong River into the Mun River and the Boon Mot ceremony commemorates Wanida (Mot) Tantiwittayapitak and other Pak Mun Dam activists who have died, both serve as reminders of past resistance and are catalysts for future contestations. Using a feminist political ecology approach, we contend that ethnic Lao villagers, especially women, constitute local geographies of anti-dam resistance through commemorative practices, ones that have been rendered unimportant and invisible by uneven power relations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".