Rescaling and Reordering Nature–Society Relations: The Nam Theun 2 Hydropower Dam and Laos–Thailand Electricity Networks
Bibliographic record
Abstract
In 2010, the largest hydropower dam ever constructed in Laos, the Nam Theun 2 (NT2) Power Project, was completed with crucial—indeed, deal-making—support from the World Bank. Although the vast majority of the electricity produced by the project is exported to neighboring Thailand, the most important negative social and environmental impacts have occurred in Laos. While much attention has focused on the dam reservoir, there have been significant effects downstream from the project along the Xe Bang Fai (XBF) River, a major tributary of the mainstream Mekong River. In this article we examine the complex relationships between energy produced by NT2 and energy consumption patterns in Thailand. We link varying electricity demand in Thai air conditioning, fluctuating water releases from the NT2 dam, and downstream changes in XBF hydrology. Taking a political ecology approach, we emphasize how NT2 is part of rescaling electricity production and consumption networks, changes to their modes of ordering, and the reworking of nature–society relations. Although NT2 involves a complex array of social and environmental civil society concerns for Thailand, Laos, and global society, this was largely obscured by the commercial and technical orientation of its novel governance systems.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 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".