Bibliographic record
Abstract
For centuries, people who call themselves Akha had formed village landscapes of rotating shifting cultivation fields amid regenerating trees together with enduring wooded sites, all under the purview of their ancestors. In Mengsong, an Akha settlement on the ridge separating China and Burma, farmers had managed complex, biodiverse and flexible landscapes for 250 years. In 1996–1997, my extended research there identified cultivation patterns that I called landscape plasticity, referring to farming practices that were highly mutable over space and time, often transgressing state-allocated property lines and the international border with Burma. From 1997 to 2011, a combination of exclusionary state forest policies, the racialization of upland minorities, and a state poverty alleviation project brought landscape plasticity and the ancestors to an end. Using concepts from sentient landscapes, resource access, environmentalism, racialization, and capitalist markets, this paper seeks to explain how landscape plasticity and the ancestors were erased. At the same time, I explore the puzzle of why Akha farmers saw these contingent outcomes as positive
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".