Cross‐border rubber cultivation between <scp>C</scp>hina and <scp>L</scp>aos: Regionalization by <scp>A</scp>kha and <scp>T</scp>ai rubber farmers
Bibliographic record
Abstract
This paper is a multi‐sited ethnography of cross‐border rubber cultivation between China and Laos. Smallholder minority rubber farmers from Xishuangbanna (China) have forged successful informal share‐cropping arrangements to grow rubber trees on the land of relatives and friends in neighbouring Laos. By becoming rich and entrepreneurial rural citizens, Akha and Tai farmers have also, in their own eyes, raised their own ‘quality’ (suzhi) and see themselves as ‘modern’. By examining various meanings of ‘modern’ in China, and contrasting the rubber farmers' experience with Jacob Eyferth's notion of rural ‘deskilling’, this paper shows how through learning to plant, cultivate and tap rubber, these farmers have taken on the discipline and technical knowledge of ‘modern’ workers and become ‘skilled’. By rising in ‘quality’, minority farmers on China's periphery challenge the entrenched binaries of urban/rural, modern/backward, prosperous/poor and Han/minority nationality. Xishuangbanna minority farmers acknowledge that they are also ‘backward’ in the Chinese social hierarchy, but their extension of rubber cultivation to kin and others in Laos has confirmed their modernity as dispensers of development, technical know‐how and ‘superior’ Chinese culture to Lao farmers who are ‘backward and poor’. In contrast to large state rubber farms that have failed to establish rubber plantations in northern Laos, minority farmers have created regionalization.
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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 | 0.000 | 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 | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".