Under the state's gaze: Upland trading‐scapes on the Sino‐Vietnamese border
Bibliographic record
Abstract
Within the politically‐defined Greater Mekong Subregion (GMS), the borderlands of southeast Yunnan, China and Lào Cai province, northern Vietnam, have been categorized as being part of the GMS North‐South Economic Corridor. I argue that the creation of this subregion and corridor have been an opportunity for the governments in these locales to extend their territorialization and create new state spaces. For centuries, relatively isolated and ignored by lowland rulers, ethnic minority residents in these borderlands maintained their own culturally appropriate livelihoods, trade networks and societies. Nowadays, an increasing state presence in the uplands presents both challenges and opportunities for local populations on either side of the border, be they ethnic minorities, or Kinh (lowland Vietnamese) and Han Chinese. Contemporary border narratives gathered from local traders managing important upland commodities shed light on the means by which these borderland spaces are shaping both attractive prospects as well as restrictive constraints. Local residents fashion new trading‐scapes by drawing on kin ties, historical linkages, local indigenous knowledges and transnational societies that reach deep inside each country. As inhabitants carefully avoid or manipulate the state's gaze, I conclude that those living in the Sino‐Vietnamese borderlands possess the agency to ‘do things differently’ from hegemonic development approaches supported by GMS sponsors, and can create, maintain, support and refashion culturally appropriate trade livelihoods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| 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".