Caring for the river‐border: Struggles and opportunities along the Salween River‐border
Bibliographic record
Abstract
Abstract Geographers have shown how borders rely on the enactment of state power and violence to reinforce territorial integrity and sovereign authority, or even perpetuate the destruction of nature. Moving away from an emphasis on violence, in this paper, I take an approach to borders and bordering that emphasises the opportunities of the border when it is also a river to understand borders as a resource and site of engagement with the state by a range of actors, including variants of care. To illustrate this, I draw on longstanding research along the Salween River, the 120 km stretch where the river forms the Thai–Myanmar (Burma) border, to reveal the ways in which borders as rivers can provide new insights into socio‐natural bordering processes. In particular, I illustrate a range of ways local residents are caring for a river‐border, and how even an ‘exploding’ or ‘hungry’ river‐border can be a fragile space for care and for non‐state actors to enact the border ‘differently’ in everyday life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".