From needs to actions: prospects for planned adaptations in high mountain communities
Bibliographic record
Abstract
Abstract Adaptation needs in high mountain communities are increasingly well documented, yet most efforts to address these needs continue to befall mountain people who have contributed little to the problem of climate change. This situation represents a contravention of accepted norms of climate justice and calls attention to the need for better understanding of prospects for externally resourced adaptation initiatives in high mountain areas. In response, this paper examines the architecture of formal adaptation support mechanisms organized through the United Nations Framework Convention on Climate Change (UNFCCC) and how such mechanisms might help to meet adaptation needs in high mountain communities. It outlines key global adaptation initiatives organized through the UNFCCC, clarifies idealized linkages between these global adaptation initiatives and meeting local adaptation needs, and evaluates actual progress in connecting such support with discrete adaptation needs in the upper Manaslu region of Nepal. The paper then critically examines observed shortcomings in matching adaptation support organized through the UNFCCC with local adaptation needs, including complications stemming from the bureaucratic nature of formal adaptation support mechanisms, the intervening role of the state in delivering aid, and the ways in which these complexities intersect with the specific socio-cultural contexts of mountain communities. It concludes by highlighting several prospects for increasing the quantity and quality of adaptation support to mountain communities. These opportunities are considered alongside several salient concerns about formal adaptation support mechanisms in an effort to provide a well-rounded assessment of the prospects for planned adaptations in high mountain communities.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".