Bibliographic record
Abstract
This chapter presents a view of risk and disaster in the mountains that finds them fully a part of public safety issues in modern states and developments, rather than separated from them. This contrasts with prevailing approaches to disaster focused on natural hazards, “unscheduled” or extreme events, and emergency preparedness; approaches strongly reinforced by mountain stereotypes. Rather, we find the legacies of social and economic histories, especially relations to down-country or metropolitan actors, are decisive in shaping contemporary “mountain realities”. Developments in transportation, resource extraction and tourism that serve state and international agendas can increase rather than reduce risks for mountain populations, and undermine pre-existing strategies to minimise environmental dangers. Above all, we see rapid urbanisation in mountains generally and the Himalaya in particular as highly implicated in exacerbating risks and creating new types of vulnerabilities. Enforced displacement, and concentration of people in urban agglomerations, is a major part of the modern history of mountain lands that invites more careful exploration. Rapid expansion of built environments and infrastructure, without due regard to hazards and structural safety, introduce new and complex risks, while altering older equations with and to the land and sapping people’s resilience. In the lives of mountain people, environmental hazards are mostly subordinate to other, societal sources of risk and vulnerability, and to the insecurities these involve. Basically we conclude that “marginalisation” of mountain lands is primarily an outcome of socio-economic developments in which their condition is subordinated to strategic planning by state, metropolitan and global actors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".