Waiting for the flood: technocratic time and impending disaster in the Himalayas
Bibliographic record
Abstract
A landslide occurred in the region of Zanskar in the Indian Himalayas in 2015, damming the Tsarap River, creating a lake that effectively became a ticking time bomb, threatening villagers downstream. During the period between the discovery of the natural dam and the bursting of the lake, the state's approach to disaster management plunged the local population into a situation where 'technocratic time' ruled, as government experts handled the impending disaster at a rhythm dictated by the production of studies and reports. Analysis of the temporality of disaster mitigation and preparedness measures during this anticipated flood, as well as of the factors that surrounded the events, reveals how attitudes towards the state shaped people's perceptions of these interventions. In Zanskar, the technocratic pace and the state's lack of transparency were seen as a form of oppression that further marginalised the region, in particular by subjecting its population to the process of waiting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".