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Record W2959250640 · doi:10.1111/disa.12379

Waiting for the flood: technocratic time and impending disaster in the Himalayas

2019· article· en· W2959250640 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDisasters · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFlood mythTechnocracyPopulationPreparednessNatural disasterState (computer science)GeographyPolitical scienceEnvironmental planningSociologyDemographyArchaeologyLaw

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.256
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it