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Record W2618955586 · doi:10.2458/v23i1.20181

Beyond "natural-disasters-are-not-natural": the work of state and nature after the 2010 earthquake in Chile

2016· article· en· W2618955586 on OpenAlexaff
Jacob Remes, Kevin Gould, Magdalena García

Bibliographic record

VenueJournal of Political Ecology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsConcordia University
Fundersnot available
KeywordsPoliticsState (computer science)Natural disasterAssertionPolitical ecologyEnvironmental ethicsNatural hazardNatural (archaeology)Political scienceSociologyNatural resourceCorporate governanceState of naturePolitical economyGeographyLawEconomicsArchaeology

Abstract

fetched live from OpenAlex

Since the 1970s, human ecologists, geographers, Marxian political economists and others have insisted that there is no such thing as a 'natural' disaster. This assertion opened a space not only for exploring socioeconomic conditions that render marginalized populations vulnerable to natural hazards, but also for the formation of a field, the political ecology of hazards. A few political ecologists further interrogated the idea of a natural disaster, asking how different notions of 'the natural' circulate in post-disaster politics and with what effects. This article extends the latter approach by documenting how interconnected categories of 'nature' and 'state' were mutually constituted by narratives of politicians and elites after Chile's 2010 earthquake and tsunami. Drawing on media reports, we identify three distinct pairings of state/nature: (1) nature as manageable and the state as manager; (2) nature as out of control and the state as a police state; and (3) nature as financial opportunity and the state as prudential. Influenced by socioeconomic and historical factors, these state/nature pairings contradicted and reinforced one another in the disaster's aftermath and were deployed to reinforce top-down—rather than democratic—strategies of post-disaster reconstruction. This case offers an unusual approach to disaster politics by tracing how entwined and power-laden categories of state and nature condition the governance of disaster reconstruction processes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.046
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.026
Scholarly communication0.0070.005
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.262
Teacher spread0.256 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations52
Published2016
Admission routes1
Has abstractyes

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