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Record W4306173689 · doi:10.1386/jem_00073_1

Purgatory islands and climate death-worlds: Interrogating the journalistic imperative to witness the climate crisis through the lens of war

2022· article· en· W4306173689 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

VenueJournal of Environmental Media · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWitnessClimate changePurgatoryHistoryPolitical sciencePolitical economyEnvironmental ethicsGeographySociologyLawLiteratureArtPhilosophy

Abstract

fetched live from OpenAlex

In this article, I examine and critique how the current and predicted future impacts of climate change are often reported on through the aesthetics and discourse of war. I argue that the journalistic imperative to witness climate change is important to consider here. Indeed, news images and descriptive accounts of climate change are often privileged for their evidentiary value according to a very strict set of visual criteria shaped by an established definition of what violence and war look like. Through a multimodal analysis of news coverage of the aftermath of Hurricane María across prominent US news magazines, I examine what constitutes compelling evidence of climate change, why and to what end in terms of the types of responses featured and proposed by journalists. Ultimately, my analysis reveals how Puerto Rico is demarcated as a ‘death-world’ across publications, effectively casting Puerto Rico as a ‘purgatory island’ dependent on the help of the United States represented as a saviour.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.058
GPT teacher head0.304
Teacher spread0.247 · 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