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Record W2800778509 · doi:10.1177/0263775818774046

We are the world (but only at the end of the world): Race, disaster, and the Anthropocene

2018· article· en· W2800778509 on OpenAlexaff
Hee-Jung Serenity Joo

Bibliographic record

VenueEnvironment and Planning D Society and Space · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsUniversity of Manitoba
FundersFederal Emergency Management Agency
KeywordsAnthropoceneRace (biology)HumanityMaterialismPoliticsEnvironmental ethicsReading (process)HistorySociologyAestheticsGender studiesPolitical sciencePhilosophyEpistemologyLaw

Abstract

fetched live from OpenAlex

This essay explores the racial politics of a select group of contemporary disaster film and fiction to reveal the relationship between race and futurity that also undergirds discussions of the Anthropocene. I provide a comparative close reading of the disasters in Roland Emmerich’s The Day After Tomorrow and 2012, Behn Zeitlin’s Beasts of the Southern Wild, and Karen Tei Yamashita’s Through the Arc of the Rain Forest. I argue that the cultural anxieties that structure these texts are expressions of the racial logic rooted in universalist concerns for the future of humanity, the very concern of the Anthropocene. Arguing against inclusion as the means of achieving equality and toward a new materialist understanding of race, my paper illuminates not only the racial assumptions of the Anthropocene but also, and perhaps more importantly, its racial consequences.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.026
Scholarly communication0.0060.006
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.203
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations24
Published2018
Admission routes1
Has abstractyes

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