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Record W7117107354 · doi:10.5206/fpq/2024.1/2.18724

Climate Crisis as Relational Crisis

2024· article· W7117107354 on OpenAlexvenueno aff
Shelbi Nahwilet Meissner, Andrew Frederick Smith

Bibliographic record

VenueFeminist Philosophy Quarterly · 2024
Typearticle
Language
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeIndigenousClimate justiceFraming (construction)AnthropoceneVisionClimate riskColonialismCivilization

Abstract

fetched live from OpenAlex

It is commonly assumed that we currently face a climate crisis insofar as the climatological effects of excessive carbon emissions risk destabilizing advanced civilization and jeopardize cherished modern institutions. The threat posed by climate change is treated as unprecedented, demanding urgent action to avert apocalyptic conditions that will limit or even erase the future of all humankind. In this essay, we argue that this framework—the default climate crisis motif—perpetuates a discursive infrastructure that commits its proponents, if unwittingly, to logics that ultimately reinforce the dynamics driving climate change and its attending injustices. By centering Indigenous feminist environmental discourses, which privilege the role of richly interweaving networks of responsibilities composing extended more-than-human kinship arrangements, we contend that climate crisis is instead primarily a manifestation of devastating multidimensional relational disruptions of Indigenous lands and lives. More pointedly, it is a rebound effect of centuries of accumulating colonial injustices against responsible lifeways that are critical for socioecological adaptability and responsiveness. Framing climate crisis as relational crisis hereby creates discursive space for much needed transformational Indigenous feminist visions for justly and effectively addressing climate change.

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)0.004
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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.039
Scholarly communication0.0070.013
Open science0.0010.010
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.235
Teacher spread0.218 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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