MétaCan
Menu
Back to cohort
Record W2957366150 · doi:10.25071/2369-7326.40293

Decolonizing the Cosmopolitan Geospatial Imaginary of the Anthropocene: Beyond Collapsed and Exclusionary Politics of Climate Change

2019· article· en· W2957366150 on OpenAlexvenueno aff
Shelby E. Ward

Bibliographic record

VenuePivot A Journal of Interdisciplinary Studies and Thought · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsnot available
Fundersnot available
KeywordsCosmopolitanismAnthropoceneThe ImaginaryPoliticsEnvironmental ethicsSociologyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

This paper extends Tariq Jazeel’s argument on cosmopolitanism to the Anthropocene. Jazeel argues that cosmopolitanism should be thought of geospatially, as a geographic analysis reveals that cosmopolitanism cannot escape its own historically Western spatial imaginary, ultimately collapsing difference and universalizing humanity (77). In reaction against suggestions that cosmopolitanism is a more ethical and socially responsible approach to changing environments, I maintain instead that the Anthropocene already operates within a cosmopolitan geospatial imaginary, which not only collapses blame and responsibility in the face of global environmental crises but also silences and erases the historical contexts of exploitation and extraction that follow within north-south lines of coloniality. Therefore, a decolonization of the cosmopolitan geospatial imaginary of the Anthropocene requires, in order to situate continued coloniality in environmental geopolitics and international relations, looking at the frameworks of both the nation-state and cosmopolitanism. The sections follow a critique of this proposed dialectic working within systems of exclusionary politics of the nation-state and the collapsing politics of cosmopolitanism.

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 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)0.001
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 score0.103
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.059
GPT teacher head0.362
Teacher spread0.303 · 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 teacher head, 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venuePivot A Journal of Interdisciplinary Studies and ThoughtSame topicClimate Change, Adaptation, MigrationFrench-language works237,207