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Record W3088644450 · doi:10.1177/0008429820960105

Political Lament: Extinction, Grief, and Embodied Silence

2020· article· en· W3088644450 on OpenAlexaffvenue
Timothy Harvie

Bibliographic record

VenueStudies in Religion/Sciences Religieuses · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsSt. Mary's University
Fundersnot available
KeywordsGriefPoliticsPraxisEmbodied cognitionTragedy (event)SociologyAestheticsEnvironmental ethicsSilenceArgument (complex analysis)LamentPsychoanalysisEpistemologyPolitical scienceSocial sciencePsychologyPhilosophyPsychotherapistLawTheology

Abstract

fetched live from OpenAlex

This article confronts the ongoing tragedy of extinction in the Anthropocene from the standpoint of grief and embodied affect. It argues that when confronted with the death of an animal other – be it in public and political settings or in personal encounters of suffering – that silent grief is an embodied form of protest to the triumphalist and anthropocentric narratives of the neoliberal petro-state. In developing an account of suffering and grief from Miguel de Unamuno the argument proceeds to account for an embodied political praxis which subverts political structures aimed at marginalizing animal-others. Finally, in dialogue with Maurice Merleau-Ponty, the article concludes with a reflection on how scholarly activities in the mode of grief might enact relational capacities with the broader animal and natural world.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.069
Scholarly communication0.0060.008
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.104
GPT teacher head0.412
Teacher spread0.307 · 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 designNot applicable
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
Published2020
Admission routes2
Has abstractyes

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