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Record W4321133560 · doi:10.54797/tfl.v42i1.11716

Kærligheden til det forsvindende

2012· article· en· W4321133560 on OpenAlexaboutno aff
Gregers Andersen

Bibliographic record

VenueTidskrift för litteraturvetenskap · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsnot available
Fundersnot available
KeywordsHumanityCriticismCharacter (mathematics)Climate changePhilosophyEnvironmental ethicsAestheticsLiteraturePsychoanalysisArtPsychologyEcology

Abstract

fetched live from OpenAlex

Love for the Disappearing: On Ice, Warming and Self-criticism in two Climate-Change Novels
 This article focuses on the configuration of the love of ice in two novels from the emergent field of climate-change fiction: The Ice Lovers (2009) by the Canadian author Jean McNeil, and Eis Tau (2011) by the Austrian author Ilija Trojanow. Both these works end with the suicide of the main character; a commonality which serves as the point of departure for this article. Additionally, the main characters’ love of ice is explored as a means of being-in-the-world, as opposed to the being-in-the-world of a humanity that is generally depicted as treating nature without love, i.e., unsustainably. In this regard the novels are also read as a site of self-criticism (or anthropocritique). In its pursuit of these two contrasting forms of being-in-the-world, the article draws heavily on the philosophy of Martin Heidegger. The ecological aspects of Heidegger’s philosophy have been firmly criticized by eco-critics and philosophers alike. However, as this article makes clear, Heidegger’s line of thought can still be detected in current writing on 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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.004

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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2012
Admission routes1
Has abstractyes

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