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Record W2906718857 · doi:10.12697/il.2018.23.1.2

Comparative Literature, World Literature and Ethical Literary Criticism. Literature’s “Infra-Other”

2018· article· en· W2906718857 on OpenAlexaboutno aff
Jüri Talvet

Bibliographic record

VenueInterlitteraria · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLiterary criticismContextualizationMainstreamCriticismLiterary scienceComparative literatureSociologySociological criticismWorld literatureLiterary theoryEpistemologyLiteraturePhilosophyPolitical scienceArtLinguisticsLaw

Abstract

fetched live from OpenAlex

Relying on some of the ideas of Yuri M. Lotman on “semiosphere”, the dynamics and dialogue between “centres” and “peripheries”, as well as on my own ideas on cultural symbiosis expounded in my essay books A Call for Cultural Symbiosis. Meditations from U (Toronto, 2005) and Kümme kirja Montaigne’ile. “Ise ja “teine” (Ten Letters to Montaigne. ‘Self ” and ‘Other’, in Estonian: Tartu, 2014; in English, 2018) and inspired by the recent foundation in China of the International Association for Ethical Literary Criticism, I will try to meditate on the interrelation of Comparative Literature, World Literature and Ethical Literary Criticism both in theory and in the practice of teaching and researching literature at universities and high schools. The main purpose is to look at the ways how a “self”-centred practice of literary research and teaching (formalistic as well as sociological approaches, restricting World Literature to the Western mainstream, or just dealing with one’s own national literature, avoiding its comparative contextualization) could be gradually replaced by a symbioticdialogical treatment of literature, capable of providing our activity with a firm and solid ethical dimension, something that would definitely strengthen the position of humanities in the world academia.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0040.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.050
GPT teacher head0.323
Teacher spread0.273 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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