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Record W4404107913 · doi:10.1080/00085006.2024.2404800

Optique de la guerre dans <i>Cassandre</i> de Lesâ Ukraïnka

2024· article· fr· W4404107913 on OpenAlexvenueno aff
Svitlana Macenka, Diana Melnyk, Yaryna Tarasyuk, Sofiya Varetska

Bibliographic record

VenueCanadian Slavonic Papers · 2024
Typearticle
Languagefr
FieldEnvironmental Science
TopicEnvironmental and Biological Research in Conflict Zones
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Le poème dramatique Cassandre (1907) de la dramaturge ukrainienne Lesâ Ukraïnka (1871–1913) est considéré comme une interprétation à multiples aspects de l’expérience de la guerre. Cette analyse est inspirée par l’intensification de la production théâtrale moderne de cette œuvre dramatique en Ukraine, qui est actuellement en état de guerre, ce qui s’explique sans doute par les problèmes extrêmement pertinents qui y sont présentés (conflit, tragédie, surmonter la catastrophe). La guerre de Troie agit comme une révélatrice des relations sociales de la communauté et des problèmes essentiels de ses citoyens. Cet article aborde la stratégie de mythification de la guerre, comme archétype de la violence, d’une version intra-historique de la guerre de Troie, du concept de mémoire dans le contexte de la guerre, de sa compréhension comme catastrophe, d’une vision de la guerre de l’intérieur et de l’extérieur. En lien avec l’image de Méduse souvent évoquée dans l’œuvre de Lesâ Ukraïnka, le regard de la mort est interprété comme médialement compris à la frontière de la photographie et du narratif.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.007
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.002
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 head0.012
GPT teacher head0.265
Teacher spread0.253 · 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 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
Published2024
Admission routes1
Has abstractyes

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