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Anny Dayan Rosenman, Les Alphabets de la Shoah. Survivre, témoigner, écrire

2009· article· fr· W311768883 on OpenAlexaff
Carine Trévisan

Bibliographic record

VenueQuestions de communication · 2009
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

C'est sous la forme d'un triptyque qu'Anny Dayan Rosenman offre une lecture de textes de survivants d'une Histoire o fut dpass un seuil de violence et de barbarie jusque-l jamais atteint. Textes qui interrogent les pouvoirs du langage, de la littrature, textes qui luttent -souvent douloureusement -avec l'ange de l'criture . Dans cette tude la frontire de plusieurs disciplines (littrature, histoire, psychanalyse), elle nous initie ce qu'elle nomme magnifiquement les Alphabets de la Shoah . l'origine de cet alphabet, trois figures qui s'engendrent l'une l'autre tout en gardant la mmoire de la prcdente : le survivant, le tmoin, l'crivain.

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0160.004

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 head0.165
GPT teacher head0.362
Teacher spread0.197 · 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
GenreOther

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

Citations7
Published2009
Admission routes1
Has abstractyes

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