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Record W2991583681 · doi:10.26522/vp.v16i2.2312

Des chemins de traverse qui ne mènent pas nulle part : Forêts, de Wajdi Mouawad, ou l’entrelacs de l’histoire et de l’intime, du politique et du psychique

2019· article· fr· W2991583681 on OpenAlexvenueno aff
Pascal Vacher

Bibliographic record

VenueVoix Plurielles · 2019
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

« Ma mémoire est une forêt dont on a abattu les arbres ». Le titre de cette pièce de Wadji Mouawad est au pluriel car la forêt est polysémique. Elle est d’abord un espace ardennais au sein duquel se trouve un domaine à l’écart de tout, conçu pour échapper à l'Histoire ainsi qu’à l’histoire de la famille Keller. Mais c’est dans ce lieu utopique que resurgit violemment l’histoire, au point que le zoo qui devait être une arche de Noé devient le lieu même de la traversée de l'intime par l'histoire, la psyché de chaque personnage étant métaphoriquement une forêt, chargée de sa mémoire et de celle de sa généalogie nécessairement marquée par l’histoire cauchemardesque du vingtième siècle. Chacune de ces forêts (psychiques et historiques) réagit sur les autres, le spectateur s'y perdant d'abord et retrouvant à la fin le fil qui permet à sa psyché de se réparer afin qu'émerge de cet entrelacs une subjectivité partagée entre personnages et spectateurs, désormais aptes à devenir sujets de leur histoire.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.007
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.018
GPT teacher head0.313
Teacher spread0.294 · 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
Published2019
Admission routes1
Has abstractyes

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Same venueVoix PluriellesSame topicPsychoanalysis and Psychopathology ResearchFrench-language works237,207