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Record W2606843475 · doi:10.21083/nrsc.v0i10.3704

De l’écriture « comme un couteau » à l’écriture « dans le vif » : Le vrai lieu d’Annie Ernaux

2017· article· fr· W2606843475 on OpenAlexvenueno aff
Mariana Ionescu

Bibliographic record

VenueNouvelle Revue Synergies Canada · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicDiverse Cultural and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

RésuméPlusieurs récits d’Annie Ernaux contiennent des réflexions sur son processus de création, mais c’est surtout dans L’écriture comme un couteau (2003) et Le vrai lieu (2014) qu’elle détaille le lien entre lieux, vie et écriture. Ces deux volumes d’entretiens éclairent l’origine de son désir d’écrire, les motivations et les circonstances qui l’ont poussée à dévoiler certaines expériences indicibles, ainsi que les stratégies de création qui lui ont permis de faire de l’écriture son « vrai lieu ». Après les premiers romans, le rejet de la fiction et des conventions romanesques s’impose à cette écrivaine soucieuse de trouver les mots justes, seuls capables de saisir la vérité de son milieu d’origine. Une fois dépassée l’étape de « l’écriture comme un couteau », elle s’appuie essentiellement sur la mémoire personnelle et collective afin de mieux capter l’intersection des histoires et de l’Histoire. AbstractSeveral of Annie Ernaux’s works contain reflections on her creative process, but it is in L’écriture comme un couteau (2003) and Le vrai lieu (2014) in particular that she elaborates in detail on the link between places, life, and writing. These two volumes of interviews shed light on the origins of her desire to write, the motivations and the circumstances which pushed her to reveal a number of unspeakable personal experiences, as well as the creative strategies which enabled her to make writing her “true place”. After her first novels, and the subsequent rejection of fiction and of novelistic conventions, it becomes imperative for Ernaux to find the right words, alone able to express the truth of her place of origin. Once past the “writing as a knife” stage, she focuses primarily on individual and collective memory in order to better capture the intersection between stories and History.

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), Science and technology studies
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 score0.640
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 studies0.0090.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.243
Teacher spread0.213 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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