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Record W1940211906 · doi:10.26522/vp.v11i1.916

Déchiffrer sa vie et l’écrire

2014· article· fr· W1940211906 on OpenAlexvenueno aff
Colette Nys-Mazure

Bibliographic record

VenueVoix Plurielles · 2014
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtSociology

Abstract

fetched live from OpenAlex

La littérature est un texte, un tissu de relations de soi à soi, de soi aux autres, d’innombrables autres passés et à venir, par le biais du langage. Cet outil premier semble appartenir à tous, mais en réalité il n’est pas à la portée de chacun. Il serait donc intéressant de relater l’expérience angevine que je viens de vivre avec Lire~Ecrire~Compter (LEC), une association pour la promotion des savoirs, l’insertion sociale et professionnelle, créée en 1986, qui lutte contre l’illettrisme. L’une de ses approches originales, la “lecture-plaisir”, consiste à proposer à des volontaires de participer à la création d’un livre. Depuis 2004, l’association permet à ses “apprenants” de rencontrer un écrivain reconnu afin de participer à des ateliers d’écriture. Le fruit de leur travail commun est retranscrit dans la première partie de l’ouvrage publié ; la seconde nait de la libre créativité de l’auteur.
 
 Deciphering one’s life and writing it
 
 Literature is a text, a fabric of relations between oneself and oneself, between oneself and others – countless past and to come –, by the means of language. This tool is supposed to belong to all, but is in fact not accessible to everybody. In this respect, an experience I just went through in Angers (France) is highly interesting. Lire-Écrire-Compter (Read-Write-Count), an association for the promotion of knowledge, social and professional inclusion, and against illiteracy since 1986, proposes to its students to take part in the creation of a book. Since 2004, this program called “Reading-pleasure” offers students the opportunity of a “writing workshop” with a renowned writer. The first part of the published book presents this collective work; the second part originates from the author’s own creativity.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · 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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.021
GPT teacher head0.259
Teacher spread0.239 · 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; both teacher heads agree on what is shown here.

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
Published2014
Admission routes1
Has abstractyes

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