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Record W4402701942 · doi:10.7202/1113223ar

De l’écriture en réseaux aux écrits de soi : les correspondances de Catherine d’Aspremont, Anne-Marie-Louise d’Orléans et Françoise de Motteville (mai-juin 1660)

2024· article· fr· W4402701942 on OpenAlexvenueno aff
Fanny Boutinet

Bibliographic record

VenueTangence · 2024
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Cet article étudie les lettres que Françoise de Motteville, Anne-Marie-Louise d’Orléans et Catherine d’Aspremont rédigent au printemps 1660. Les épistolières assistent alors au mariage de Louis XIV. Elles adressent plusieurs lettres à un réseau de correspondantes désireuses d’être informées des dernières nouvelles de la cour. L’étude de la correspondance permet d’approcher un réseau aristocratique féminin, ses pratiques de publication et les actions que ses membres entreprennent par le biais de l’épistolaire. Cet article s’intéresse également à la correspondance que nouent les deux mémorialistes, Françoise de Motteville et Anne-Marie-Louise d’Orléans, qui reprend les codes des jeux d’écriture mondains. Nous analysons les liens qu’entretiennent chez elles l’écriture épistolaire et l’écriture mémorialiste, la lettre étant commentée ou reprise dans les mémoires. L’étude rend ainsi compte des gestes d’échange, de circulation, de conservation et de réemploi de la lettre par les autrices du xviie siècle. Pratique collégiale, écriture de l’immédiateté, la lettre participe à terme à la construction d’un récit de soi, l’écriture épistolaire trouvant in fine une continuation dans l’oeuvre mémorielle.

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)0.002
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.010
Scholarly communication0.0070.003
Open science0.0000.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.020
GPT teacher head0.271
Teacher spread0.252 · 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
Published2024
Admission routes1
Has abstractyes

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