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Record W2797876802 · doi:10.4000/framespa.4553

Oublier la Renaissance, désapprendre l’humanisme : Le premier Baroque entre exploitation des acquis et table rase imaginaire

2018· article· fr· W2797876802 on OpenAlexaff
Itay Sapir

Bibliographic record

VenueLes Cahiers de Framespa · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsArtBaroqueHumanitiesArt history

Abstract

fetched live from OpenAlex

Si l’histoire de l’art situe, traditionnellement, une coupure nette entre le maniérisme tardif, encore sous l’emprise de la Renaissance et de l’humanisme, et la révolution qui donna naissance au baroque, les historiens de l’art s’étant penchés sur la question ne sont pas dupes : Caravage, tout en revendiquant sa différence et la nouveauté éclatante de son art, a appris énormément des œuvres qu’il découvre d’abord en Lombardie, puis à Rome. La tension entre continuité et rupture, entre ce qui reste et ce qui change, a toujours été un des thèmes majeurs sur lesquels devaient se prononcer les historiens de l’art. Cet article a comme objectif de réviser le récit de l’apparition du Baroque en évitant à la fois le mythe de la table rase et la méprise (et le mépris) du déjà-vu ; en expliquant comment Caravage, et d’autres après lui – particulièrement Jusepe de Ribera – ont cherché à garder vivant le souvenir de certains acquis importants de l’art des prédécesseurs tout en oubliant activement des normes, des règles et des idéaux.

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)0.002
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: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.020
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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