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Record W2996658245 · doi:10.7202/1065068ar

RENAISSANCE – REBIRTH: SOME REMARKS ABOUT THE HUMANISTIC INTERPRETATION OF HISTORY

2019· article· en· W2996658245 on OpenAlexvenueno aff
Andreas Kablitz

Bibliographic record

VenueSurfaces · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanismInterpretation (philosophy)ScholasticismPerfectionLiteraturePeriod (music)NominalismMiddle AgesPhilosophyArtHistoriographyItalian RenaissanceClassicsThe RenaissanceHistoryArt historyAestheticsEpistemologyTheologyLinguistics

Abstract

fetched live from OpenAlex

The author works towards a historical understanding of humanism through his analysis of the notion of rebirth which was a key concept, but under different guise, both in the self-interpretation of the sixteenth century as well as in the appearance, during the nineteenth century, of the term "Renaissance" when it was first used to describe a historical period. However, the contexts of Vasari’s use of the word rinascita and later of Michelet’s use of the word Renaissance differ greatly. Whereas in Vasari, rebirth is meant to reinterpret the relationship of art to nature against nominalism’s views that there are pre-ordained possibilities, in Michelet rebirth is meant to refer to the development of empirical studies of nature and the retrieval of the Greek and Latin program of self-constitution for mankind through the work of reason. Hence, the Middle Ages, and scholasticism especially, are blamed for their suppression of nature. The loss of the importance of art in Michelet's conception of the Renaissance follows logically from the interpretation of this period as a re-establishment of truth. On the contrary, if art is of crucial importance in Vasari's conception of rinascita , it is because art as creation opens all possibilities and, thus, is part of an effort towards perfection.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.234
Teacher spread0.203 · 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
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

Citations1
Published2019
Admission routes1
Has abstractyes

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