MétaCan
Menu
Back to cohort
Record W2374772458 · doi:10.5206/notabene.v9i1.6605

Zarlino, Anamorphosis, and Cinquecento Italy

2016· article· en· W2374772458 on OpenAlexvenueno aff
Edwin Li

Bibliographic record

VenueNota bene · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTonalityImitationPoliticsAestheticsConservatismEpistemologySchema (genetic algorithms)The RenaissanceSociologyHistoryPsychologyPhilosophySocial psychologyLiteratureArtLawPolitical scienceComputer scienceArt history

Abstract

fetched live from OpenAlex

This paper examines the relationship between Gioseffo Zarlino’s personal considerations and the socio-cultural circumstances in Cinquecento Italy on the basis of anamorphosis—the idea that an object can be understood from multiple angles. Arguably one of the most important theorists of the sixteenth century, Zarlino, although cognizant of chords as vertical constructs, deliberately disguised tonality as modality. This prompts a myriad of questions as to why he did not further develop his theory into a major-minor schema, given that he had already emphasized the Ionian and Aeolian modes in Le Istitutioni Harmoniche. This paper explores the reasons behind his conservatism, arguing that Zarlino’s religious posts and the tumultuous religious-cultural-political climate of late-sixteenth-century Venice influenced his anamorphic inclinations. The paper also attributes his constraint to the prevalent Renaissance concept of the imitation of nature. By looking into the essential qualities of nature, notably eternality, this paper claims that the imitation of nature can explain both the perpetuation of modality and Zarlino’s adoption of tonality. The paper concludes that Zarlino’s belief in God can be seen as an overarching force in his theoretical formulation, positing a hierarchical relationship among the factors discussed.

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 score0.767
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 head0.199
Teacher spread0.169 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueNota beneSame topicRenaissance and Early Modern StudiesFrench-language works237,207