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Record W1893174401 · doi:10.12745/et.18.1.2587

Margaret Shewring, ed. <i>Waterborne Pageants and Festivities in the Renaissance: Essays in Honour of J.R. Mulryne</i>. Aldershot: Ashgate, 2013. Pp xxv, 439.

2015· article· en· W1893174401 on OpenAlexvenueno aff
Steve Mentz

Bibliographic record

VenueEarly Theatre · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHonourThe RenaissanceArtArt historyPerformance artMedia studiesSociologyHumanitiesPolitical scienceLaw

Abstract

fetched live from OpenAlex

This dense and detailed collection of case studies provides an authoritative overview of waterborne festivities in Renaissance Europe.The volume is presented as a festschrift for J.R. Mulryne, who directed the research program 'Festivals of the European Renaissance' at Warwick's Centre for the Study of the European Renaissance and whose biography introduces this volume in a two-page head note (ix-x).The twenty-one essays range across different European geographies, with concentrations in France, Italy, and England in the later sixteenth century.Some chapters cover more than one location, but a rough count indicates seven chapters primarily exploring festivals in Italy, six on festivals in England, four on French festivals, and smaller numbers concerning festivals in Spain, Denmark, or other locations.Margaret Shewring's introduction frames the project as exploring 'the cultural significance of th[e] liquid environment' (1) for Renaissance Europe.She celebrates the diversity of the festivals as a 'testament to the wealth of commentary invited by waterborne events' (1) and suggests that this volume aims to produce a 'coherent overview' designed to stimulate 'further study of this important topic' (7).With equal attention to the engineering feats and cultural meanings of waterborne spectacles, the succeeding chapters provide

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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.

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

Citations1
Published2015
Admission routes1
Has abstractyes

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