MétaCan
Menu
Back to cohort
Record W628276831 · doi:10.5860/choice.39-3173

Harlequin unmasked: the commedia dell'Arte and porcelain sculpture

2002· article· en· W628276831 on OpenAlexaboutno aff

Bibliographic record

VenueChoice Reviews Online · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsSculptureArtPaintingVisual artsExhibitionThe artsDecorative artsEntertainmentArt historyVisual arts education

Abstract

fetched live from OpenAlex

The commedia dell'arte began in Italy as irreverent, improvised street theatre and is best known for its exuberant characters, specifically Harlequin, Pantalone, Pulcinella, Scaramouche, and Colombine, among others. Since the sixteenth century, these personalities have inspired paintings, engravings, and porcelain sculptures. Encompassing theatre, court culture, masquerades, and the decorative arts, this splendidly illustrated and engaging book offers original perspectives on porcelain commedia figures while also making an important contribution to the study of the commedia dell'arte. The volume focuses on nearly 150 porcelain sculptures as it tells the story of the commedia dell'arte's transformation into sculpture. Why were the figures made? Why do they appear as they do? What inspired their gestures and costumes? How did street-theatre themes become integrated into court life and entertainment? Examining these delightful porcelain figures in greater breadth and detail than ever before, this book is essential for those interested in theatre, painting, costume, and the decorative arts. This catalogue accompanies an exhibition at the Gardiner Museum of Ceramic Art, Toronto, from 21st September 2001 to 20th January 2002.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.006
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.110
GPT teacher head0.270
Teacher spread0.160 · 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

Citations4
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueChoice Reviews OnlineSame topicShakespeare, Adaptation, and Literary CriticismFrench-language works237,207