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Record W2909176061 · doi:10.26522/gbuujh.v3i0.1673

Art in Early Modern Italy: Artemisia Gentileschi and Caravaggio

2018· article· en· W2909176061 on OpenAlexvenueno aff
Joslin Holwerda

Bibliographic record

Venuethe general brock university Undergraduate journal of history · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBaroquePaintingStyle (visual arts)Period (music)ArtEarly modern periodApprehensionCriticismReputationHistoryArt historyAestheticsVisual artsLiteratureSociologyPsychologyAncient historySocial science

Abstract

fetched live from OpenAlex

This paper compares the careers of two internationally known painters from seventeenth century Rome, one male and one female, to further understand the broader gender relations of early modern Italy. Michelangelo Merisi da Caravaggio and Artemisia Gentileschi are individually known for being Italy’s greatest painters of the Baroque period. As artists, the professional challenges that they faced exemplified the dichotomy between genders in the early modern period. While Caravaggio’s controversial art style and violent lifestyle did not hinder his success, Gentileschi faced persistent apprehension and criticism by her contemporaries, solely because she was a woman working in an almost exclusively male profession. The professional restrictions and limitations that were experienced by female artists in the seventeenth century are represented in the career and reputation of Artemisia Gentileschi. By comparing the art, careers, and reputations of Rome’s most notable painters, this paper offers insight into how art is representative of gender and gender relations in early modern Italy.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.005
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.180
Teacher spread0.161 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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