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Record W2890530461 · doi:10.17805/ggz.2018.3.5

Дьявол на сцене «Белл Сэвидж»: эпизод антитеатральной полемики в Англии XVI–XVII вв.

2018· article· ru· W2890530461 on OpenAlexfundno aff
Виктория Андреевна Колесник, Владимир Сергеевич Макаров

Bibliographic record

VenueГоризонты гуманитарного знания · 2018
Typearticle
Languageru
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsnot available
FundersUniversity of Victoria
KeywordsArt

Abstract

fetched live from OpenAlex

<p>В статье рассмотрены исторический, культурный и религиозный контекст легенды о дьяволе, внезапно появившемся на сцене лондонского театра (в наиболее известном случае — трактира «Белл Сэвидж»). Авторы предлагают анализировать ее в рамках общего исследования театральной полемики XVI — первой половины XVII вв. с ее взаимовлиянием литературных жанров. Традиция связывать происхождение театра с дьявольскими силами отчасти подпитывается через восприятие актеров и зрителей как вольных или невольных слуг «альтернативной иерархии», восходящей к дьяволу — однако важна и интерпретация «дьявола на сцене» как предупреждения о необходимости покаяния.</p>

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0600.031

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 head0.022
GPT teacher head0.212
Teacher spread0.190 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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