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Evil Medieval

2020· reference-entry· en· W4243603714 on OpenAlexaff
James Deaville

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsHistoryArtNarrativeOmenLiteratureArt historyClassicsArchaeology

Abstract

fetched live from OpenAlex

During the late 1960s and early 1970s, a noticeable shift occurred in the plots and soundtracks of narrative film in the United States. The genre of horror came to occupy a leading position among new releases (Rosemary’s Baby, 1968; The Devils, 1971; The Exorcist, 1973; The Omen, 1976), accompanied by music that would invert the signification of the church’s most sacred spiritual heritage: Latin became the language of the devil and chant his music. This chapter explores the historical and cultural bases for this turn to the dark side, to an evil medieval, by examining such concurrent events as Vatican II, the publication of Anton LaVey’s The Satanic Bible, the Charles Manson murders, and the Vietnam War.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: Other
Teacher disagreement score0.984
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.007
Scholarly communication0.0070.002
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.003

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 head0.035
GPT teacher head0.319
Teacher spread0.284 · 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.

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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same topicGothic Literature and Media AnalysisFrench-language works237,207