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Record W2740232994 · doi:10.12957/abusoes.2017.27771

DIÁLOGO ENTRE H. P. LOVECRAFT E ARTHUR MACHEN: UMA ANÁLISE COMPARATIVA DE THE DUNWICH HORROR E THE GREAT GOD PAN

2017· article· pt· W2740232994 on OpenAlexaff
Shirley de Souza Gomes Carreira

Bibliographic record

VenueAbusões · 2017
Typearticle
Languagept
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

RECEBIDO EM 04 MAR 2017 APROVADO EM 30 MAR 2017 Em seu ensaio sobre o horror sobrenatural na literatura, H. P. Lovecraft dedica parte de um capítulo à obra de Arthut Machen, por quem nutria admiração e a quem atribuía a capacidade de elaborar um “êxtase do medo” inalcançável aos outros escritores do gênero. The Great God Pan , primeira e mais conhecida obra de Machen, foi publicada no ano em que Lovecraft nasceu e este a menciona mais de uma vez em seus escritos, admitindo publicamente que ela o havia inspirado na escrita de alguns dos seus textos. Este trabalho propõe a análise do conto “ The Dunwich Horror ”, de Lovecraft, e da novela The Great God Pan , de Machen, a fim de verificar os pontos de convergência entre as obras. // In his essay on supernatural horror in literature, H. P. Lovecraft devotes part of a chapter to the work of Arthut Machen, whom he admired and to whom he attributed the ability to elaborate a “rapture of fear” unachievable to other writers of the genre. The Great God Pan , Machen’s first and best-known work, was published in the year Lovecraft was born and he mentioned it more than once in his writings, publicly admitting that it had inspired him in writing some of his texts. This work proposes to analyze Lovecraft’s short story “The Dunwich horror” and Machen’s novella The Great God Pan, in order to verify the points of convergence between them. DOI: 10.12957/abusoes.2017.27771

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)0.000
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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0040.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.028
GPT teacher head0.273
Teacher spread0.245 · 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.

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
Published2017
Admission routes1
Has abstractyes

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