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Record W7039970517

‘Neo-Gothic Clairvoyance and Palingenetic Myth in Late Soviet Czechoslovakia and Post-Soviet Israel: Pavel Kohout’s The Premonitions of St Clara (1980) and Its Film Adaptations’

2022· article· en· W7039970517 on OpenAlexaboutno aff

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMythologyTopos theoryCzechMacabreGermanGirlHEROPsychicMiracle
DOInot available

Abstract

fetched live from OpenAlex

Pavel Kohout’s bestselling novel The Premonitions of St Clara (Nápady svaté Kláry), whose first German edition was published in\nHamburg in 1980, and first Czech edition in Toronto in 1981, describes a commotion caused by a psychic teenage girl called Clara\nin an unnamed Communist-run small provincial Czech town in the mid-1960s. My article traces how the novel and its adaptations\n– a 1980 German-language film by Vojtěch Jasný and a 1996 Israeli full-length feature by Ari Folman and Ori Sivan – transform a\nhost of cultural topoi across a transnational setting, for different reasons and to varying effects. Such topoi include, among others,\nthe clairvoyant child; the lustful male villain; and the unbeliever to whom the existence of the supernatural is eventually proven.\nAlthough Kohout’s book and its derivatives do not involve vampires, doppelgängers, pedicides and haunted castles, in my opinion,\nthey nevertheless qualify as (neo-)Gothic, because of the book’s and the films’ Gothic-like focus on remote settings (such as the\nCzech or Israeli backwaters) and on the mysterious, the violent and the macabre (as some of the female teenager’s prophesiescome-true entail a flood and an earthquake).

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.015
Scholarly communication0.0070.002
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.292
Teacher spread0.254 · 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
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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDuo Research Archive (University of Oslo)Same topicGothic Literature and Media AnalysisFrench-language works237,207