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Record W2800293008 · doi:10.1080/00085006.2018.1445417

Friedrich Nietzsche, Dmitrii Merezhkovskii, and the Russian Renaissance

2018· article· en· W2800293008 on OpenAlexaffvenue
Ana Siljak

Bibliographic record

VenueCanadian Slavonic Papers · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicNietzsche, Schopenhauer, and Hegel
Canadian institutionsQueen's University
Fundersnot available
KeywordsThe RenaissancePhilosophyArtArt history

Abstract

fetched live from OpenAlex

The artistic, poetic, and literary movement in the years between 1890 and 1917 has long been known as the “Silver Age,” a name that does not convey the movement’s essence and one that was mostly used retrospectively. The artists, philosophers, and writers of the day gave their own name to this cultural flourishing, the “Russian Renaissance,” because they believed they were embarking on a rebirth of literature, culture, art, and religion similar to that of the European Renaissance. In their search for a new aesthetic vision, the Russian Renaissance turned to the classical world, especially ancient Greece. But their view of that culture was distinctly shaped by works of the German philosopher Friedrich Nietzsche. This article will highlight the particular, crucial role of Dmitrii Merezhkovskii in bringing a Nietzschean view of Greece into the Russian Renaissance. Merezhkovskii’s Nietzschean celebration of the classical world, and his belief that this world could reinvigorate Christianity and Russian culture, proved greatly influential for the artists, poets, and philosophers that followed him.

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: none
Teacher disagreement score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.006
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.211
Teacher spread0.196 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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