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Record W7117573980 · doi:10.56620/rm.2025.4.128-144

Russian Music in Marc-André Hamelin’s Performing Practice (Part 1)

2025· article· ru· W7117573980 on OpenAlexaboutno aff
И В Сухорукова

Bibliographic record

VenueRussian musicology. · 2025
Typearticle
Languageru
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRepertoirePianoMelodyConcertoMusicalPerforming artsGermanTonalityPerfectionPeriod (music)

Abstract

fetched live from OpenAlex

Canadian pianist and composer Marc-André Hamelin (b. 1961) is an expert in Russian music. His repertoire includes all the piano sonatas by Alexander Scriabin, Nikolai Medtner and Samuil Feinberg, the piano concertos of Sergei Rachmaninoff, Dmitry Shostakovich and Rodion Shchedrin. He pertains to the small number of pianists who promote the music of the Russian avant-garde and rarely performed composers (Georgy Catoire, Nikolai Roslavets). In this article, attention is focused on Hamelin’s interpretation of works by Russian composers of the turn of the 19th and the 20th centuries — Scriabin, Rachmaninoff and Medtner. A central place in the pianist’s repertoire is held by the music of Medtner, whose compositions induce Hamelin to contemplate. The performer is attracted, first of all, to the detailed quality of Medtner’s piano texture. In Scriabin’s sonatas, Hamelin experiments with sound, disclosing the contrasting boundaries of the composer’s musical world — intellectual perfection and the “outbursts” of emotions. In Rachmaninoff’s music, he accentuates attention on the diversity of the timbral colors of the piano, the palette of strokes and dynamic shadings, disclosing before the listeners the pianistic qualities of the composer’s thought. Special attention in the article is given to the placing of the fingerings in Rachmaninoff’s works carried out by Hamelin upon commission of the German publishing house G. Henle Verlag. It is noted that the pianist’s decisions of fingering are stipulated by various performing goals: the necessity to accentuate attention on the melodic lines, to achieve a conciseness of articulation, to even out a line in a passage in terms of its sound.

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)0.000
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 score0.261
Threshold uncertainty score0.519

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.003
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.265
Teacher spread0.240 · 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
Published2025
Admission routes1
Has abstractyes

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