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Record W4288436679 · doi:10.1017/s1479409822000209

John Field's Russian Landscape and the Early Nineteenth-Century Piano Nocturne

2022· article· en· W4288436679 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNineteenth-Century Music Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPianoMusicalStyle (visual arts)Field (mathematics)ArtIrishArt historyHumanitiesLiteratureHistoryVisual artsLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

This article examines the creation and early dissemination of John Field's nocturnes, tracing this œuvre through initial publications in St Petersburg by Dalmas (1812; H24–25) to the posthumous collected editions by Schuberth and Liszt first released in the 1850s. Inspired by discourse on music and environment, I take the peculiar qualities of Russian night landscapes as a key factor in understanding how these works were composed and then marketed internationally. Although little documentation remains of Field's Russian experiences as described in his own voice, it is possible to reconstruct the place in which he worked through his musical publications, related contemporary descriptions, images and recollections of friends and admirers. These sources shed fresh light on his shift in musical style on relocation from England to Russia. Viewing Field's nocturnes through the lens of this landscape, both real and as imagined by later promoters such as Liszt, offers the opportunity to reach a newly nuanced understanding of Field's array of national identities – Irish, English and Russian – and of his nocturne as a Russia-based idiom.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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: Review · Consensus signal: none
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.000

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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