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Record W7042364749

Piano Music of Georgs Pelēcis : a study of selected works

2017· dissertation· en· W7042364749 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typedissertation
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Music Media and Technology
Fundersnot available
KeywordsPianoStyle (visual arts)RhythmOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses three works for piano by the Latvian composer Georgs Pelcis: Prelude in F major from Descendente per Tertias (2008), Marche funbre (1998), and New Year's Music (1977).Analysis of each work's form, melody, harmony, and rhythm reveal characteristic features of the composer's style such as diatonicism, major-minor modal interplay, and the use of persistent rhythmic patterns.Published interviews with the composer are used in order to establish his aesthetic principles.Where appropriate, other works (by Pelcis, and others) are referenced as possible sources of inspiration.Aspects of performance practice for each work are also discussed, providing suggestions for pianists who are interested in performing these works. AbstraitCe travail se concentre sur trois oeuvres pour piano du compositeur letton Georgs Pelcis:Prlude en fa majeur, extrait de Descendente per Tertias (2008), Marche funbre (1998), et New Year 's Music (1977).Ces trois pices sont analyses avec des paramtres musicaux tels que la forme, la mlodie, l'harmonie et le rythme, qui rvlent des traits caractristiques du style du compositeur: le diatonisme, l'interaction entre majeur et mineur, et des motifs rythmiques continuels.Les principes esthtiques du compositeur sont dfinis grce des entretiens publis avec lui.Le cas chant, d'autres oeuvres de Pelcis ou d'autres compositeurs sont rfrences comme de possibles sources d'inspiration.Chaque pice a galement fait l'objet d'une tude des diffrents aspects de l'interprtation, afin de fournir des suggestions aux pianistes souhaitant jouer ces oeuvres.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.032
GPT teacher head0.242
Teacher spread0.210 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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