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Record W2595098500 · doi:10.7202/1038947ar

Ethics and Musical Language: A Gramscian Reading of Dallapiccola’s Liriche greche and Their Influence

2017· article· en· W2595098500 on OpenAlexvenueno aff
Jamuna Samuel

Bibliographic record

VenueIntersections Canadian Journal of Music · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical theory and Gramsci
Canadian institutionsnot available
Fundersnot available
KeywordsLyricsReading (process)MusicalNexus (standard)PoetryLiteraturePeriod (music)PoliticsArtHistoryLinguisticsAestheticsPhilosophyLawPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Luigi Dallapiccola (1904–75)—a pioneering figure as serialist, composer of protest music, and trailblazer for the avant-garde—wrote hisGreek Lyricssong cycle (1942–5) as an escape from wartime anxiety. I locate theLyricswithin a nexus of technique, text setting, and ethical engagement. That complex resonated with the younger composers Berio, Nono, and Maderna, each responding in the postwar period with settings from the same collection, Quasimodo’s 1940 free translation of classic Greek lyrics. I examine Quasimodo’s ethics, placing his poetry and Dallapiccola’s settings within Gramsci’s notions of language and politics, which were highly influential on postwar Italian composers.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.024
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0020.003
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 head0.061
GPT teacher head0.348
Teacher spread0.287 · 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 designTheoretical or conceptual
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

Citations1
Published2017
Admission routes1
Has abstractyes

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