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Record W2156643799 · doi:10.1017/s1479409814000366

Fact and Fiction in the Life Story of Luigi von Kunits

2014· article· en· W2156643799 on OpenAlexaffabout
Robin Elliott

Bibliographic record

VenueNineteenth-Century Music Review · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsViolinSymphonyMusicalArt historyBartokArtChamber musicHistoryVisual arts

Abstract

fetched live from OpenAlex

Luigi von Kunits (1870–1931) had a substantial impact on classical music in Toronto. Born and educated in Vienna, he emigrated to Chicago in 1893 and then moved to Pittsburgh in 1896 as the concertmaster of the Pittsburgh Orchestra. After 17 years in the USA, he returned to Vienna for two years, before moving to Toronto to take up a teaching position at the Canadian Academy of Music. From the time of his arrival in Toronto in 1912 to his death in 1931 he was active on many fronts: teaching violin, composing, editing The Canadian Journal of Music (1914–1919), performing as a chamber musician and violin soloist, and serving as the conductor of the Toronto Symphony Orchestra (1922–1931). To many he seemed the very embodiment of the great Central European musical tradition: a pupil of Bruckner and Hanslick, associated with Brahms and acquainted with celebrated European musicians and composers. Much of what we know about Kunits derives from statements issuing from the musician himself or his immediate circle, with little or no corroborating evidence to support his assertions. As a result, it is difficult at this remove to separate fact from fiction. This article takes stock of the sources of information that are available and attempts to construct as accurate an account of his life and activities as possible.

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)0.003
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.007
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.038
GPT teacher head0.234
Teacher spread0.195 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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