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Record W4395087467 · doi:10.1017/9781108891349

Leonard Bernstein in Context

2024· book· en· W4395087467 on OpenAlexaff
Elizabeth A. Wells, Paul R. Laird, Ann Glazer Niren, Mark Kligman, Nadine Hubbs, Barry Seldes, Sally Bick, Daniel E. Callahan, Megan Francisco, Rob Haskins, Jennifer Del Motte, Michael Slon, Katherine Baber, Ralph P. Locke

Bibliographic record

VenueCambridge University Press eBooks · 2024
Typebook
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsMount Allison University
Fundersnot available
KeywordsContext (archaeology)History

Abstract

fetched live from OpenAlex

Designed for students, aficionados of classical music, and historians, this volume offers a wide-ranging, multi-disciplinary and comprehensive view of one of the most important musicians of the twentieth century at his 100th anniversary. Scholars from diverse backgrounds and fields have contributed rich insights into Bernstein's life and work in an approachable style, shedding light on Bernstein's social, professional and ideological contexts including his contemporaries and rivals on Broadway, his artistic collaborations, his celebrity status as a conductor on the international concert circuit, and his involvement in music education via broadcasting. From his early education, through his conducting and composing careers, to his fame as musical and cultural ambassador to the world, this book views Bernstein the man and the artist and provides a fascinating overview of American classical music culture during Bernstein's long career in the public spotlight.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0300.008

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 head0.074
GPT teacher head0.198
Teacher spread0.124 · 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
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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