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Record W7043859937

Voice-in-the-World: An Exploration of Mid-Career Opera Singers’ Non-Musical Stressors and Coping Strategies

2021· dissertation· W7043859937 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsOperaCoping (psychology)FeelingNarrativeStressorDistancingConversationSinging
DOInot available

Abstract

fetched live from OpenAlex

Singers are constantly balancing how they, as subjects, interact with objects in the world to create a consistent product (sound). But singers are also used as objects in the creation of someone else’s work by composers, directors, and companies, etc. This results in a highly unstable and unpredictable career that can upset the inner balance between coping and resilience. Using Interpretative Phenomenological Analysis (IPA), this thesis explores the lived experience of seven elite-level Canadian opera singers through in-depth narratives to discover these performers’ non-musical stressors and coping strategies. The four emergent stress themes (finances, expendability, peripatetic lifestyle, and fatigue) were all accentuated by feeling a lack of control, or lack of agency, and instability. Often, the coping strategies were obfuscated by stress and were in fact harder for the singers to discuss or identify. The three main coping strategies outlined—routines and consistency, emotional self-management, and support network and communication—reflected how the singers tried to create stability and control to find resilience and longevity in the opera business. This thesis ends by bringing awareness to the idea of creator mind versus the singing body—a dichotomy which, I argue, leads to the subjugation of opera singers. This study is not meant to produce definitive conclusions or solutions; rather it is meant to prompt a conversation by focusing on what Heidegger (1927/2010) would call a caring “attunement” towards a deeper understanding of what it is to be an opera singer in Canada.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0110.014
Scholarly communication0.0070.003
Open science0.0020.005
Research integrity0.0010.002
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 head0.121
GPT teacher head0.359
Teacher spread0.238 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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