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Record W7061933682

Seeking Vocal Alignment

2023· dissertation· en· W7061933682 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsMusicalCoherence (philosophical gambling strategy)Process (computing)Framing (construction)SingingHeuristic
DOInot available

Abstract

fetched live from OpenAlex

Analyzing his own research-creation over the years, the author uses a framework around a heuristic notion of alignment to analyze the quest for coherence between his sense of self and his artistic practice. Although this quest has characterized his personal and artistic trajectory, the model offers a distinct potential to help other research-creation artists locate and address areas of misalignment (friction points between their art and their self), prompting or framing their own processes of seeking alignment. Seeking alignment is both a process of self-reflection and a research-creation method that leads to discernible shifts in an artist’s life and practice. \n \nThe author has evolved this notion of alignment from the more specific term vocal alignment, commonly used in vocal technique and pedagogy. His conception of vocal alignment includes and goes beyond the physiological alignment of different body systems designed to optimize the production of vocal sound, giving equal importance to both semantic interpretations of the word voice. It asks: how can an artist align the vocal sounds their body produces with their artistic, personal, social, and political voice? \n \nThis thesis investigates the author’s process of seeking vocal alignment through his voice-based artistic work. Each of the three core chapters is preceded and followed by sections called “Alignments,” in which self-reflexive and auto-ethnographic writing provides insight into his research-creation process. The reader is invited to engage with these artistic works through sections called “Exhibits” (Lip Service, Anthropologies imaginaires, and Bijuriya). \n \nChapter 1 investigates the author’s critical stance on musical, social, theoretical, and practical aspects of musical life in the Canadian new music scene, highlighting the colonialist assumptions, cultural prejudices, and power imbalances that impact it. \n \nChapter 2 is an analysis of the author’s project Anthropologies imaginaires (2014). He analyzes how his use of voice, body, satire, deception, humour, and laughter formulates a critique of coloniality. \n \nChapter 3 focuses on the author’s solo interdisciplinary drag performance Bijuriya (2021-22). He analyzes the different musical, vocal, and performative strategies that coexist in the piece, and his exploration of different relations to the body and the voice, in line with the concept of vocal alignment.

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)0.011
metaresearch head score (Gemma)0.017
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0070.016
Scholarly communication0.0130.011
Open science0.0020.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.002

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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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
Published2023
Admission routes1
Has abstractyes

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