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Record W2943724198

Humanasonics: Compositions Inspired by Anthropological Human Universals

2017· dissertation· en· W2943724198 on OpenAlexfundno aff
Paul Anthony Novotny

Bibliographic record

VenueYorkSpace (York University) · 2017
Typedissertation
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsProblem of universalsHumanityUniversality (dynamical systems)Composition (language)Unconscious mindEpistemologyPhilosophyCognitive scienceLinguisticsPsychology
DOInot available

Abstract

fetched live from OpenAlex

Human universals are the commonalitiesthe onenessof mankind, and anthropology is charged with their study. Universals form a general, immutable foundational theory of humanity. The purpose of this thesis is to show how that theory can be used to inspire composition. \n \nHuman Universals, Donald E. Browns seminal 1991 work is an exhaustive and comprehensive overview of the subject and provided my understanding of anthropological human universals. Music composition is viewed as the organization of contrasting soundssonics. Humanasonics is a new word that names the concept of deriving inspiration from human universals for music composition. \n \nThis suite of program music is structured in four movements, totalling approximately twenty minutes, for jazz orchestra. Each movement is inspired by a human universal trait or condition. \n \nThe conclusion asserts that when music is metaphorically based on immutable human universality, it will lead to an inherent understanding, unconscious or conscious, of the work.

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: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.013
Scholarly communication0.0030.004
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.020
GPT teacher head0.259
Teacher spread0.239 · 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
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
Published2017
Admission routes1
Has abstractyes

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