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Changing Social Focussing in the Development of Jazz Music

2015· article· en· W2286550110 on OpenAlexaff
James Hay, J. David Flynn

Bibliographic record

VenueJournal of Sociocybernetics · 2015
Typearticle
Languageen
FieldComputer Science
TopicChaos, Complexity, and Education
Canadian institutionsThe King's UniversityWestern University
Fundersnot available
KeywordsJazzMusicalPeriod (music)Violin musical stylesContext (archaeology)Style (visual arts)PianoCentralitySociologyAestheticsVisual artsHistoryArtMathematicsArt history

Abstract

fetched live from OpenAlex

This paper traces the development of jazz musical styles by relating those styles to the organization of jazz musicians and the social context of American society. The authors use a theory developed by Flynn and Hay (2012) derived from chaos and complexity science. The Flynn/Hay theory states that social focussing (chaos, complexity or order: SF) is directly proportional to internal structure (differentiation: D) and inversely related to external information (centrality: C). In mathematical terms: SF = D/C.The authors of this paper describe the social focussing of jazz styles in terms of being chaotic, complex or ordered. They then relate the styles of social focussing to the differentiation of the social system of jazz musicians, and the centrality inputs from the surrounding American society. Their results demonstrating that the style of jazz at each period from the late 19th century to the present era, is dependent upon the ratio of d/c.They conclude that the same analysis could be applied to subsystems of the jazz system, including the development of jazz styles in different geographic regions, as well as within each band and even over the career of each musician, in a kind of fractal effect, where the shape of social focussing is the same at each level.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.551
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.316
Teacher spread0.175 · 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 teacher head, 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

Citations1
Published2015
Admission routes1
Has abstractyes

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