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Record W110639048 · doi:10.15173/mjc.v3i0.233

The Control and Dissemination of Music in Corporate Controlled Markets

2006· article· en· W110639048 on OpenAlexaffvenue
Robert Petti

Bibliographic record

VenueThe McMaster Journal of Communication · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsMcMaster University
Fundersnot available
KeywordsControl (management)BusinessEconomicsManagement

Abstract

fetched live from OpenAlex

For the radio industry, music has become a tool for attracting listeners with the purpose of providing a specific demographic audience for corporate advertisers. As profit increasingly becomes a predominant focus, individual artistic expression and limited opportunity become a growing concern for aspiring musicians, producers and songwriters. This essay begins by demonstrating what hopeful artists often encounter when they begin their journey within the realm of the music business. It will be argued that artistic integrity often becomes compromised in a business where powerful gatekeepers often shape and dictate cultural trends that optimize consumer consumption. This essay will explore how illegal business practices flourish, as payola (pay for play) becomes a way of securing limited airplay within a radio station’s playlist. In a business where music is regularly selected for its profit potential, music has become a way of shaping popular culture rather than reflecting its true nature.

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)0.006
metaresearch head score (Gemma)0.021
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 score0.017
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.019
Scholarly communication0.0170.014
Open science0.0010.005
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.211
Teacher spread0.191 · 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

Citations11
Published2006
Admission routes2
Has abstractyes

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