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Record W2043204313 · doi:10.1142/s0218495812500100

CREATING AN INDEPENDENT MUSIC BUSINESS IN CANADA: A CASE STUDY

2012· article· en· W2043204313 on OpenAlexaffabout
CORA PETTIPAS, Kalinga Jagoda

Bibliographic record

VenueJournal of Enterprising Culture · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsMount Royal University
Fundersnot available
KeywordsExploratory researchBusinessBusiness developmentMarketingKnowledge managementPublic relationsComputer scienceSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

The goal of this research is to contribute to a pragmatic knowledge of building a Canadian small business for an independent music artist who does not know where to start in creating a business. It is meant to be an initial guide for musicians planning to consider this form of business development, as opposed to signing with a label, or as a way to increase the likelihood of becoming noticed by a label. This research paper is initial and exploratory in 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)0.002
metaresearch head score (Gemma)0.005
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 score0.091
Threshold uncertainty score0.662

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0410.006
Scholarly communication0.0060.001
Open science0.0030.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.046
GPT teacher head0.314
Teacher spread0.268 · 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

Citations4
Published2012
Admission routes2
Has abstractyes

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