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Record W2166885719

Faddists, enthusiasts and Canadian divas: a model of the recorded music market *

2012· preprint· en· W2166885719 on OpenAlexaboutno aff
Martin Richardson, Simon Wilkie

Bibliographic record

VenueRePEc: Research Papers in Economics · 2012
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicDigital Platforms and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexActive listeningDiversity (politics)Sign (mathematics)Broadcasting (networking)IncentiveAdvertisingWelfareTasteBusinessMusic industryTelecommunicationsEconomicsComputer scienceMicroeconomicsMathematicsPolitical scienceMarket economySociologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

This paper constructs a model of the provision of commercial music in which some consumers (enthusiasts) enjoy diversity and others (faddists) prefer to follow what is popular. Record companies sign up bands, only some of whom will 'succeed' - a process modelled in a number of alternate ways - and radio stations broadcast recordings. Consumers hear music on the radio and purchase recordings, where the likelihood of purchase depends, in part, on the extent of radio airplay for a particular recording. We show that consumers' taste for diversity leads to under-entry in general and we illustrate the working of the model by considering the impact of a local content quota in broadcasting. It is shown that a quota that restricts the airtime devoted to foreign music induces a shift in the pattern of band entry into 'international' genres. But a mild quota is welfare-improving in this model: even though the diversity of local music is reduced, the quota increases the number of new entrants, drawn in by the increased profitability of success. We also discuss the consequences of a quota that requires increased broadcasting of 'new' music and show that, while the addition of the 'new' band component decreases the total amount of time devoted to listening to the radio by consumers (yielding a welfare loss), it does nothing to a record company's incentives to sign up new bands.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.041
GPT teacher head0.238
Teacher spread0.197 · 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.

Study designOther design
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

Citations2
Published2012
Admission routes1
Has abstractyes

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