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Record W1540720425 · doi:10.16995/dscn.51

Every Track You Take: Analysing the Dynamics of Song and Genre Reception Through Music Downloading

2014· article· en· W1540720425 on OpenAlex
Matthew Woolhouse, James Renwick, Dan Tidhar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueDigital Studies / Le champ numérique · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMusicalDownloadUploadMainstreamPopular musicHistoryMedia studiesAdvertisingArtLiteratureSociologyComputer scienceWorld Wide WebPhilosophyTheologyBusiness

Abstract

fetched live from OpenAlex

<p id="d2e68">Using a music-download database provided by the Nokia Corporation, this paper explores three primary questions: (1) Do different musical genres create different patterns of downloading? (2) Do different countries download a particular song in different ways? And (3) how do different events affect downloading? Question (1) is studied in relation to representative songs from the pop, rap and rock genres, and reveals rock to be significantly different from pop and rap in a number of key respects. Question (2) investigates the downloading patterns of a mainstream pop song in Brazil, Germany, Italy, and Mexico. Using Kolmogorov-Smirnoff tests to compare the countries’ download distributions, Brazil is found to be substantially dissimilar to the other countries. And Question (3) is explored with respect to types of event, the first "musical" (Adele's Grammy Awards triumph in February 2012), and the second "extra-musical" (the death of Michael Jackson in June 2009). The extra-musical event is found to have had a far greater effect on downloading patterns than the musical event. The findings are discussed in relation to various factors, including musical genres, the music industry, social media, and globalisation. <p id="d2e76"> À l’aide d’une base de données de téléchargement de musique fournie par Nokia Corporation, cet essai explore trois questions principales : (1) Est-ce que différents genres de musique créent différents modèles de téléchargement? (2) Est-ce qu’une chanson en particulier est téléchargée de différentes façons dans différents pays ? Et (3) comment différents événements affectent-ils le téléchargement ? La question (1) est étudiée relativement à des chansons représentatives des genres pop, rap et rock, et révèle que le rock est sensiblement différent des musiques pop et rap à bien des égards. La question (2) examine les modèles de téléchargement d’une chanson pop au Brésil, en Allemagne, en Italie et au Mexique. Faisant appel aux tests de Kolmogorov-Smirnov pour comparer les distributions de téléchargement de ces pays, on a découvert que le Brésil est sensiblement différent des autres pays. Et à la question (3), on explore les types d’événements, premièrement un événement "musical" (le triomphe d’Adele lors des Grammy Awards en février 2012), et deuxièmement un événement "extra-musical" (la mort de Michael Jackson en juin 2009). On a constaté que l’événement extra-musical a eu un effet beaucoup plus important sur les modèles de téléchargement que l’événement musical. Les constatations font l’objet de discussions relativement aux divers facteurs, y compris les genres musicaux, l’industrie de la musique, les médias sociaux et la mondialisation.

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.

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)0.000
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 score0.184
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.040
GPT teacher head0.227
Teacher spread0.187 · 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