Generalizing case-based analyses in the study of global music consumption
Bibliographic record
Abstract
Using large-scale analysis of a music-download database provided by MixRadio, a leading online music-service provider formerly under Nokia ownership, this paper investigates the following in relation to global-music consumption: (1) differences in the downloading trajectories of various musical genres; (2) the extent to which downloading trajectories are invariant with respect to countries and/or genres; and (3) possible links between the downloading behaviour of various genre-defined user subgroups and pre-existing music-personality studies. Substantial differences were observed between download trajectories pertaining to pop, rap, rock and metal—metal, in particular, was seen to exaggerate features of rock's trajectory. Of the genres studied, metal was found to have the only invariant trajectory, seemingly impervious to the local conditions of the country in which it was downloaded. Similarly, musical styles within Brazil were found to be downloaded in more or less the same way, in contrast to the UK where download trajectories varied with musical genre. Lastly, the analysis demonstrated a statistical link between pre-existing music-personality research and patterns of downloading within the metadata, suggesting that different downloading behaviours are due, in part, to differences in personality. Au moyen d’une analyse à grande échelle d’une base de données de téléchargement de musique fournie par MixRadio, un fournisseur principal de service de musique en ligne qui appartenait auparavant à Nokia, cet article examine ce qui suit en ce qui concerne la consommation musicale : (1) les différences de trajectoires de téléchargement en ce qui concerne les divers genres de musique; (2) la mesure dans laquelle les trajectoires de téléchargement sont invariantes selon les pays et/ou les genres; et (3) des liens possibles entre le comportement de téléchargement de divers sous-groupes d’utilisateurs dont le genre est défini et les études de personnalité musicale actuelles. Des différences importantes ont été observées entre les trajectoires de téléchargement en ce qui concerne les genres pop, rap, rock et métal — métal, en particulier, a été perçu comme une exagération des caractéristiques de la trajectoire du rock. De tous les genres étudiés, on a constaté que seul le métal avait une trajectoire invariante, apparemment insensible aux conditions locales des pays où il a été téléchargé. De la même façon, on a constaté que les styles musicaux téléchargés au Brésil l’étaient plus ou moins de la même façon, contrairement au Royaume-Uni, où les trajectoires de téléchargement variaient selon le genre musical. Enfin, l’analyse a démontré un lien statistique entre les recherches de personnalité musicale actuelles et les modèles de téléchargement au sein des métadonnées, ce qui suggère que différents comportements de téléchargement sont dus, en partie, aux différences de personnalité.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".