Sharing music files: Tactics of a challenge to the industry
Bibliographic record
Abstract
The sharing of music files has been the focus of a massive struggle between representatives of major record companies and artists in the music industry, on one side, and peer-to-peer (p2p) file-sharing services and their users, on the other. This struggle can be analysed in terms of tactics used by the two sides, which can be classified into five categories: cover-up versus exposure, devaluation versus validation, interpretation versus alternative interpretation, official channels versus mobilisation, and intimidation versus resistance. It is valuable to understand these tactics because similar ones are likely to be used in ongoing struggles between users of p2p services and representatives of the content industries.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.028 | 0.040 |
| Scholarly communication | 0.026 | 0.019 |
| Open science | 0.002 | 0.023 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".