Digital Cultural Governance: Regulation Issues, AI Challenge and Business Partnerships Global watch on culture and digital trade, n°33). International Federation of Coalitions for Cultural Diversity.
Bibliographic record
Abstract
The April report begins with the visit of US President Joe Biden in Canada and the concerns expressed by a collection of US-based business groups regarding the Canadian Online Streaming Act and its compatibility with the provisions of the Canada-United States-Mexico Agreement (CUSMA). The report also discusses an industry letter from music streaming services regarding anticompetitive and unfair practices from Apple. In addition, the report emphasizes the struggle for subscribers and geographical expansion among online platforms, focusing on the new pan-African streaming service established by South African media group MultiChoice, Comcast’s NBCUniversal and Sky, as well as on the debates about content spending from Netflix and European broadcasters. Finally, the report turns to new partnerships and business plans, dealing with discussions about the treatment of artificial intelligence (AI) tools by the Writers Guild of America and with the agreement between Universal, Deezer and TIDAL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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 teacher head, 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".