Negotiation of the UNESCO Convention on the Protection and Promotion of the Diversity of Cultural Expressions
Bibliographic record
Abstract
Summary Since its beginning in September 2004, the negotiation of the Convention on the Protection and Promotion of the Diversity of Cultural Expressions has raised a great deal of interest and even tension among UNESCO member states. A record number of members and non-governmental observers have been involved, and, on many occasions, the debates have taken place in overflowing rooms. During the study of the draft convention by Commission IV, on 77 October 2005, the debate even had to be temporarily suspended in order to find a larger room. Obviously, the negotiations, which addressed head on the problem of the interface between trade and culture, dealt with a very sensitive matter. On 20 October 2005, the convention was finally adopted by the UNESCO General Conference (148 votes for, two against, and four abstentions). Considered to be a historical moment by several delegations in their closing declaration, the results of this decision was vigorously denounced by the United States. It went so far as to assert, in a declaration made public by the US embassy in Paris, that the proposed convention was deeply flawed since it dealt with trade rather than culture and that it therefore fell outside UNESCO jurisdiction. How was such a result achieved? This article attempts to clarify these issues, following the negotiation step by step as well as the dynamic that led to the ultimate result.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".