When low level of constraint and effectiveness go hand in hand: The example of the 2005 Convention
Bibliographic record
Abstract
Abstract The year 2022 marks 15 years since the entry into force of the United Nations Educational, Scientific and Cultural Organization’s 2005 Convention on the Protection and Promotion of the Diversity of Cultural Expressions. Among its objectives, this treaty aims at acknowledging the specific nature – economic and cultural – of cultural activities, goods, and services, reaffirming the sovereign right of states to adopt or implement measures they deem appropriate for the protection and the promotion of the diversity of cultural expressions as well as reinforcing international cooperation for more balanced cultural exchanges. Since its adoption, this treaty has been criticized for its low level of constraint. However, data collected over the years show that parties rely extensively on the Convention to undertake diverse initiatives to achieve the treaty’s objectives. Based on concrete examples, this article aims to show that the effectivity of a legal instrument does not only rely on its degree of constraint but also on other factors, including monitoring mechanisms put in place in the context of its implementation.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.031 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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".