Cultural Diversity, Cultural Networks and Trade: International Cultural Policy Debate
Bibliographic record
Abstract
This article sketches some of the ways in which the language and concepts of cultural diversity are being taken up internationally. The debate has been driven in part by concerns about the treatment of cultural goods, services and knowledge in trade agreements. But it also involves larger questions about the role of the state, the role of non-state actors in domestic policy formation, and the shape and function of international policy communities comprising both state and non-state actors. The extent of the discussion of cultural diversity internationally is described through new formal and informal cultural networks and work towards an international instrument for cultural diversity to lay out ground rules for international trade, cultural exchange and policy principles to guide governmental responsibilities. The article concludes with analysis of some of these new networks, and investigates why Canada has been so prominent in these international efforts.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.017 | 0.075 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".