Treatment of Cultural Services in Central American Countries’ Preferential Trade Agreements
Bibliographic record
Abstract
Cultural products (including goods and services) encompass visual, performing and literary arts, as well as newspapers, magazines, books, films, video and music recordings, radio and television, either in traditional or digital format. To the extent that they reflect the cultural identities of states, their treatment in international trade has been debated as to whether, or the extent to which, they should be exempted from trade obligations. The proliferation of preferential trade agreements and of digital platforms has rendered the debate ever more salient. The article summarizes the provisions on cultural services in Central American countries’ preferential trade agreements and discusses the scope of these provisions, in light of the cultural policy measures involved and states’ ability to pursue cultural policies. The countries considered are those belonging to the Central American Common Market, namely Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, and Panama. These countries share some characteristics which make them worth considering in regard to the trade and culture debate. They also vary widely with respect to the number and scope of their commitments and/or exceptions relating to culture within the preferential trade agreements to which they are parties. In turn, such significant variations are primarily attributable to the importance each Central American country attaches to the protection of its cultural sector.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".