Comparative Frameworks in EAC Competition Law: An Analysis of São Tomé and Príncipe's Implementation Context
Bibliographic record
Abstract
The East African Community (EAC) Competition Law aims to promote fair competition in member states' markets. São Tomé and Príncipe is one of EAC's least developed countries, making its implementation context unique. The study employs comparative analysis to assess the effectiveness of EAC Competition Law in São Tomé and Príncipe, drawing insights from existing literature and official documents. São Tomé and Príncipe has introduced specific provisions for small-scale businesses, which represents a significant departure from full alignment with EAC standards. This finding highlights the need for tailored legal frameworks in developing economies. The analysis underscores the importance of adapting international competition law to local contexts to ensure effective implementation and benefits for all stakeholders. São Tomé and Príncipe should consider developing a comprehensive enforcement mechanism, including training for officials and awareness campaigns among businesses.
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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 | 0.016 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".