Protection against unfair competition—African Regional Intellectual Property Organization member states and South Africa
Bibliographic record
Abstract
Abstract This article summarizes the current status of protection against unfair competition in 19 Member States of the African Regional Intellectual Property Organization (ARIPO) as well as South Africa. Since several study countries are Member States to at least one Regional Economic Community (RECs) or customs union, which have introduced regional or sub-regional competition regimes to advance regional integration in this area, the relevant RECs and customs unions are also briefly analysed. This is followed by some reflections on the impact of the African Continental Free Trade Area (AfCFTA) and the AfCFTA’s recently adopted Phase II protocols on Intellectual Property Rights and Competition Policy. The article then examines the different approaches adopted in the study countries to fulfil the obligation to ensure effective protection against unfair competition, as stipulated in Article 10bis(1) of the Paris Convention (PC), and investigates how the concept of ‘honest practices in industrial or commercial matters’ (Article 10bis(2) PC) is interpreted and applied. The article also explores how study countries have implemented the examples of prohibited acts of unfair competition contained in Article 10bis(3) PC, and addresses the question whether additional acts fall within the scope of protection against unfair competition in the study countries. The findings here are presented in such a way that observations from several countries are typically clustered together to exemplify general approaches and categories. The article observes that while countries in the region typically provide some form of legal protection to safeguard fair play in the business sector, study countries represent a variety of legal systems (civil law, common law, a combination of civil law and common law and/or religious law). This influences the way of how they address unfair competition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".