Bibliographic record
Abstract
Franchising is a system of marketing and distribution where an independent businessperson, the franchisee, is granted the right to market the goods and services of another, the franchisor. As a vehicle for entrepreneurship and investment, franchising allows for efficient expansion of good business practices, the development of intellectual property both domestically and internationally, and the promotion and growth of small businesses. Since the late 1950s, the franchising business format has rapidly expanded throughout the United States. Around the globe, the US concept of franchising is relatively new and has earned an increasing share of international commerce. Franchised businesses worldwide have steadily accrued hundreds of billions of dollars in annual sales — a record of growth that is likely to continue. Numerous countries have responded to this rise in franchising by enacting franchise disclosure laws and, sometimes, franchise relationship laws as well. The franchise sector was first regulated in the 1970s in the United States and Canada. By 1990, they were joined by France and Mexico. As of 2000, thirteen countries had enacted franchise legislation, including Australia, Brazil, China, Taiwan, Indonesia, Malaysia, Romania, and Spain. Currently, over thirty countries, representing about one-third of the nations where franchised businesses operate, have enacted franchise-specific regulation. Increased international franchise activity coupled with a growing recognition that franchising has its own distinctive business model has led the move toward more regulation. However, despite the tremendous growth of international commerce and an increasingly global business climate for which uniform laws would be a true boon, there has been no franchise law equivalent to the Convention on Contracts for the International Sale of Goods. Despite, for example, the creation of the International Institute for the Unification of Private Law (“UNIDROIT”) Model Franchise Disclosure Law in 2002, the laws vary from country to country. The Republic of South Africa is no exception. In comparing South Africa’s new franchising regulations against the regulations of older commercial regulations, this Article examines key features, such as cooling-off periods, the unconscionability doctrine, and penalties for violations, which together set the consumers’ rights orientation of the South African law far from that of other key countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".