New legislative measures in South Africa aimed at combating over‐indebtedness—are the new proposals sufficient under the constitution and law in general?
Bibliographic record
Abstract
Abstract The National Credit Bill codifies a number of fundamental rights of consumers in the credit market. It provides inter alia for a right to information to enable consumers to make informed choices and thereby contributes to one of the purposes of the proposed legislation, namely to provide mechanisms to combat over‐indebtedness. The main purpose of this research is to evaluate the proposed measures in the Bill aimed at combating over‐indebtedness and also to determine to which extent these measures comply with the general constitutional consumer protection demands. In order to achieve this, the relevant guidelines of the INSOL Consumer Debt Report and measures in other jurisdictions will also be considered. Since the South African Constitution does not directly obligate the state to enact specific credit laws and as the Bill seeks, in the spirit of the supreme law, to codify certain basic consumer rights, the new legislative initiatives are to be welcomed. It is, however, submitted that the Bill does not go far enough in achieving its particular aims and objectives and that more could be done to bring South African legislation in line with measures in other jurisdictions. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".