Consumer Debt Relief in South Africa—Should the Insolvency System Provide for NINA Debtors? Lessons from New Zealand
Bibliographic record
Abstract
Abstract South African natural person insolvency law has remained largely creditor‐orientated despite the international trend to assist over‐indebted debtors. Furthermore, although the South African system provides for a number of debt relief procedures, the entry requirements are of such a nature that most debtors are effectively excluded from any form of relief and therefore bound to their desperate situations. The majority of these excluded debtors fall within the no income and no assets (the so‐called No Income No Asset (NINA) debtors) category‐the main feature of this article. In the South African insolvency system, a person can therefore be ‘too poor to go bankrupt’. With reference to international principles and a thorough comparative study of the New Zealand system, the South African system is analysed, and some recommendations are made in order to provide a more accessible, effective and nondiscriminate system with specific focus on the plight of the NINA debtor. This is done by keeping the complex South African debt and poverty situation in mind as it is acknowledged that any reform should take cognisance of the unique socio‐economic and cultural background. It is recognised that providing relief to the NINA category debtors will have an impact on the economy. However, it is submitted that the exclusion of this group will be even more expensive as it creates an obstacle for these debtors to enter the formal sector and economy, thereby discouraging broader economic growth. Copyright © 2013 INSOL International and John Wiley & Sons, Ltd.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".