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Record W2103535062 · doi:10.1002/iir.1211

Consumer Debt Relief in South Africa—Should the Insolvency System Provide for NINA Debtors? Lessons from New Zealand

2013· article· en· W2103535062 on OpenAlexvenueno aff
Hermie Coetzee, Melanie Roestoff

Bibliographic record

VenueInternational Insolvency Review · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsDebtorCreditorInsolvencyDebtPovertyEconomicsBusinessFinancial systemEconomyFinanceEconomic growth

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.077
GPT teacher head0.361
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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