NINA/LILA debtors under the Portuguese Insolvency Act: A hidden problem in plain sight?
Bibliographic record
Abstract
Abstract No income, no assets (NINA) and low income, low assets (LILA) debtors are a non‐negligible part of the increasingly ‘financialized’ market economy. Falling outside the financial market or accessing it through low quality financial products, NINA/LILA debtors appear to be under prioritized by both legal and judicial regimes and public policies. Focusing on the legal and judicial dimension, and taking as an illustration the Portuguese context, we discuss how preinsolvency and insolvency solutions still remain ill‐adjusted for such cases. In spite the existence of some legal provisions aiming at fostering access to law and courts regardless individuals' financial conditions, they do not perform very well with insolvent debtors lacking a regular income. Addicionally, there are non‐legal barriers that prevent those with less economic means to fight properly for their social and economic rights.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".