Preference Transaction Avoidance in Ghana: Has the Liquidator's burden changed?
Bibliographic record
Abstract
Abstract Financially distressed companies sometimes conceive plans to pay off certain creditors before petitioning the Court for winding up. This last‐minute payment referred to as a preference transaction puts the preferred creditor in a better position than the rest of the company's creditors because the distressed company may not have enough assets to satisfy everyone. Insolvency law frowns on such last‐minute transactions and provides the Liquidator with the power to avoid these transactions, to restore the asset to the company and distribute it to all the creditors. Preference avoidance forms an integral part of the corporate insolvency law in Ghana. These principles founded upon the common law of England are now provided for under the Bodies Corporate (Official) Liquidation Act 1963 (Act 180) of Ghana. This essay discusses preference avoidance under Ghanaian law. It also examines a recent judicial application of the law and finally suggest avenues for reform.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".