Strike-out Appeals, Unjust Enrichment, and Discoverability: Insights from Kenya
Bibliographic record
Abstract
This note analyses a judgment of the Kenyan Court of Appeal that implicates issues that have been on the move in private law jurisprudence around the common law world. These issues are: (1) the interlocutory/final ruling distinction that appellate courts in Australia, Canada, Ghana, India, New Zealand, and elsewhere continue to grapple with; (2) when courts can reframe pleadings for breach of contract as claims in unjust enrichment, an issue recently considered by the Privy Council (2020); (3) the essentiality of ‘mistake’ for the purposes of benefitting from an extended limitation period – the subject of continued contention among unjust enrichment scholars; and (4) when mistakes are reasonably discoverable for limitation purposes, which has been the subject of major litigation before the United Kingdom Supreme Court (2020) and the Supreme Court of Canada (2021). The resolution of these issues in Alba Petroleum Ltd v Total Marketing Kenya Ltd could have been usefully informed by – and can inform – comparative common law jurisprudence.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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.
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".