The Structure of Unjust Enrichment Law: Is Restitution a Right or a Remedy
Bibliographic record
Abstract
This essay provides a model for distinguishing between court orders that directly enforce primary duties (e.g., to not trespass) and court orders that require defendants to repair the harm caused by failing to perform a primary duty (e.g., to pay compensatory damages), and then applies the model to the case of restitutionary orders (e.g., a court order that the recipient of a mistaken payment pay an equivalent sum to the payor). Drawing upon, on the one hand, theoretical arguments about the nature of law and the moral foundations of duties to repair, and, on the other hand, the nature of restitutionary orders, Professor Smith concludes that restitutionary orders can be either direct enforcement orders or orders to repair – sometimes they are the former, sometimes the latter.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.049 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".