A Theory of Contracts with Limited Enforcement
Bibliographic record
Abstract
We develop a theory of contracts with limited enforcement in the context of a dynamic relationship. The seller is privately informed on his persistent cost, while the buyer remains uninformed. Public enforcement relies on remedies for breaches. Private enforcement comes from terminating the relationship. We first characterize enforcement constraints under asymmetric information. Those constraints ensure that parties never breach contracts. In particular, a high-cost seller may be tempted to trade high volumes at high prices at the beginning of the relationship before breaching the contract later on. Such “take-the-money-and-run” strategy becomes less attractive as time passes. It can thus be prevented by backloading payments and increasing volumes over a transitory phase. In a mature phase, enforcement constraints are slack and the optimal contract, although keeping memory of the shadow cost of enforcement constraints binding earlier on, looks stationary. Second-best distortions depend on a modified virtual cost that encapsulates this shadow cost of enforcement.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".