Bibliographic record
Abstract
Through discussion of a sample of his work, this article identifies a key theme in Michael Trebilcock’s astonishingly deep and broad body of scholarship: trade-offs matter. Trebilcock’s analysis of a House of Lords case, Macauley v Schroeder Publishing, demonstrates the perils of one-sided economic analysis: the court ignored trade-offs in determining that a contract was unfair when there were facts and economic arguments that offered strong indications of the mutually beneficial nature of the contract. From a broader normative perspective, The Limits of Freedom of Contract calls attention to the complexities and trade-offs that inform the boundaries of legally permissible contracting. While economic analysis is useful, it does not have the only relevant things to say about difficult moral questions that surround certain contracts, such as those concerning parental surrogacy; a variety of normative perspectives are also relevant and ought to be taken seriously if the law is to reflect society’s values. Trebilcock’s thinking about optimal institutional design also reflects the importance of trade-offs and ties the strands of his work together. Where a question, such as the economic fairness of a contract, requires the assessment of a technocratic trade-off, a technocratic institution, such as a court, ought to decide it. On the other hand, where a question requires a trade-off among incommensurable normative values, such as surrogacy contracts, there ought to be political oversight and accountability, such as the direct regulation of the content of surrogacy contracts. The article discusses this institutional perspective in relation to his scholarship on competition law institutions. Not only does Trebilcock provide important substantive answers to legal questions that involve technocratic and normative trade-offs, but his work also provides an institutional way of thinking about trade-offs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".