Bibliographic record
Abstract
59 (1975) (characterizing the publication of articles by Calabresi and Ronald Coase in the early 1960s as giving birth to the "new" economic analysis of law, which differs from prior economic analyses that did not "apply economic analysis in a systematic way to areas of law that did not purport to regulate economic relationships"). No. 2 2014] DISTRIBUTIVE ECONOMIC ANALYSIS 167But economists need no longer use terms in ways that, however unintentionally, can easily be misunderstood by decisionmakers as leading to conclusions that have normative validity independent of their distributional effects! 10 As Calabresi had recognized in an earlier article, the normative validity of a distributional outcome is determined by initial entitlements: "[A]bsent such a notion of starting points, we cannot say anything about distribution or equality either.We cannot meaningfully say that we have treated Marshall and Taney equally, or justly favored Marshall over Taney, without a concept of what it is to treat them equally."11 The just distribution of risk depends on the initial specification of legal entitlements, which in turn depends on the principle of equality that guides (and constrains) the legal system.Having recognized that the principle of equality determines the just distribution of risk in tort law, Calabresi then maintained that the issue can be informed by economic analysis:For it seems to me that economists and lawyer-economists can have a great deal to say, as scholars, about what is distributionally desirable.We need not simply make our distributional judgments clear and let political decisionmakers accept them or not.We can develop scholarly definitions of just distributions, both theoretical definitions, and definitions based on empirical studies of particular societies.But a further discussion of such distributional studies . . .must await subsequent articles.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.032 |
| Scholarly communication | 0.009 | 0.021 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".