Bibliographic record
Abstract
Many legal theorists have argued that analogical reasoning is merely rule-following in which the general rule is not stated. Lloyd Weinreb's tries to defend the practice of analogical reasoning on its own terms. He does so by giving examples of the way people use analogical reasoning, both in legal and non-legal contexts, as a means for deciding how to act in particular circumstances. By itself such evidence does not support Weinreb's case, because to justify analogy he must show that analogical reasoning can somehow lead us to correct answers. Moreover, his evidence does nothing to challenge the claim that analogical reasoning is simply following suppressed rules.I try to give Weinreb a helping hand. I use the data he mentions that people actually reason by analogy as a starting point for a novel justificatory account of analogical reasoning based on the notion of reliable results: a process of reasoning is reliable, and therefore reliance on it justified, if it tends to generate correct results. This requires explaining what counts as correct results in law, which is a question of political philosophy. I show that the most fundamental condition for the acceptability of analogical reasoning is that the standard of legal correctness is not determined by principles derived by Reason (as is the approach in the civil law tradition) but rather by a standard of acceptance (more prevalent in the common law tradition). Nonetheless, I argue that there two other conditions - shared social values and skepticism about the possibility of discovering the right normative foundations to legal questions - that together have to obtain in order to justify reliance on analogical reasoning. Since that in a modern society it is unlikely that these two conditions are not likely to obtain, I conclude that even this sympathetic reconstruction of Weinreb's argument ultimately fails.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.052 | 0.014 |
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".