Differential Asset Valuation in the Medieval Post-Talmudic Legal Literature
Bibliographic record
Abstract
The Talmud’s analysis of asset valuation comprises deep insights often mixed with abstruse logic. This amalgam is likely due to religious stric-tures. Consider the issues of interest and capitalization. Biblical law pro-hibits the payment of interest on loans. According to the Talmud, even nominal interest rates are usurious and strictly forbidden by religious sanction.1 It is hardly surprising, therefore, that Talmudic scholars do not always value assets from a purely economic perspective. This is not because the Talmud does not understand interest. On the contrary, “interest is the time value of money, ” declares Rabbi Nachman.2 Nor is the concept of capitalization a problem. Indeed, when valuation involves human capital, the Talmud correctly values these assets by reference to slave markets (see Kleiman 1987). Thus, if A accidentally destroys B’s arm, A must pay B the difference between the value of a slave (in the same profession as B)
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".