The Thing and Judicial Methodology in Resolving Novel Property Claims: It Matters When It Matters
Bibliographic record
Abstract
This article explores, in a very preliminary way, two issues that emerge when Bruce Ziff’s identification of two judicial methodologies in resolving novel property claims is coupled with the two currently dominant theories of property. First, that there is an intuitive correspondence, or correlation, between judicial approach and theory of property produces two correlatives — the attributes-property as things correlative, and the functional-property as relations correlative. And, second, in neither of the two correlatives is the thing or subject-matter of property merely a dispensable backdrop to the inquiry; rather, for both, the thing remains absolutely essential to understanding what property is and concluding that it exists in any given case. But less certainty exists as to when a court must take account of the thing in the context of a discrete novel property claim. Perhaps the most that can be claimed is that it matters when it matters.
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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 | 0.121 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.015 | 0.026 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.012 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".