Bibliographic record
Abstract
The leaves cry. It is not a cry of divine attention, Nor the smoke-drift of puffed-out heroes, nor human cry. It is the cry of leaves that do not transcend themselves, In the absence of fantasia, without meaning more Than they are in the final finding of the ear, in the thing Itself, until, at last, the cry concerns no one at all. (Wallace Stevens, “The Course of a Particular,” Palm 367) In the first chapter I noted how David Hume traces the provenance of justice to an experience of natural scarcity. The notion of equity arises, he speculates, as a practical means of coping with a world where there is not enough food, shelter, or property to satisfy everyone, prompting the need for a regulatory system governed by principles and enacted through laws. A state of permanent abundance – recall the bounty of Huck Finn's six-foot catfish – would make justice irrelevant, since there would be no need either to be possessive or to share. At the other extreme, a state of utter deprivation would impose a perpetual emergency in which justice would be ineffectual. The former would have no need for justice, the latter no use for it. In both, “[b]y rendering justice totally useless , you thereby totally destroy its essence, and suspend its obligation upon mankind” (Hume 16).
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".