Bibliographic record
Abstract
Prompted by the thesis that an organism’s umwelt possesses not just a descriptive dimension, but a normative one as well, some have sought to annex semiotics with ethics. Yet the pronouncements made in this vein have consisted mainly in rehearsing accepted moral intuitions, and have failed to concretely further our knowledge of why or how a creature comes to order objects in its environment in accordance with axiological charges of value or disvalue. For want of a more explicit account, theorists writing on the topic have relied almost exclusively on semiotic insights about perception originally designed as part of a sophisticated refutation of idealism. The end result, which has been a form of direct givenness, has thus been far from convincing. In an effort to bring substance to the right-headed suggestion that values are rooted in the biological and conform to species-specific requirements, we present a novel conception that strives to make explicit the elemental structure underlying umwelt normativity. Building and expanding on the seminal work of Ayn Rand in metaethics, we describe values as an intertwined lattice which takes a creature’s own embodied life as its ultimate standard; and endeavour to show how, from this, all subsequent valuations can in principle be determined.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".