Bibliographic record
Abstract
It is at this point, I think, that we can best make the comparison between ethics and science, and the insurmountable barrier between them seems to me to lie in this fact, that in science we have such a source of conviction and in ethics we have not. Science rests ultimately on a basis of absolute certainty; ethics, so far at least, has not in general found any basis at all. Thus asserted “Prof. H. Dingle” (Herbert Dingle) in an article in Nature in 1946, as quoted in “50 Years Ago” in 1996. He continued: Science can therefore advance with confidence that although it may make mistakes they are not irreparable, and that even though its most trusted structures may come tumbling about its ears, it cannot finally collapse because underneath are the everlasting arms. They are two – reason and experience; on these twin supports science has an indestructible foundation. [Dingle 1996] Although not everyone would endorse Professor Dingle's confidence about the absoluteness of the certainty in science, few would disagree with the proposition that science and ethics rest on different bases. And many would agree that attempts to provide a compelling epistemic warrant for ethical theory have failed. Indeed, moral theorists have often been willing to give up the search and engage in descriptive and normative ethical discussions, leaving the metatheoretical search to others. Biologists and philosophers of biology have eagerly taken up the challenge. Thus an unabashed program for naturalizing ethics has gained enthusiastic supporters in recent decades. Sociobiology, evolutionary ethics, and genetic determinism have all played their parts.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.434 | 0.271 |
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".