Bibliographic record
Abstract
In his Nobel Prize acceptance speech in 1987, the Russian-born American poet Joseph Brodsky argued that aesthetics is the mother of ethics. However, there is an ambiguity in his use of the term aesthetics. In the first part of this article, I distinguish between Brodsky’s narrow use of aesthetics, which refers to problems of beauty, and the broader sense, which refers to the cognitive function of sensibility and feeling. I then suggest that good sense can be made of the claim about the origins of ethics only if we employ the broader sense of aesthetics. The second part draws on examples from Brodsky and the American poet Jorie Graham to illustrate the ways in which the feelings generated by human sensuous receptivity transform the world from a meaningless physical system into meaningful sets of life-valuable relationships. The third part sharpens this conclusion by considering the conditions under which the world can appear to be meaningless. In the final section I link Brodsky’s poetic responsiveness to the world to John McMurtry’s philosophical analysis of “the felt side of being.” Poetic evocation and philosophical argument are two approaches to the same problem which, when brought together, provide a comprehensive explanation of why aesthetics is the mother of ethics.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".