Biology and Ethics: A Case for Aristotle’s Theory of Moral Habituation
Bibliographic record
Abstract
Prior to evolutionary biology, ethics, as a theoretical discipline, was essentially confined to philosophy, where it aimed to analyse the content of morality and what it required of humans. Albeit, in The Descent of Man and Selection in Relation to Sex (1871), Charles Darwin redefined morality to be an innate biological trait, which is inherent in the human biological constitution, thereby opening the way for the ‘biologicization’ of ethics. However, the Darwinian approach projected mere elaborate descriptions of the underlying biological mechanisms of moral behaviour as ethics, thereby sidelining the core normative concerns of traditional ethics. In reducing morality to a mere biological instinct—a spontaneous outburst that requires little human striving—it logically voided the notions of moral culpability, blameworthiness, and approbation. Moreover, the biological approach consigned habit and the intellect to the primordial past, suggesting that these faculties are of secondary importance in the moral behaviour of subsequent human generations. This resulted in a ‘closed habituation’ model, which is also logically inadequate for dealing with the notions of human freedom and moral responsibility. This paper is an attempt to resolve these shortfalls, using Aristotle’s theory of moral habituation as bench mark. The paper proposed a broad theoretical model which reincorporated the sidelined concerns of traditional ethics and, therefore, demonstrated that traditional moral philosophy could not be rendered obsolete by the incursion of biology into ethics, as contemporary evolutionary theorists of ethics have claimed. Key words: Aristotle; Biologicized ethics; Evolution; Morality; Habituation
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.067 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".