Bibliographic record
Abstract
Neo-Aristotelian ethical naturalists argue that moral norms are natural norms that apply to human beings. A central issue for neo-Aristotelians is to determine what belongs to the good human life; the question is complicated, since we take up a diversity of different lives, many of which seem good, and it seems unclear what the human species-characteristic life really is. The Aristotelian tradition gives some guidance on this question, however, because it describes us as rational animals with intellectual and appetitive powers; the perfection of those powers is what makes us good qua human. This is especially well spelled out in Thomas Aquinas; he takes moral virtues of courage and temperance to be perfections of our sense appetites, a power of going for things presented as good through our senses. These virtues thereby shape our passions, specifically the passions of fear, daring and concupiscent love, which are a result of the sense appetites pursuing what appears as good. This view provides a framework for virtue, which can then be taken as the perfections of distinct powers shared by all human beings, though actualized in a variety of ways. In this article, I will focus on the passion of fear, which I here describe, following Aquinas, as a movement of sense appetite away from evils that are difficult or impossible to avoid. My focus will be on showing that this passion is necessary, irreplaceable by our cognitive powers, and that the underlying sensitive appetites that produce fear must be perfected for any human being to count as good.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.040 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".