Bibliographic record
Abstract
Empirical virtue researchers have not generally relied on robust virtue theory. Without a unifying theory of virtue, scientific studies have developed without guidance, and the result is a patchwork of relatively disconnected studies of specific virtues based on ad hoc assumptions about those virtues. Therefore, this chapter presents an ecumenical, realistic virtue theory as a conceptual foundation for empirical research in virtue science. It suggests that moral virtues are (1) acquired traits that are (2) manifested in behavior, (3) steered by knowledge, and (4) fully motivated. The virtue theory presented is inspired by philosophic work (primarily Aristotle and Confucius), but it does not engage in the contentious debates active in philosophical approaches to virtue, leaving aside the debates about the nature and importance of ideal human virtue and focusing on the ordinary virtues that are often ascribed to people who are morally good. We also discuss the important role of culture in virtue definition. Finally, we outline the four components of virtue: (1) behavior, (2) cognition, (3) emotion/motivation, and (4) practical wisdom.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".