Bibliographic record
Abstract
Consistent with the idea that business ethics is a form of applied ethics, many virtue ethicists make use of an extant (pure) moral philosophy framework, namely, one developed by Alasdair MacIntyre. In doing so, these authors have refined MacIntyre’s work, but have never really challenged it. In here questioning, and developing an alternative to, the MacIntyrean orthdoxy, I illustrate the merit of business ethicists adopting a broader philosophical perspective focused on constructing (new) theory. More specifically—and in referring to action sports (e.g., mountain biking, snowboarding)—I propose that an external good motive is not only much more consistent with virtuous practical excellence than MacIntyreans acknowledge, but that such a motive is fundamental to identifying and explaining how practices can be deliberately created (by businesses). Consequently, and in stark contrast with MacIntyre’s deeply pessimistic outlook on modern business and society, I propose that those who value practices might celebrate our current era.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.032 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".