Bibliographic record
Abstract
This doctoral dissertation is a study of Nietzsche's views on morality in order to assess his contribution to moral philosophy. Towards this end, it examines Nietzsche's understanding of morality as well as the scope of his attack. I then offer a reading of Nietzsche's critique of morality, arguing that he rejects morality insofar as it functions within society to preserve the 'herd' at the expense of 'higher types' whose flourishing resides elsewhere. In short, I claim that Nietzsche rejects morality insofar as it proves inimical to the flourishing of these 'higher types'. I also claim that Nietzsche is more than a mere critic of morality, and that his fundamental 'ethical' preoccupation with exemplary individuals is what motives his critique, and forms the basis of his affirmative ethic of human flourishing. Moreover, I contend that Nietzsche defends his positive morality by presenting the character of Zarathustra (Thus Spoke Zarathustra), and later himself (Ecce Homo) as exemplars of human excellence who must rely on their ability to convince others performatively, rather than by means of discourse, or argumentation. Ultimately, I conclude that Nietzsche's ethics does not fit comfortably within the moral tradition as he is an opponent of deontological ethics, utilitarianism, and virtue ethics despite certain affinities with the latter. This fact does not detract from the rich contribution that Nietzsche makes to moral philosophy as bode critic and champion of an affirmative ethic.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".