Amor Fati: Nietzsche's formula for human greatness (A philosophical guide to saying Yes to life)
Bibliographic record
Abstract
This dissertation might be described as a philosophical biography of an idea —Nietzsche’s idea of ‘amor fati’, ‘love of fate’. First introduced in 1882, amor fati marks a renewed affirmation of life for Nietzsche, a new understanding of what it means to say yes to life. In this thesis I show how loving fate informs both Nietzsche’s critique of Christianity, and proposed replacement of traditional values with life-affirming values. For such an important idea, Nietzsche’s published references to amor fati are not frequent — four occurrences in his published works. In fact, the importance of the idea to Nietzsche is highlighted, not cast into doubt, by a close look at how and when he discusses it in his published works. After he introduces the notion in 1882 as a very important new year’s resolution urging himself to love fate, he returns to it in the final three occurrences at the end of his productive life. I argue that the ambition of loving fate acted as a type of lighthouse – his beacon drawing him back from the dangerous waters of philosophical exploration and the dark clouds of personal suffering. He calls amor fati his “greatest love” and as his “formula for human greatness in a human being”.
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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 | 0.003 | 0.013 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| 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".