Bibliographic record
Abstract
Friedrich Nietzsche famously and mischievously begins the notorious Second Essay in On The Genealogy of Morals (1887) with an assertion that ties the proper breeding of mankind to the right to make promises. Nietzsche maintains: “[t]o breed an animal with the right to make promises—is this not the paradoxical task that nature has set itself in the case of man? Is this not the real problem which man not only poses but also faces?” Nietzsche’s language challenges its reader from the start to comprehend its various possibilities of mood and mode, rhetoric and grammar: is it a bold statement of authorial values or an ironic insinuation meant to trap the bad conscience of civilized man? More simply, is it a “real” question or a rhetorical statement? The passage loses no time in deploying some of the soldiers in the army of poetical tropes that Nietzsche unmasks as the producers of truth in his equally well-known short piece, “On Truth and Lie in an Extra-Moral Sense” (here prosopopoeia: speaking for nature).Based on this small sampling, already we can sense fully how the “literary” intensity and instability of Nietzsche’s style are embedded in his very conduct of philosophy. The question marks on which the two sentences of this opening salvo end (or sort of end, as there are original ellipses “…”) may not indicate a question has been posed at all for the reader directly to answer. No question, at least, has been posed from the quasi-naïve and open premise that we tend to call a question on equal (epistemological) footing or in (sociable) “good” faith. Not a “real” question from Nietzsche, then; but all the more a real problem. A driving interrogation in fact: in light of what the next sentence calls the “countervailing” and saving “force of forgetfulness,” the conduct of the human will in verbal action becomes “the real problem” we both pose and face as linguistic beings engaged by what Stanley Cavell understands in the term moral perfectionism.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".