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Record W4386469162 · doi:10.32920/24093759

Nietzsche’s eternal recurrence as a transformative cosmological teaching

2023· preprint· en· W4386469162 on OpenAlexaff
Muhammad Omar Khan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicNietzsche, Schopenhauer, and Hegel
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTransformative learningMeaning (existential)Interpretation (philosophy)PhilosophyEpistemologyValue (mathematics)Power (physics)PsychologyPhysicsMathematicsQuantum mechanicsPedagogy

Abstract

fetched live from OpenAlex

According to Nietzsche’s idea of eternal recurrence, everything that happens now must have already happened an infinite number of times and will happen an infinite number of times again. How one reacts to such an idea is a measure of how life-affirming or life-denying one’s attitude is vis-à-vis a world bereft of transcendent value or meaning. The debates about how to interpret this idea have centered around two broad options: some interpret eternal recurrence as a psychological test, others think Nietzsche presented it as a cosmological hypothesis. I present a more unified account than either of these two interpretations by arguing (a) that Nietzsche presents eternal recurrence as transformative teaching and (b) that the transformation it is supposed to induce cannot take place unless the idea is believed to be factually true. On my interpretation, then, eternal recurrence’s cosmological import is central to its projected transformative psychological power.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.021
Scholarly communication0.0040.009
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.103
GPT teacher head0.314
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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