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Record W2603104713 · doi:10.22329/p.v11i2.4781

On the Uses and Abuses of Nietzsche in Self-Help Literature

2016· article· en· W2603104713 on OpenAlexvenueno aff
Anne-Gaëlle Argy

Bibliographic record

VenuePhaenEx · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicNietzsche, Schopenhauer, and Hegel
Canadian institutionsnot available
Fundersnot available
KeywordsHappinessExpression (computer science)PhilosophyEpistemologySelfPsychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

This paper investigates the uses that self-help literature makes of Nietzsche’s philosophy. Some specific concepts of his philosophy, as well as his choices in terms of expression, made Nietzsche a topmost reference for self-help authors in the U.S. and in France. As a philosopher and a nearly legendary figure, Nietzsche, in a strange way, fits more easily than other philosophers in the self-help project of leading people, through practical advices, to peace and happiness. Through examples taken from American and French self-help literature, and with comparisons made with other philosophers, this paper shows how self-help functions when it comes to borrowing from other people’s works.

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)0.015
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.005
Science and technology studies0.0140.075
Scholarly communication0.0090.016
Open science0.0010.010
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.026
GPT teacher head0.233
Teacher spread0.207 · 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
GenreEmpirical

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

Citations1
Published2016
Admission routes1
Has abstractyes

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