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Record W3210553553 · doi:10.30965/22102388-12340002

The Theme of Happiness and British Utilitarianism in Russian Thought, from the 1860s to the Early 1880s

2021· article· en· W3210553553 on OpenAlexaff
Julia Berest

Bibliographic record

VenueJournal of Modern Russian History and Historiography · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicRousseau and Enlightenment Thought
Canadian institutionsWestern University
Fundersnot available
KeywordsHappinessIntelligentsiaTheme (computing)UtilitarianismAestheticsSociologyPhilosophyPsychologyEpistemologySocial psychologyLawPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Abstract The theme of happiness is a neglected topic in studies of Russian thought, in part because the Russian intelligentsia came to be associated with the ethos of self-abnegation and sacrifice in the name of the common good. It is little known that the spread of utilitarian philosophy in Russia in the early 1860s sparked a debate on the notion of happiness (individual and collective) between the left intelligentsia and their opponents on the conservative spectrum. The publication of the Russian translations of Jeremy Bentham and John Stuart Mill in the late 1860s provided a new spur to the controversy and gave it a more philosophical flavor. While the intelligentsia thinkers asserted the right to happiness as one of the fundamental human needs, rooted in the very essence of human nature, the conservative writers contested both the idea of happiness as a right and the notion that happiness is the purpose of life. This article examines the intellectual and contextual development of the theme of happiness in Russian thought throughout the 1860s–1880s.

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)0.002
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: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.186
Teacher spread0.169 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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