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Record W2151973792 · doi:10.5539/ass.v11n19p211

Confucius and Immanuel Kant: The Problem of Virtue and Morality

2015· article· en· W2151973792 on OpenAlexvenueno aff
Nazgul Zhanisovna Kudaibergenova, Saniya Edilbay, Gulzhan Kanaevna Abdigalieva, Zhandos Zhumalbekovich Kumganbayev

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsnot available
Fundersnot available
KeywordsCategorical imperativeMoralityEpistemologyPhilosophyKantian ethicsHumanismVirtueContext (archaeology)Ideal (ethics)DoctrinePractical philosophyNormative ethicsMoral philosophySociologyEnvironmental ethicsTheology

Abstract

fetched live from OpenAlex

The article presents the results of a comparative analysis of the basic principles of Confucius and Immanuel Kant ethics, and made an attempt to make a reconstruction of the moral ideal in the context of comparative philosophy of the East - West. Particular attention was paid to the following objectives: - to perform a comparative analysis of the Confucius teachings and Kant's philosophy to recreate the spiritual significance of Confucian and Kantian philosophy in understanding the issues of virtue, moral and spiritual development of man - based on existing research in the field of comparative studies, Confucianism and Kantian ethics to analyze the ontological, anthropological, moral content of these teachings. To reveal the essence of humanistic social and ethical teachings of Confucius and the philosophy of Kant. The philosophical teaching of Confucius had a profound impact on the development of ethical thought in China. In Western philosophical space Immanuel Kant is a significant figure, and developed by him the doctrine of moral categorical imperative and an autonomous morality is the basis of almost all further attempts to build ethical models in the West.

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)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.051
Scholarly communication0.0050.006
Open science0.0010.003
Research integrity0.0020.003
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 head0.041
GPT teacher head0.313
Teacher spread0.273 · 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 designTheoretical or conceptual
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

Citations3
Published2015
Admission routes1
Has abstractyes

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