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Record W1704707540

Samsara, Karma, and Self-Enlightenment: A Buddhist Perspective on Mo Yan's Life and Death Are Wearing Me Out

2015· article· en· W1704707540 on OpenAlexvenueno aff
Omid Akhavan

Bibliographic record

VenueStudies in literature and language · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicIndian and Buddhist Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKarmaBuddhismEnlightenmentPerspective (graphical)ConsciousnessPhilosophyDharmaEpistemologyAestheticsSociologyPsychologyTheologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Buddhism may best be defined as a path of practice and spiritual improvement leading to insight into the true nature of reality. Buddhist beliefs and practices intend to change individuals so as to develop the qualities of consciousness, benevolence, and wisdom. The experience developed within the Buddhist tradition over thousands of years has made a unique asset for each one of human beings who wish to pursue a path—a path which ultimately culminates in Enlightenment. The theory of Karma is the central tenet of that ethical path in Buddhism. According to this theory, actions good or bad which drives samsara (cycle of existence) for creatures, produce their consequences in the life of the individuals. The present study undertakes to examine the theory of karma in Mo Yan’s Life and Death Are Wearing Me Out. It likewise demonstrates that human beings can liberate themselves from samsara by following the Buddhist path which helps them to attain salvation and self-enlightenment that are considered to be the ultimate goal in an individual’s life.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.010
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.024
Scholarly communication0.0050.002
Open science0.0010.002
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 head0.037
GPT teacher head0.288
Teacher spread0.251 · 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
Published2015
Admission routes1
Has abstractyes

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