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Record W4205487683 · doi:10.36993/rjoe.2020.9194

RELATIONSHIPS AND MORAL CONFLICT IN MANRO’S TRAIN

2021· article· en· W4205487683 on OpenAlexaboutno aff
Dr.P. Krishnaveni, Dr.D. Bharathy

Bibliographic record

VenueResearch Journal Of English · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Science, and History
Canadian institutionsnot available
Fundersnot available
KeywordsSocial psychologyPsychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Alice Munro is primarily known for her short stories and has published many collections over the years. She was born on 10 July 1931 in Wingham, which is in the Canadian province of Ontario. She also won the Nobel Prize in Literature in 2013. "TRAIN" is also one of her short stories from Dear Life (2012) collection. In Train, a young Soldier, his name is Jackson, returning to his fiance from the Second World War, jumps off the train before his stop ignoring the fiance waiting for him and starts a new life where he lands. He saw a woman out milking a cow, she is Belle. Jackson pities Belle and thinks that he can work for her for a few months and then continue on his way. After numerous years Jackson and Belle have settled down in Mennonites. I consider the association between them is purely platonic. Munro's stories are often set in small town environment where there is a struggle for socially adequate affairs and ethical conflicts. This paper is an attempt to explore the theme of relations and moral conflicts in her Short story Train.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.928
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.255
GPT teacher head0.340
Teacher spread0.085 · 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 teacher head, 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

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