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Record W4226280597 · doi:10.18282/l-e.v10i5.2707

An Analysis of Munro’s Works from the Post-colonial Perspective

2022· article· en· W4226280597 on OpenAlexaboutno aff
Anqi Gu

Bibliographic record

VenueLearning & Education · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismPerspective (graphical)IndigenousNarrativeFeminismHistorySociologyArt historyGender studiesArtLiteratureVisual artsArchaeology

Abstract

fetched live from OpenAlex

Alice Munro is an outstanding Canadian short story writer, Nobel Prize winner in Literature for Runaway in 2013. Most of Munro’s works are set in the remote towns of southern Ontario, highlighting unique indigenous nature of Canada. It is noteworthy that Canada is a post-colonial country, and Munro’s works are deeply influenced by the post-colonial characteristics of Canada. So far, domestic and foreign scholars tend to study Munro’s stories from two main aspects of narrative strategy and feminism, but they often neglect the post-colonial nature of Munro’s writing. Therefore, starting from the post-colonial perspective, this paper attempts to deeply explore the construction of post-colonial features reflected in Munro’s writing for the purpose of having a deeper understanding of her 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)0.001
metaresearch head score (Gemma)0.004
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 score0.264
Threshold uncertainty score0.525

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0270.018
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.007
GPT teacher head0.261
Teacher spread0.253 · 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
Published2022
Admission routes1
Has abstractyes

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