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Record W4393899406 · doi:10.5430/wjel.v14n4p174

Revisiting Ezra Pound: An Ecofeminist Approach to “The River-Merchant’s Wife: A Letter”

2024· article· en· W4393899406 on OpenAlexvenueno aff
Jingmei Shang, Hamoud Yahya Ahmed Mohsen, Hongmei Zhang, Jijun Wang

Bibliographic record

VenueWorld Journal of English Language · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPound (networking)WifePhilosophyArtComputer scienceTheologyWorld Wide Web

Abstract

fetched live from OpenAlex

The paper focuses on one of intrinsic studies of literary works called ecofeminism. For the object of the current research, the author chooses one of Ezra Pound's poems, as is known to all, The River-Merchant’s Wife: A Letter. The author uses descriptive and analytic method in this paper. As is discussed, the author analyzes the potential ecofeminism by reading this poem carefully and giving a special attention for the lines that express and convey ecofeminism. Meanwhile, the author uses description and figure of speech analysis to build a concrete and poetic artistic conception in this poem. The findings suggest Ezra Pound spent a lot of conception and thinking on the description of environmental vision, including women and nature. On the one hand, the writing vision is tangible, evidenced by integrating his realistic living surroundings and the artistic conception in this poem. On the other hand, the expression of this poem is emotional, which, to a certain degree, evokes contemporary sensitivity to ecology and the concern on women, even the present social and environmental challenges, and the links between nature and literary that have become increasing obvious in the literary studies. The description of the natural surroundings of the poet prompts his deep awareness of environment, which can be looked upon as a potential ecofeminism.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.839
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.227
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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