Revisiting Ezra Pound: An Ecofeminist Approach to “The River-Merchant’s Wife: A Letter”
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".