Bibliographic record
Abstract
Through the study of Emily Dickinson’s life and her works as well as the comments on her, the thesis is intended to find out that how Eco-feminism influences her works and life deeply, and the perspective of Eco-feminism in her poetry. As one of the most prominent poetesses in the nineteenth century, Emily Dickinson made a great impact on American literature, and she was praised as “the most topping poetess in the west since Sapphic”. She was outstanding among the contemporary poets for her unique writing style, creating images and profound ideology. This thesis begins with the fundamental introduction of Emily Dickinson and the Eco-feminist criticism. Based on the former researches on Dickinson and her poetry, this paper further discusses Dickinson’s Eco-feminism, mainly exploring Dickinson’s rebellion and challenge on the religious belief, literary trends and social tradition in the nineteenth century. After that, this thesis analyzes the themes and styles of Dickinson’s poetry from Eco-feminism. Through the Eco-feminist reading of the themes and styles of Dickinson’s poetry, Dickinson research not only means to make a detailed description and analysis of her life and poetry, but also means to provide new interpretive methods and appreciating perspectives. In the first chapter of this essay, I just explain the Eco-feminism idea in a whole way. The reflection of Eco-feminism to Dickinson’s life and her poems writing are discussed in the second and third chapter. In the last chapter, I mainly analyze the Eco-feminist style in Dickinson’s poems.
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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 | 0.000 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".