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Record W2028148651 · doi:10.5539/ells.v4n1p1

An Ecocritical Reading of William Wordsworth’s Selected Poems

2014· article· en· W2028148651 on OpenAlexvenueno aff
Abolfazl Ramazani, Elmira Bazregarzadeh

Bibliographic record

VenueEnglish Language and Literature Studies · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
FundersShiraz University
KeywordsEcocriticismPoetryRomanceRomanticismLiteratureReading (process)PhilosophyAestheticsArtHistory

Abstract

fetched live from OpenAlex

With the publication of Lawrence Buell’s The Environmental Imagination (1995) and Cheryll Glotfelty and Harold Fromm’s joint collection, The Ecocriticism Reader (1996), Ecocriticism emerged in the 1990s and the critics changed their angles of vision and examined the works of art by focusing on the relationship between man and Nature. Hence, Romantic poetry, in general, and William Wordsworth, in particular, became the key icons of ecocritical studies. Wordsworth was a major English Romantic poet who has been considered as a forerunner of English Romanticism. His views towards Nature and man’s treatment of Nature have supported his position as an important icon of ecocritical studies. His fame lies in the general belief that he has been viewed as a Nature poet who viewed Nature superior to humans. In other words, his views about Nature and his poems seek to heal the long-forgotten wounds of Nature in the hope of reaching unification between man and Nature. Therefore, this study is an attempt to focus on Wordsworth’s selected poems in the light of Ecocriticism in order to shed light on the poet’s cautious views about the interdependence of man and Nature and purge Wordsworth of the unjust labels tagged to him as a self-centered poet. Accordingly, this research takes into account the importance of the reciprocal relationship between man and Nature as the major constituents of a vast ecosystem and helps the readers grow ecologically and achieve tranquility in an era suffocated by technological pollution.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.633

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.233
Teacher spread0.225 · 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 designQualitative
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

Citations5
Published2014
Admission routes1
Has abstractyes

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