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Record W2925754059 · doi:10.5539/ijel.v9n3p57

American Dream or Avaratia: Critical Circumspectis of American Dream Through Ages

2019· article· en· W2925754059 on OpenAlexvenueno aff
Faiza Zaheer, Kamal Ud Din

Bibliographic record

VenueInternational Journal of English Linguistics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Studies and Interdisciplinary Research
Canadian institutionsnot available
Fundersnot available
KeywordsDreamDeconstruction (building)AestheticsPostmodernismArtLiteraturePsychoanalysisPsychology

Abstract

fetched live from OpenAlex

This paper is an attempt to apply Jacques Derrida’s theory of Deconstruction to American Dream and its treatment in the language of Edward Albee’s play American Dream and other American Playwrights. Different deconstructive terms have been applied to understand and analyze the language of Albee’s The American Dream. Deconstructive terms; Différance, Erasure and Aporia have been applied to the language used by Albee to analyze the concept of American dream and its relation to its context of old American Dream as envisaged by the founding fathers and the new American Dream as defined by James Truslow Adams. These deconstructive terms will help readers to understand the themes and language of postmodern and post war American drama in general and those of Albee’s in particular. This, in turn, makes the reader realize that American dream as depicted in modern American Playwrights is materialistic, illogical, futile and bizarre: Albee’s play reflects modern American society and its sensibility. Language of modern is simple yet it communicates multi-faceted interpretations and those interpretations have been explored in the light of all these deconstructive terms. The basic purpose of involving these deconstructive terms in analyzing the language of Albee’s The American Dream and the other major postmodern American plays is not only to understand the mutability and fluidity in the diction but also to expose absurdity and apparent meaninglessness in it.

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)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.694
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.355
Teacher spread0.314 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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