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Record W3037399884 · doi:10.5539/ells.v10n3p1

Hawthorne’s Dimmesdale and Waliullah’s Majeed Are Not Charlatan: A Comparative Study in the Perspective of Destabilized Socio-Religious Psychology

2020· article· en· W3037399884 on OpenAlexvenueno aff
Tanzin Sultana

Bibliographic record

VenueEnglish Language and Literature Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyLawConvictionCrueltyPsychoanalysisSocial scienceCriminologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

The purpose of this paper is to discuss comparatively Hawthorne’s The Scarlet Letter and Waliullah’s Tree Without Roots to address the social and religious challenges behind the psychology of a man. Dimmesdale and Majeed are not hypocritical. Nathaniel Hawthorne is an important American novelist from the 19th century, while Syed Waliullah is a famous South Asian novelist from the 20th century. Despite being the authors of two different nations, there is a conformity between them in presenting the vulnerability of Dimmesdale and Majeed in their novels. Whether a religious practice or not, a faithful religion is a matter of a set conviction or a force of omnipotence. If a man of any class in an unfixed socio-religious environment finds that he is unable to survive financially or to fulfill his latent propensity, he subtly plays with that fixed belief. In The Scarlet Letter, the Puritan Church minister, Arthur Dimmesdale cannot publicly confess that he is also a co-sinner of Hester’s adultery in Salem. In Tree Without Roots, Majeed knows that the ‘Mazar of Saint Shah Sadeque’ is a lie to the ignorant people of Mahabbatpur. There is also a similarity, however, between Dimmesdale and Majeed. They understand the cruelty of man-made, unsettled social and religious verdicts against a man’s emotional and physical needs. So, despite suffering from inner torment against goodness and evil, they are not willing to reveal their truth of wrongdoing in public action to save their status as well to survive.

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)0.001
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 score0.063
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.048
GPT teacher head0.399
Teacher spread0.351 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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