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Record W2949453596 · doi:10.31142/ijtsrd21365

Socio – Cultural Concern in Margaret Atwood’s Novels

2019· article· en· W2949453596 on OpenAlexaboutno aff
Mrs. S. Selva Priya, T. Poornima

Bibliographic record

VenueInternational Journal of Trend in Scientific Research and Development · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPsychoanalysisArtArt historyPsychology

Abstract

fetched live from OpenAlex

Margaret Atwood is a multi-faceted genius in Canadian literature. In her novel surfacing nameless protagonist of the story returns the undeveloped island, Northern Quebec, where she grew up, to search for his missing father. The protagonist realizes the gap between her natural self and her artificial construct only when she gets in direct contact with nature. Her association with nature raises her consciousness in regards to subordination of women. Since the novel introduces issue pertaining to feminism and environmentalism, it constitutes a representative literary example of ecological feminism. The Blind Assassin encompasses a science fiction story within the main narrative. Iris Chase, the eldest daughter of a wealthy man who owns a button factory is the narrator of the story. The readers follow the span of Iris's life as well as things going on around her community through her. With the help of her sister, her husband, her sister-in-law, and her dead parents, Iris discovers her family secrets; her family's covered up stories; and finds out that not everything is the way it seems. The Blind Assassin is a tale of loss of wealth, heartbreaks, deaths, and sufferings. The language, events and characters in this novel reflect a world that oppresses and dominates both women and nature. The study analyzes the novels in socio-cultural.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical
Teacher disagreement score0.937
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.176
GPT teacher head0.382
Teacher spread0.205 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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