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Record W4381513140 · doi:10.55529/jlls.34.12.14

Analysis and Study of Margaret Atwood’s Influence on the Canadian Society

2023· article· en· W4381513140 on OpenAlexaboutno aff
Muntadhar Jabbar Abbas

Bibliographic record

VenueJournal of Language and Linguistics in Society · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsHuman sexualityPornographyOryxOppressionGender studiesSexual desireSociologyPsychologyCriminologyPsychoanalysisPolitical scienceLaw

Abstract

fetched live from OpenAlex

Atwood is able to cast an important spotlight on the culturally formed gender roles by challenging the binary oppositions established by a patriarchal culture through these characters, such as by portraying Oryx an experienced businesswoman who utilizes her sexuality to her own advantage. In this case, pornography may be considered as the catalyst for gender oppression since it serves as sex education for guys who have not yet had first-hand sexual encounters and because it has the potential to incite sexual violence against men. Both Jimmy and Crake think of women in terms of their bodies as a result of being influenced by the excessive sexual pictures, sexually oppressed them. While Crake totally removes himself from his sexuality by viewing it as a flaw inherent to everyone, Jimmy is unable to control his. Jimmy is a "product of the affective system," whereas Crake only appears to be one in order to take advantage of the system to further his own interests (Kroon). Crake develops the genetically altered Crakers as a remedy to liberate society from this weakness; he is investigating the sexual boundaries of the human being. This eliminates the conflict between desire and the act of sexual contact.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.124
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0380.010
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.027
GPT teacher head0.273
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of Language and Linguistics in SocietySame topicUtopian, Dystopian, and Speculative FictionFrench-language works237,207