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Record W2972348910 · doi:10.26643/rb.v118i6.7665

Interdisciplinary Study of Margaret Atwood’s Novel Surfacing

2019· article· en· W2972348910 on OpenAlexaboutno aff

Bibliographic record

VenueInternational Journal of Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsEntrepreneurshipEntrepreneurship educationPerceptionSelf-confidencePsychologyPublic relationsMarketingEconomic growthBusinessSociologyPolitical scienceSocial psychologyEconomics

Abstract

fetched live from OpenAlex

Margaret Atwood’s novel Surfacing is a landmark novel in Canadian literature. It presents a richly layered narrative that lends itself to interdisciplinary interpretation. The paper examines the novel through the critical frameworks of eco-criticism, gender studies, psychoanalytic theory, postcolonial discourse and mythological studies.The young and unnamed protagonist comes back to Northern Quebec, the wilderness in search of her father who disappears. Her journey into the Quebec wilderness in search of her father transforms into a search for her identity. The novel throws light on gender oppression, cultural imperialism, environmental problems and psychological issue. Surfacing is immensely relevant in the present scenario of environmental crisis, gender oppression and cultural crisis. Atwood proposes that authentic survival necessitates confronting truth, reclaiming fractured identity and restoring an ethical relationship with Nature.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.444
Threshold uncertainty score0.882

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0460.025
Scholarly communication0.0110.003
Open science0.0020.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.072
GPT teacher head0.393
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreOther

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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