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Record W7067307947

Literature as Counter-History in The Blind Assassin and Atonement

2016· other· en· W7067307947 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2016
Typeother
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAtonementSubject (documents)CriticismMetafictionFocus (optics)Literary criticism
DOInot available

Abstract

fetched live from OpenAlex

By comparing The Blind Assassin by Margaret Atwood and Atonement by Ian McEwan, this thesis provides an insight into the way literature can reflect on the traditional historical narrative, which has been a subject of criticism in postmodernism, and even supplement it. Through their use of literary techniques found in historiographic metafiction and fictions of memory, the two novels criticize the one-sided, dominant representations of the 1930s and 40s in Canada and England, which usually focus on soldiers, bombs, and politics. The novels present a counter-history by reclaiming underrepresented parts of the past; in this case issues of gender and class.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.016
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0140.042
Scholarly communication0.0160.013
Open science0.0010.007
Research integrity0.0040.004
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 head0.010
GPT teacher head0.195
Teacher spread0.186 · 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
Published2016
Admission routes1
Has abstractyes

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