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Record W3017899672

Crime in Alias Grace, a half-said truth

2018· article· fr· W3017899672 on OpenAlexaboutno aff
É. Toullec

Bibliographic record

VenueSavoirs et clinique · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAphorismPhilosophyPsychoanalysisAssertionLiteratureArtEpistemologyPsychology
DOInot available

Abstract

fetched live from OpenAlex

The protagonist of Margaret Atwood’s novel Alias Grace is accused of a double murder in 1843 in Canada. At the novel’s climax, the writer redirects the criminal plot toward a questioning of the relationship between truth and the discourse that underpins such truth. This is reminiscent of Lacan and his aphorism “truth is structured like fiction,” as well as of his theory of the four discourses. In particular, the encounter between the discourse of the master and that of the hysteric opens the way for another type of understanding of the logic of alienation and domination at work in the story. The novel also offers a fascinating testimony of the erring ways of science confronted with hysteria before the birth of psychoanalysis.

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)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.109
Threshold uncertainty score0.217

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.018
Scholarly communication0.0120.004
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.364
Teacher spread0.320 · 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
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
Published2018
Admission routes1
Has abstractyes

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