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Record W2778081954

Tim O’Brien as Grail Knight: “On the Rainy River”

2017· article· en· W2778081954 on OpenAlexaboutno aff
Jay Ruud

Bibliographic record

VenueOpenEdition (OpenEdition) · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt
DOInot available

Abstract

fetched live from OpenAlex

La nouvelle « On the Rainy River » d’O’Brien prend le contrepied des réactions traditionnelles face à la guerre. Dans cette histoire, le Vietnam n’est pas un lieu où se rendent les héros. Ici, c’est la fuite vers le Canada qui constitue un choix courageux. Aux yeux du protagoniste, le Canada représente un renouveau et un rétablissement spirituels et psychologiques. Historiquement, le Graal est le symbole littéraire archétypal associé à ces éléments. Par conséquent, cet article avance que l’histoire d’O’Brien est une réécriture moderne de l’histoire originelle du Graal, Perceval de Chrétien de Troyes. Dans les deux récits, le jeune héros idéaliste échoue lors de la première épreuve importante de sa vie. Dans les deux cas, les pressions sociales poussent le jeune homme à refréner ce qui lui semble instinctivement juste. Les deux débâcles ont de terribles conséquences dépassant les échecs individuels des protagonistes. La Terre Vaine d’O’Brien ne nécessite pas la guérison du Roi Pêcheur, mais celle du personnage du Chevalier du Graal, qui est, dans la version d’O’Brien, le microcosme de sa nation.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.005
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0190.004

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 head0.033
GPT teacher head0.233
Teacher spread0.199 · 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
Published2017
Admission routes1
Has abstractyes

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