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Record W1508228328

Representations of Region in Child of God and The Coming of Winter

2012· article· en· W1508228328 on OpenAlexaff
Peter Thompson

Bibliographic record

VenueJournal of New Brunswick Studies / Revue d’études sur le Nouveau-Brunswick · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicModern American Literature Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsHumanitiesPoliticsEthnologyArtPhilosophyHistoryPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the way in which two 1970s-era novels, Cormac McCarthy’s Child of God and David Adams Richards’s The Coming of Winter , contribute to regionalist movements in Appalachia and the Maritimes. These novels undermine conventional images of the two regions: both present dark and violent portraits of the two spaces that counteract received images of Appalachia and the Maritimes as pastoral, welcoming, and quaint. Although there are few comparative studies between Appalachia and the Maritimes, reading McCarthy and Richards together suggests that there may be connections between the two regions that the political boundary separating them obscures. Resume  Cet article explore la maniere par laquelle deux romans des annees 1970, Child of God , de Cormac McCarthy, et The Coming of Winter , de David Adams Richards, ont contribue aux mouvements regionalistes dans les Appalaches et dans les Maritimes. Ces romans contredisent les images traditionnelles des deux regions : les deux presentent des portraits actuels, sombres et violents des deux espaces, qui sont bien loin des idees recues sur les Appalaches et les Maritimes pastorales, accueillantes et paisibles. Bien qu’il n’existe que peu d’etudes comparatives entre les Appalaches et les Maritimes, en lisant McCarthy et Richards, on se rend compte qu’il y a peut etre un rapport entre les deux regions que masquent les frontieres politiques qui les separent.

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)0.002
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: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.026
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.271
Teacher spread0.226 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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