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Record W4385497600 · doi:10.3138/cras-2023-006

North of Carmel: Jeffers, Bringhurst, and the Ecological View

2023· article· en· W4385497600 on OpenAlexaffvenueabout
Nicholas Bradley

Bibliographic record

VenueCanadian Review of American Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsWildernessParallelsPoetryHumanityEthosReading (process)HistoryLiteratureEcologyEthnologyArtPhilosophyBiology

Abstract

fetched live from OpenAlex

This article proposes that the works of the modern American poet Robinson Jeffers and those of the contemporary Canadian poet Robert Bringhurst are linked by an ecological ethos. Although specific instances of Jeffers’s influence occur here and there in Canadian literary history, the connection between Jeffers and Bringhurst is more substantial, if not immediately obvious. It consists in an aesthetic and intellectual affinity—in a shared poetic terrain that is a conceptual equivalent of the western North American geography they have in common. (Jeffers was a Californian poet; Bringhurst is often associated with the Pacific Northwest.) The poets are comparably concerned with wilderness, which in their works is not always remote or uninhabited but rather characterized by the peripheral place of humanity. In attending to parallels between the authors’ works, the article suggests that reading across the border between Canada and the United States brings into view significant literary connections.

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)0.003
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 score0.788
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0150.014
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.024
GPT teacher head0.246
Teacher spread0.222 · 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
Published2023
Admission routes3
Has abstractyes

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