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Record W4387584704 · doi:10.22190/full230412010c

CONNECTIONS BETWEEN NORTHROP FRYE AND ROBERT GRAVES

2023· article· en· W4387584704 on OpenAlexaboutno aff
Tanja Cvetković

Bibliographic record

VenueFacta Universitatis Series Linguistics and Literature · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsMythologyPoetryCriticismMeaning (existential)LiteratureTRACE (psycholinguistics)PhilosophyHistoryArtEpistemologyLinguistics

Abstract

fetched live from OpenAlex

Though any written trace of direct communication between Canadian theoretician Northrop Frye and British poet and novelist Robert Graves cannot be found, Frye often referred to the prolific British author in his reviews especially when weighing in Graves’ contribution to the mythopoetic school of criticism. In Frye’s opinion, Graves’s contribution is not in creating a “systematic mythology” but in depicting “mythical use of poetic language, where we invent our own myths and apply them to an indefinite number of human themes” (Gill 2010, lvi). Graves does not lead us to the objective systematic mythology since the myth in his poetry does not seem to be part of an objective system but a kaleidoscopic chaos of human fragments. It is the combination of mythical fragments that create the meaning of the poem after all while the central path to the author’s mind is found through broken images. In that sense the paper shows how the absence of direct correspondence between two authors gives way to the presence of relations between their works which is mainly reflected through the way they applied the myth of the Goddess in their works.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.116
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.022
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.002

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueFacta Universitatis Series Linguistics and LiteratureSame topicShort Stories in Global LiteratureFrench-language works237,207