MétaCan
Menu
Back to cohort
Record W1472064904

Cult Author versus Literary Celebrity: Commentary of and on Janet Frame and Margaret Atwood

2011· dissertation· en· W1472064904 on OpenAlexaboutno aff

Bibliographic record

VenueResearchSpace (University of Auckland) · 2011
Typedissertation
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsCultFrame (networking)Performance artArt historyHistoryArtMedia studiesLiteratureSociologyEngineeringTelecommunicationsAncient history
DOInot available

Abstract

fetched live from OpenAlex

'Cult Author versus Literary Celebrity: Commentary of and on Janet Frame and Margaret Atwood' is a comparative exploration of authorial commentary and the critical interaction with that commentary. The mythology that surrounds an author is a powerful force. It can affect and inform critical interpretations of their fiction. The way that authors participate in and attempt to shape their mythologies therefore has implications for the body of literary criticism that attaches to their work. This meta-critical study charts the nature and magnitude of the commentary produced by New Zealand author Janet Frame and Canadian author Margaret Atwood. It aims to investigate how each author has intervened as an active agent to mould the mythological discourse that surrounds them, and to examine the effect of each author's commentary by ascertaining where it has influenced overarching critical narratives of their work. The use of the authors' commentary as a critical tool is canvassed, as is critical reaction to the personae each author projects through their commentary.

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)0.010
metaresearch head score (Gemma)0.050
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.178
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.050
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0240.018
Scholarly communication0.0080.004
Open science0.0020.004
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.056
GPT teacher head0.266
Teacher spread0.211 · 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 designQualitative
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
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueResearchSpace (University of Auckland)Same topicUtopian, Dystopian, and Speculative FictionFrench-language works237,207