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Record W2806901901 · doi:10.52086/001c.25888

Strategic, stylistic and notional intertextuality: Fairy tales in contemporary Australian fiction

2017· article· en· W2806901901 on OpenAlexaboutno aff
Danielle Wood

Bibliographic record

VenueTEXT · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicFolklore, Mythology, and Literature Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntertextualityLiteratureContext (archaeology)Style (visual arts)AppropriationPostmodernismHistoryArtLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

While Canadian scholar Lisa M Fiander argues that fairy tales are ‘everywhere’ in Australian fiction, this paper questions that assertion. It considers what it means for a fairy tale to be ‘in’ a work of contemporary fiction, and posits a classificatory system based on the vocabulary of contemporary music scholarship where a distinction is made between intertextuality that is stylistic and that which is strategic. Stylistic intertextuality is the adoption of features of a style or genre without reference to specific examples, while strategic intertexuality references specific prior works. Two distinct approaches to strategic fairy-tale revision have emerged in Australian writing in recent decades. One approach, exemplified in works by writers including Kate Forsyth, Margo Lanagan and Juliet Marillier, leans towards the retelling of European fairy tales. Examples include Forsyth’s The Beast’s garden (’Beauty and the Beast’), Lanagan’s Tender morsels (‘Snow White and Rose Red’) and Marillier’s short story ‘By bone-light’ (‘Vasilisa the Beautiful’). The other, more fractured, approach is exemplified in works by writers including Carmel Bird and Murray Bail, which do not retell fairy tales but instead echo them and allude to them. This paper proposes that recent Australian works that retell fairy tales are less likely to be set in a recognisably Australian context than are works which take a more fractured approach to fairy tale. It also explores the notion that, presently, transporting European fairy tales, whole, into an Australian setting, seems to be a troubling proposition for writers in a post-colonial settler society that is highly sensitised to, but still largely in denial about, its colonial past.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.913
Threshold uncertainty score0.471

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.128
GPT teacher head0.309
Teacher spread0.181 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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