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Record W3043100097

Shakespeare, again? Australian Literary Adaptations of Shakespeare for Children and Young Adults

2020· dissertation· en· W3043100097 on OpenAlexaboutno aff
Michael Marokakis

Bibliographic record

VenueThe Sydney eScholarship Repository (The University of Sydney) · 2020
Typedissertation
Languageen
FieldArts and Humanities
TopicShakespeare, Adaptation, and Literary Criticism
Canadian institutionsnot available
Fundersnot available
KeywordsLiteratureHistoryArt
DOInot available

Abstract

fetched live from OpenAlex

This thesis surveys, codifies and analyses adaptations of Shakespearean plays written by Australian authors for children and Young Adults between 1988 and 2019. It is revealed that the corpus of Australian texts represents a diverse and productive era of adapting Shakespeare. Through an analysis of Australian and international marketplaces, physical and imaginative spaces and the body as a site of meaning, this thesis argues that texts are imbued with the ideological dissemination of Shakespearean cultural capital. Combining current research in children’s literature and Bourdieu’s theory of cultural capital further deepens the critical awareness of the status of Australian literature while extending the pre-existing concentration on British, American and Canadian adaptations. Chapter 1 surveys and codifies the Australian marketplace of adaptations by identifying trends and authorial interests. Chapter 2 examines the representation of classroom, stage and imaginative spaces as contemporary sites upon which the texts cast their adaptations. Chapter 3 analyses gendered bodies as sites that recreate characters from Shakespeare’s plays. Chapter 4 returns to the macrocosmic level of the marketplace to contextualise the Australian texts in the international space. This comparative method determines elements of originality in Australian adaptations. This thesis draws into focus the consequences of the socialising nature of children’s literature by both highlighting the didactic and ideological qualities of the Australian texts.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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.

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
Published2020
Admission routes1
Has abstractyes

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