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Record W4404676996 · doi:10.24043/001c.126242

Between Realms: The Island as a Liminal Space of Redemption and Fantasy in ‘the Tempest’ and ‘Lost’

2024· article· en· W4404676996 on OpenAlexvenueno aff
Mingying Zhou, Xiaohong Zhang

Bibliographic record

VenueIsland Studies Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPhilippine History and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsTempestLiminalityFantasySpace (punctuation)ArtAestheticsArt historyLiteraturePhilosophy

Abstract

fetched live from OpenAlex

This article embarks on a comparative analysis to uncover the role of the island as a liminal space in William Shakespeare’s The Tempest and the television series Lost , exploring its function in facilitating redemption, fantasy, and transformation. The study elucidates how both narratives utilize the island not merely as a setting but as a crucial catalyst for character evolution and thematic depth. Through an examination of geographical, temporal, and psychological dimensions of liminality, the article demonstrates the island’s pivotal role as a space where human complexity, the quest for identity, and aspirations towards redemption unfold. The comparative inquiry highlights narrative and thematic correspondences, underlining the interpretive richness offered by the concept of liminality within literary and media studies. This analysis accentuates the enduring significance of liminal spaces in fostering significant personal and collective transformations, despite disparities in medium and historical context.

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: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.024
Scholarly communication0.0070.007
Open science0.0010.006
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 head0.046
GPT teacher head0.364
Teacher spread0.318 · 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
Published2024
Admission routes1
Has abstractyes

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