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Record W2581557380 · doi:10.3138/jrpc.28.2-3.3459

The History of Religions Read as Fantasy: On the Construction of (Religious) Ambiguity in the Television Show<i>Lost</i>

2016· article· en· W2581557380 on OpenAlexvenueno aff
Dirk Johannsen, Anja Kirsch

Bibliographic record

VenueJournal of Religion and Popular Culture · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsDramaNarrativeMythologyFantasyAmbiguityLiteratureStorytellingIndeterminacy (philosophy)HistoryEPICAestheticsArtPhilosophyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

With its intricate “mythology,” the ABC drama series Lost invites a wide range of religious interpretations. Starting off as a survivor drama, the show evolves into a fantastic epic, in which the pilot episode's initial question “Where are we?” triggers reflections such as “where do we come from, where are we going, and what are we” and is finally passed on to the world religions. Against the backdrop of Tzvetan Todorov's and Marianne Wünsch's work on the fantastic, we translate literary scholar Wolfgang Iser's aesthetic response theory into a tool for analyzing narrative structures of contemporary supernatural fiction. Taking storytelling and reception culture into account, this piece shows how Lost uses the enactment of religion(s) to perpetuate structural ambiguity concerning the series' genre. We identify the narrative devices used to create generic indeterminacy both in content and form of the Lost narrative. With this ambiguity reverberating on the religious traditions referred to, Lost suggests the history of religions as an extradiegetic analogue of the literary fantastic.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.027
GPT teacher head0.246
Teacher spread0.218 · 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 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
Published2016
Admission routes1
Has abstractyes

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