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Record W6948347874 · doi:10.48336/vv7f-g842

Apocalyptic cinema: the supernatural T.V. series as an original neo-humanistic interpretation of the Book of Revelation

2022· article· en· W6948347874 on OpenAlexaff

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInterpretation (philosophy)RevelationPerspective (graphical)TheismReflexive pronounTerm (time)Universe

Abstract

fetched live from OpenAlex

This thesis aims to develop a critical analysis and interpretation of a long-running streaming television series, Supernatural (2005-2020), whose main story is adapted from the Book of Revelation. This thesis describes, analyzes, and interprets the creatively unique apocalyptic worldview presented in the series through a content/narrative analysis methodology and employing the modeling technique of Game Theory. This study shows that Supernatural creates a universe in which an apocalyptic worldview is projected by a radical type of humanism, which I term ‘Neo-Humanism.’ Neo-Humanism is a kind of perspective whose worldview has roots in the deepest layers of religious belief and its lifestyle is the same as the most exclusive levels of humanism. Neo-Humanism claims that if there is a god, who created human beings with free will and the ability to distinguish between good and evil, as theism says, His creation will inevitably be above everything and able to do everything. And more importantly, even the Creator God Himself does not want, cannot, and should not interfere in humans’ affairs. Even though the Neo-Humanism perspective seems too illogical and surreal to be believable, this thesis shows that in the universe that Supernatural depicts, the inner logic of Neo-Humanism works appropriately.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.223
Teacher spread0.192 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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