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Record W2924210421 · doi:10.3138/jrpc.2017-0021

Mythologizing Mortis: The Clone Wars as Dialogic Spirituality

2019· article· en· W2924210421 on OpenAlexvenueno aff
Derek R. Sweet

Bibliographic record

VenueJournal of Religion and Popular Culture · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicMedia, Religion, Digital Communication
Canadian institutionsnot available
Fundersnot available
KeywordsTrilogySpiritualityArgument (complex analysis)IdeologyRhetorical questionAestheticsRhetoricLiteratureAmbivalenceContemplationSociologyHistoryPhilosophyEpistemologyArtLawTheologyPolitical sciencePsychologySocial psychologyPolitics

Abstract

fetched live from OpenAlex

This article explores the Mortis trilogy, a three-episode story arc from the third season of Star Wars: The Clone Wars, as the rhetorical articulation of a spiritual text. As more than one Star Wars scholar has pointed out, some fans draw on the spiritual ideologies scattered throughout the popular franchise and position themselves as real-life followers of a Jedi code. With this in mind, I suggest that the Mortis story arc offers a lucid account of the Force as related to spiritual practice. As Scott Stroud points out in his work examining the intersection of popular culture, rhetoric, and religion, spiritual texts serve two primary functions: (1) to explain the divine nature of the world and (2) to offer the means to achieve spiritual awareness. I contend that the Mortis trilogy fulfills both of these functions. To make my argument concerning The Clone Wars story arc explicit, I explore the relationship between Star Wars and spiritual practice, emphasize the rhetorical nature of such a relationship, and illustrate how the Mortis trilogy offers a coherent spirituality lacking in the other texts of the Star Wars universe.

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)0.002
metaresearch head score (Gemma)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.008
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.032
Scholarly communication0.0080.008
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.269
Teacher spread0.238 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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