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Record W2805749373 · doi:10.29173/spectrum34

Top-Down Processing: A Network Analysis of The Lord of the Rings as a Means of Defining Good and Evil

2018· article· en· W2805749373 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSpectrum · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOpinion Dynamics and Social Influence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFantasyPower (physics)SightKey (lock)Class (philosophy)The InternetGood and evilSociologyLiteraturePhilosophyEpistemologyComputer scienceArtComputer securityWorld Wide WebPhysics

Abstract

fetched live from OpenAlex

This essay was written for Dr. Quamen’s ENGL 486 class on the Internet as Environment. Using networktheory, I seek to analyze the structural characteristics of power and authority in J.R.R. Tolkien’s TheLord of the Rings. I then compare my findings with H.C. Mack’s parametric analysis of the texts, andsuggest that both structural methodologies serve to reinforce the idea that concepts of sight andegotism play a key role in Tolkien’s binary portrayal of characters as being either good or evil. Theessay concludes with the suggestion that the configurations power and authority in LotR are deeply tiedto Tolkien’s portrayal of the nature of good and evil, and suggests further research into the questionof whether such power configurations may have since become mythic tropes in Western fantasy.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.244
Teacher spread0.239 · 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