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Record W6997577382

What It Means To Be a Monster: The British Raj, Race Science, and "The Other" in Fantasy and Folklore

2022· article· en· W6997577382 on OpenAlexaboutno aff

Bibliographic record

VenueHIMALAYA · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFantasyIdeologyFolkloreRace (biology)White (mutation)EliteQuarter (Canadian coin)CommonwealthServant
DOInot available

Abstract

fetched live from OpenAlex

J.R.R. Tolkien wrote The Fellowship of the Ring, the first entry in the culture-defining Lord of the Rings trilogy, from his cottage on Northmoor Road, nestled comfortably in the sleepy streets of North Oxford: the intellectual heart of the British Empire, during the last decade preceding the nation’s imperial decline. British rule over an entire quarter of the planet maintained itself not by force alone, but by the imposition of the ideology of white supremacy on commonwealth citizens, first implemented through Christian thought and later through the “scientific” study of race in the 19th and 20th centuries. While being a thoughtful opponent of the status quo in his time, this paper argues that Tolkien’s background both as a catholic and a scholar among the British elite undoubtedly introduced the illogics of race science into his work, specifically the Lord of the Rings saga which in turn became the groundwork for all fantasy literature and media in the West that came after. Focusing on Tolkien’s use of the term “race” to delineate separate species of independent origin and the formation of “orcs” as a society of dark-skinned, evil-natured, “mongol-types” positioned as inherently disposable and deserving of total annihilation presents troubling implications for the genres of storytelling which adopted Tolkien’s language without question. This legacy has produced two tropes that have pervaded decades after, first the association of the word “race” with immutable biological difference as well as alien otherness, and second the conclusion that the answer to evil is genocide. In response I present the history of race as a fictional narrative that begins in Europe and has persisted in maintaining the illusion of innate difference resulting in western-dominant racial hierarchy across the globe. Drawing on cultivation theory I argue that decades of storytelling which concludes with the annihilation of a racial or alien “other” has preserved the logic of imperial extermination and bolstered death drive junkies who beg and plead for a modern thermonuclear crusade against those they’ve decided are monsters worth slaying.

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: Empirical · Consensus signal: none
Teacher disagreement score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.045
Scholarly communication0.0120.008
Open science0.0010.003
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.226
Teacher spread0.212 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueHIMALAYASame topicThemes in Literature AnalysisFrench-language works237,207