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Record W6999481859

The Critique of Colonial Cartography in N. K. Jemisin’s The Hundred Thousand Kingdoms

2023· article· en· W6999481859 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsTrilogyFantasyNarrativeThe ImaginaryEPICColonialismInheritance (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

Epic fantasy is well-known for supplying readers with maps of fantastic secondary-world settings. N. K. Jemisin’s The Inheritance Trilogy is an example of an epic fantasy series that might have benefited from a map, but its author specifically chose not to include one. Jemisin has publicly acknowledged her aversion to the fantasy map as little more than a cliché that oftentimes spoils the role that places on the map will have in a fantasy text. Critical descriptions of cartographic images in The Inheritance Trilogy, particularly in its first novel The Hundred Thousand Kingdoms, suggest there is more to the story: that the omission of a reader map adds emphasis to the series’ postcolonial critique of what map theorists call “the cartographic gaze.” Associating the very idea of a world map with the arrogance of empire, The Inheritance Trilogy characterizes the god’s eye view of colonial cartography as harmfully misguided, even blasphemous, in its attempt to capture the world from a single totalizing perspective. Jemisin counters the objectifying vantage point of the god’s eye view with the subjective narrative perspective of the colonized other. She is by no means the only fantasy author to use first-person narration to promote postcolonial perspectives, but doing so enables her to recapture a depth of experience that is lost when worlds (both imaginary and real) are framed by the colonial cartographic gaze.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.023
Scholarly communication0.0080.005
Open science0.0010.003
Research integrity0.0020.004
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 head0.166
GPT teacher head0.510
Teacher spread0.345 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicThemes in Literature AnalysisFrench-language works237,207