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Record W4206235227 · doi:10.3390/h11010014

Their Own Devices: Steampunk Airships as Heterotopias of Crisis and Deviance

2022· article· en· W4206235227 on OpenAlexaff
Courtney Krentz, Mike Perschon, Amy St. Amand

Bibliographic record

VenueHumanities · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSpatial and Cultural Studies
Canadian institutionsMacEwan UniversityUniversity of British Columbia
Fundersnot available
KeywordsHeterotopia (medicine)Deviance (statistics)FREAKTrilogyLiminalitySociologyRomanceMichel foucaultIdentity crisisGender studiesPsychoanalysisHistoryPsychologyPolitical scienceLawComputer securityArt historyPolitics

Abstract

fetched live from OpenAlex

Michel Foucault uses a sailing vessel as the exemplar of his theory of heterotopia because of its mobility. The lateral and vertical mobility of the steampunk airship indicates the potential for an even greater exemplar of heterotopia, particularly of Foucault’s defining principles of heterotopic crisis and deviance. These principles are explored onboard the steampunk airships of Scott Westerfeld’s Leviathan trilogy and Gail Carriger’s Finishing School series, resulting in travel towards progressive social frontiers of gender and race. The protagonists of the Leviathan trilogy move from a position of crisis to deviance, as mediated through the friendship and romance of two representatives of warring factions. In contrast, the heroine of the Finishing School series moves from deviance to crisis as she navigates the vagaries of gender and racial identity. These airship heterotopias of young adult fiction, which not only descend geographically but also socially, cross liminal crisis spaces of class, race, gender, and identity to craft literary cartographies for these social frontiers, providing readers with literary maps for their uncertain real worlds of crisis.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.013

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 studies0.0060.021
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.284
Teacher spread0.204 · 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 designQualitative
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

Citations1
Published2022
Admission routes1
Has abstractyes

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