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Record W7126475109

The Future as Warning: Narrative Voice and Literary Form in Modern Dystopian Novels

2025· article· en· W7126475109 on OpenAlexaboutno aff
Jocelyn Sears

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsDystopiaNarrativeIdeologyLiterary genrePoliticsPlural
DOInot available

Abstract

fetched live from OpenAlex

Since modern dystopian fiction appeared in the wake of the First World War and the Russian Revolution, texts in the genre have warned against the dreadful consequences that could result from current sociopolitical trends and have sought to intervene in the present to prevent the manifestation of nightmarish futures. During this time, Anglophone dystopian novels have frequently eschewed the transparent first- and third-person narrators that dominate both realist literary fiction and genre fiction, instead favoring conspicuous and estranging voices. Putting narrative theory in dialogue with dystopian scholarship, “The Future as Warning” investigates this under-researched phenomenon, exploring the relationship between narratorial form, thematic content, and ideological messaging in dystopian fiction. Analyzing texts by American, British, and Canadian writers, as well as one influential Russian, this dissertation examines four narratorial forms that recur across twentieth- and twenty-first-century dystopian novels: the plural first-person we-voice, narration in an invented future version of English, the diary conceit, and the found-document conceit.

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 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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0050.007
Open science0.0010.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.236
Teacher spread0.225 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDigital Access to Scholarship at Harvard (DASH) (Harvard University)Same topicShort Stories in Global LiteratureFrench-language works237,207