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Record W4383197149 · doi:10.1017/9781009182942

The Rise of the Graphic Novel

2023· book· en· W4383197149 on OpenAlexaboutno aff
Alexander Dunst

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsNarrativePeriodizationGraphic designStyle (visual arts)TimelineDiversification (marketing strategy)LiteratureArgument (complex analysis)Representation (politics)Comic stripArtHistoryVisual artsPoliticsPolitical science

Abstract

fetched live from OpenAlex

Bringing digital humanities methods to the study of comics, this monograph traces the emergence of the graphic novel at the intersection of popular and literary culture. Based on a representative corpus of over 250 graphic novels from the United States, Canada, and Great Britain, it shows how the genre has built on the visual style of comics while adopting selected features of the contemporary novel. This argument positions the graphic novel as a crucial case study for our understanding of twenty-first-century culture. More than simply a niche format, graphic novels demonstrate how contemporary literature reworks elements of genre narrative, reconfiguring rather than abolishing distinctions between high and low. The book also puts forward a new historical periodization for the graphic novel, centered on integration into the literary marketplace and leading to an explosive growth in page length and a diversification of aesthetic styles.

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 score0.017
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.019
Scholarly communication0.0170.007
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.031
GPT teacher head0.184
Teacher spread0.152 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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