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Is there a comic book industry?

2020· article· en· W3127139501 on OpenAlexaff
Benjamin Woo

Bibliographic record

Venue9ª Arte (São Paulo) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsCarleton University
Fundersnot available
KeywordsComicsPublishingMainstreamAdvertisingProduct (mathematics)SociologyStyle (visual arts)Media studiesVisual artsPolitical scienceBusinessArtLaw

Abstract

fetched live from OpenAlex

The “American comic book industry” is not American, its true product is not comic books, and it may not even be an industry. This article uses a geospatial map of comic book and graphic novel publishers active in the US market as well as sales estimates derived from both the direct market of specialty comic book retailers and trade book stores to question inherited “mental maps” of comic book publishing, such as the divide between “mainstream” and “alternative”/“independent” publishing. Adopting a relational approach, it suggests that a sociology of comics publishing – and of the cultural industries more generally – must be cautious of taking on board un-sociological concepts like “industry.”

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 score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.004
Scholarly communication0.0080.011
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.043
GPT teacher head0.296
Teacher spread0.253 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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