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Record W635276826

Stan Lee : conversations

2007· book· en· W635276826 on OpenAlexaboutno aff
Jeff McLaughlin

Bibliographic record

VenueUniversity Press of Mississippi eBooks · 2007
Typebook
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsAdventureUncannyArtArt historyPerformance artPublishingPopular cultureMainstreamMedia studiesPoliticsLiteratureVisual artsSociologyLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Stan Lee (b. 1922), cocreator of the Amazing Spider-Man, the Fantastic Four, the Incredible Hulk, and the Uncanny X-Men, is one of the most successful writers and publishers of comics. During the 1960s and 1970s, he wrote superhero adventures for Marvel Comics. His storylines imbued the genre with angst and contemporary politics and focused as much on the personal lives of his characters as on heroics. His work, in collaboration with cartoonists such as Jack Kirby and Steve Ditko, remains deeply influential. His role as a spokesperson and impresario for Marvel paved the way for the superhero genre to be taken seriously by the critical establishment and for the penetration of Marvel Comics into mainstream American culture. Stan Lee: Conversations collects interviews ranging from 1968 to 2005. Lee's charm, good humor, and keen business sense are on display. He has spirited conversations with cartoonists Jack Kirby, Harvey Kurtzman, and Roy Thomas, talk show host Dick Cavett, and Jenette Kahn (head of DC Comics, Marvel's rival), among others. He talks with candor about his creative process, publishing, film and television adaptations of his comic books, and the evolution of the comics industry. The volume concludes with a new interview conducted by the editor. Jeff McLaughlin is assistant professor of philosophy at Thompson Rivers University in Kamloops, British Columbia.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.906
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
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.196
Teacher spread0.162 · 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
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

Citations3
Published2007
Admission routes1
Has abstractyes

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