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Record W2986667048 · doi:10.1525/luminos.65

Frame by Frame: A Materialist Aesthetics of Animated Cartoons

2018· book· en· W2986667048 on OpenAlexfundno aff
Hannah Frank

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicMedia, Gender, and Advertising
Canadian institutionsnot available
FundersAmherst CollegeWalt Disney CompanyYork UniversityYale UniversityEli Lilly and Company
KeywordsAnimationVisual artsFrame (networking)ArtMaterialismAssemblage (archaeology)AestheticsArt historyHistoryComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Edited and with an introduction by Daniel Morgan Foreword by Tom Gunning In this beautifully written and deeply researched study, Hannah Frank provides an original way to understand American animated cartoons from the Golden Age of animation (1920–1960). In the pre-digital age of the twentieth century, the making of cartoons was mechanized and standardized: thousands of drawings were inked and painted onto individual transparent celluloid sheets (called “cels”) and then photographed in succession, a labor-intensive process that was divided across scores of artists and technicians. In order to see the art, labor, and technology of cel animation, Frank slows cartoons down to look frame by frame, finding hitherto unseen aspects of the animated image. What emerges is both a methodology and a highly original account of an art formed on the assembly line. “A thrilling read—one of the most exuberant, brilliant books I’ve come across in a very long time. I have lived with many of the cartoons Hannah Frank analyzes for pretty much my entire life and never suspected the hidden life or lives within their images, the inscription of histories (social, personal, technological, aesthetic) in which, it turns out, they abound.” SCOTT BUKATMAN, Stanford University “Frank’s work is deeply refreshing in its ability to think across and weave together different strands of the debates about animation that have arisen to date. These are big conversations, and Frank is impressive in her ability to think lucidly across them in such fluent and productive ways.” KAREN REDROBE, University of Pennsylvania HANNAH FRANK (1984–2017) was Assistant Professor of Film Studies at the University of North Carolina Wilmington. Her work has been published in Critical Quarterly and Animation: An Interdisciplinary Journal, and she contributed to A World Redrawn: Eisenstein and Brecht in Hollywood. DANIEL MORGAN is Associate Professor of Cinema and Media Studies at the University of Chicago and is author of Late Godard and the Possibilities of Cinema.

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)0.002
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 score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0050.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.024
GPT teacher head0.311
Teacher spread0.287 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

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