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Record W3128245733

Worlds of Vision

2021· article· en· W3128245733 on OpenAlexvenueno aff
Juliet J. Fall

Bibliographic record

VenueACME: An International Journal for Critical Geographies · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsNarrativeComic stripReading (process)Embodied cognitionMateriality (auditing)SituatedVocabularyVisual artsLinguisticsSociologyAestheticsHistoryArtLiteratureComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

The spatial visuality of comics has received substantial attention from comics’ scholars and, more recently, from cultural and political geographers. These have shown how reading comics is an embodied, codified, learnt and culturally-situated activity. Viewer involvement takes place through the distinctive devices, vocabulary and grammar of comics: parts are observed while the whole is sensed and constructed. In this experimental academic comic, I explore how this active involvement might help orient critical geographical practices. Comics’ specific visuality makes readers labour to produce meaning, translating the spatiality of two-dimensional sequential images into four-dimensional narrative, what Dittmer has called ‘a map of time’ (2010). Methodologically, I use detournement (Debord 1956) to build a visual argument that combines a text-based scholarly literature review with a limited corpus of pre-existing images taken from two recent popular Italian comics to tell a story. Reading between images, texts and gutters makes concrete the paradoxical materiality of words and discursivity of images, while building upon a purposefully limited visual corpus. This dialogue of images and words results in a call for an empathic geography, connecting bodies and experiences visually, suitable for representing a fragmented world built upon making sense of a diversity of viewpoints.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.999

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 communication0.0000.001
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 head0.030
GPT teacher head0.345
Teacher spread0.315 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueACME: An International Journal for Critical GeographiesSame topicComics and Graphic NarrativesFrench-language works237,207