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Record W3000332257 · doi:10.4324/9780429266157

Performativity, Cultural Construction, and the Graphic Narrative

2019· book· en· W3000332257 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPerformativityNarrativeAestheticsArtVisual artsSociologyLiteratureGender studies

Abstract

fetched live from OpenAlex

"Performativity, Cultural Construction, and the Graphic Narrative draws on performance studies scholarship to understand the social impact of graphic novels and their sociopolitical function. Addressing issues of race, gender, ethnicity, race, war, mental illness, and the environment, the volume encompasses the diversity and variety inherent in the graphic narrative medium. Informed by the scholarship of Dwight Conquergood and his model for performance praxis, this collection of essays makes links between these seemingly disparate areas of study to open new avenues of research for comics and graphic narratives. An international team of authors offer a detailed analysis of new and classical graphic texts from Britain, Iran, India, and Canada as well as the United States. Performance, Social Construction and the Graphic Narrative draws on performance studies scholarship to understand the social impact of graphic novels and their sociopolitical function. Addressing issues of race, gender, ethnicity, race, war, mental illness, and the environment, the volume encompasses the diversity and variety inherent in the graphic narrative medium. This book will be of interest to students and scholars in the areas of communication, literature, comics studies, performance studies, sociology, languages, English, and gender studies, and anyone with an interest in deepening their acquaintance with and understanding of the potential of graphic narratives."--Publisher's description

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.221
Threshold uncertainty score0.895

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.356
Teacher spread0.319 · 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.

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

Citations7
Published2019
Admission routes1
Has abstractyes

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