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Record W4409565669 · doi:10.55917/2154-2171.1071

Movement and Mobility: Representing Trauma Through Graphic Narratives

2016· article· en· W4409565669 on OpenAlexaboutno aff
Stella Oh

Bibliographic record

VenueAsian American Literature Discourses & Pedagogies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsMovement (music)NarrativeComputer graphics (images)Visual artsCommunicationComputer sciencePsychologyArtAestheticsLiterature

Abstract

fetched live from OpenAlex

The formal and stylistic movements found within the comic architecture of From Busan to San Francisco and Mail Order Bride interrogate the ways in which the visual and textual narrative can represent the emotional landscape of trauma and displacement through comics language. Engaging in a visual and textual critique of the global economy that trades in feminine identities, these graphic narratives interrogate the mobility and visibility of those who are trafficked. In these works, transnationalism is artistically embedded in consumptive practices of reading and seeing that reinforce or challenge Orientalist cultural assumptions about the Asian female body. Geographical movements of protagonists from South Korea to US and Canada as well as graphical movements of panel arrangements provide a form of ethical optics that allow us to reconsider narratives of trauma and commodification.

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)0.003
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.026
Scholarly communication0.0140.010
Open science0.0010.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.286
Teacher spread0.265 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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