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Record W2995213809 · doi:10.1080/21504857.2019.1700145

Traumatic loss and productive impasse in comics: visual metaphors of depression and melancholia in Jillian and Mariko Tamaki’s <i>This One Summer</i>

2019· article· en· W2995213809 on OpenAlexaff
David Lewkowich

Bibliographic record

VenueJournal of Graphic Novels & Comics · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMelancholiaSadnessPsychicPsychoanalysisFreudian slipInterpretation (philosophy)Psychoanalytic theoryComicsPsychologyFeelingGriefCharacter (mathematics)ConsciousnessArtLiteratureAngerPsychotherapistPhilosophySocial psychologyMood

Abstract

fetched live from OpenAlex

In this paper, I explore how Jillian and Mariko Tamaki, in This One Summer, employ a variety of images and visual metaphors to address the emotional situations of traumatic loss. In this graphic novel, we encounter a character named Alice, who is often distracted and withdrawn, and appears to suffer from a prolonged, inescapable period of depression and sadness. By the graphic novel’s end, however, she begins to learn how to live with the effects of a loss that won’t let her go, as her depressive period becomes reframed as a state of productive impasse. In my discussion, I move through three major types of images that help to illuminate the inner transformations of Alice’s psychic condition: Shattering, Shifting Temporalities, and Diving. Throughout this paper, I use the conceptual touchstones of psychoanalytic theory to describe the interrelation of mourning and melancholia, and suggest that focusing closely on the visual elements of emotional events in comics might allow for an interpretation of those ephemeral aspects of human experience – including moods and feelings – whose expression inevitably requires more than words alone.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.246
Teacher spread0.227 · 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 designObservational
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
Published2019
Admission routes1
Has abstractyes

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