Mend the gap: visual writerly strategies, the missing piece of reader engagement in comics
Bibliographic record
Abstract
How do comics engage readers? Scholars argue that comics readers become invested in the story by using their imagination to fill in narrative gaps created by the gutter spaces that mark missing visual details in between panels. Theories of the gap, however, do not approach gaps as images that like other ambiguous images create instances of narrative uncertainty that prompt the interpretative input of readers. Inspired by Roland Barthes’s distinction between the readerly and the writerly, this thesis proposes that to reach a plausible, coherent comics narrative, readers either 1) adopt visual readerly strategies to decode conventional images (including the gap), or they 2) employ visual writerly strategies to creatively interpret unconventional, indeterminate images and reach a plausible meaning through inference. In the latter case, the narrative input of readers is extensive and necessary for the narrative to cohere. Several scholars have examined how comics guide readers to decode their conventional visual language. By contrast, little work has been done in relation to the increasingly common use of indeterminate images that demand the writerly input of readers. This thesis addresses this gap in scholarship, adopting a narratological approach to study how unconventional images in nine comics activate the engagement of readers so that the narrative coheres. Because readers enter stories primarily through the thoughts and feelings of characters and narrators, this thesis focuses on the indeterminate visual representation of characters’ or narrators’ minds. Specifically, this thesis demonstrates how: 1) the visual doubling, joining, or blending of cues of minds encourage readers to writerly perceive at once the intramental and the intermental thinking of characters (Chapter One); 2) in the absence of cues of mind, spatial cues enable readers to writerly characterize characters with unreadable minds (Chapter Two); 3) the altering of documents function as focalization cues that prompt readers to writerly respond to the manipulative, confused or ambivalent mind of the narrator who compiled them (Chapter Three). In all instances, the indeterminacy of images and the writerly engagement they trigger draw readers into the storyworld and into the minds of its agents, thus uniquely investing readers as co-creators of the comics narrative.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".