Palatable Political Passion Projects?: Feminist Instatoons in South Korea
Bibliographic record
Abstract
This article builds on the work of existing English language-printed academic texts on webtoons and webcomics, and introduces instatoons (a portmanteau of Instagram and cartoon) as a medium used by creators to disseminate feminist ideas. Webcomics, as an instrument of feminist storytelling, are seen worldwide. Dubbati (2017) has examined Deena Mohamed’s webcomic Qahera, an Egyptian hijab-wearing superheroine; the French comic artist Emma (2017) published a series of comics in The Guardian, depicting issues such as ‘the mental load’ and maternity leave; Canadian artist Aminder Dhaliwal’s (2017) Instagram series Woman World tells a story of a post-apocalyptic future where men are extinct; and the Indian webcomic Priya Shakti (2014) follows a rape survivor ‘who, along with the Goddess Parvati, defends women against sexual predators’ (Aldama 2021: 5). Focusing on two South Korean (hereafter Korean) instatoons by the award-winning creator Soo Shin Ji (수신지), the notion of Korean feminist instatoons as palatable political passions projects will be explored. Myeoneuragi (며느라기, also known as SARIN) (2017-2018), and Gone (곤) (2019-2020), were both initially published on Instagram and Facebook. Myeoneuragi follows newlywed Min Sa-rin, tracking her experiences of day-to-day inequalities during her incorporation into her husband’s family, and Gone is set in a fictional world where all women who have had abortions face legal punishments. Myeoneuragi, begins with the wedding of the main character Min Sa-rin and her husband Mu Gu-young. The instatoon quickly shows the subtle inequalities that Sa-rin experiences on a daily basis, while she navigates her company job and her new role as a daughter-in-law (fig. 1).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".