Bibliographic record
Abstract
<div><i>Mediating Gender in Post-Authoritarian South Korea</i> focuses on the relationship between media representation and gender politics in South Korea. Its chapters feature notable voices of South Korea’s burgeoning sphere of gender critique enabled by social media, doing what no other academic volume has yet accomplished in the sphere of Anglophone studies on this topic. Seeking to interrogate the role of popular media in establishing and shaping gendered common sense, this volume fosters cross-disciplinary conversations linked by the central thesis that gender discourse and representation are central to the politics, aesthetics, and economics of contemporary South Korea. In the post-authoritarian period (the late 1980s to the #MeToo present), media representation and popular discourse changed the gender conventions that are found at the core of civic, political, and cultural debates. <br><br><i>Mediating Gender in Post-Authoritarian South Korea</i> maps the ways in which popular media and public discourse make the social dynamics of gender visible and open them up for debate and dismantling. In presenting innovative new research on the ways in which popular ideas about gender gain concrete form and political substance through mass mediation, the book’s contributors investigate the discursive production of gender in contemporary South Korea through trends, tropes, and thematics, as popular media become the domain in which new gendered subjectivities and relations transpire. The essays in this volume present cases and media objects that span multiple media and platforms, introducing new ways of thinking about gender as a platform and a conceptual infrastructure in the post-authoritarian era.</div>
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".