‘You’re standing on my neck’: Feminist cynicism and queer anti sociality in MTV’s Daria
Bibliographic record
Abstract
Abstract ‘Look right through me / Say I’m gloomy / Yea, so sue me [...] I’ve got to be direct / It’s like a big train wreck / You’re standing on my neck / You’re standing on my neck,’ sing post-grunge band Splendora, throughout the opening sequence to MTV’s popular 1990s cartoon series, Daria. Brooding, sarcastic, and surly, Daria Morgendorffer – a teenager and unapologetic misanthrope from the small, fictional town of Lawndale – has much to offer scholars of feminist negativity and queer anti-social theory. Following Lee Edelman’s rejection of a communitarian, heteronormative ‘politics of hope,’ this article seeks to theorize Daria as an important feminist killjoy and queer cynic; one who vehemently disavows the liberal humanist and capitalist-driven narratives of heroism, optimism, femininity and success that so often saturate teenage television programming. Lauding negativity’s ability to ‘poke holes in the toxic positivity of contemporary thinking’, as Jack Halberstam writes, this article is interested in the kinds of alternative imaginings that are produced by one’s refusal to ‘grow up’ and to ‘fit in’.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.047 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".