I want my Snooki: MTV’s failed subjects and post-feminist ambivalence in and around the<i>Jersey Shore</i>
Bibliographic record
Abstract
As a sexually promiscuous and outrageously flamboyant young woman, Nicole “Snooki” Polizzi of MTV’s Jersey Shore (2009–2012) Jersey Shore. 2009–2012. Television Series. Seasons 1–6. USA: MTV. [Google Scholar] could be said to be the ultimate example of Angela McRobbie’s post-feminist subject. However, as pervasive as post-feminist narratives have become in popular culture, the figure of Snooki problematizes its ideal forms of femininity and meritocratic success. In this paper I argue that Snooki’s potential challenges to post-feminist ideology were contained by news reporting on her at the height of her fame. This analysis posits a noteworthy divide in that those most inclined to watch/consume Snooki-as-text (the MTV audience) likely remained beyond the reach of the news media’s attempt to re-inscribe hegemonic ideologies onto her star image/text. I examine the relation between Snooki-as-text (the Snooki presented on Jersey Shore) and the extra-textual attempts to undermine her popularity and legitimacy. I frame this discussion along three axes of transgression and containment: the sexual empowerment/threat paradigm; the physical markings of class and ethnic subjectivity; and the textual boundaries of meritocratic success. Despite efforts to contain her, Snooki’s short-lived success hints at an ambivalence toward post-feminism today that could help chart a revitalized form of feminist politics within youth-driven popular culture.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".