Monster Menstrual: Women, Girls, and Queer Horror in <i>Stranger Things</i>
Bibliographic record
Abstract
The 2016 Netflix series Stranger Things is a calculated homage to the 1980s; in addition to its period setting and the inclusion of star Winona Ryder, it further incorporates tropes and references from popular 1980s’ films including Stand By Me, E.T., and The Goonies. But the series does not only draw from stories about young boys coming of age in America; it also calls back to Stephen King’s Carrie and other science fiction and paranormal images marked by the fear of female sexuality. Stranger Things’ slimy passages, alien umbilical cords, “demogorgon” vaginas dentata, and liminally gendered and sexualized characters all speak to long-standing fears about the monstrous feminine, and further invoke the monstrous queer. Stranger Things is a contemporary take not only on 1980s’ cinema but on classical feminine body horror, and this analysis interrogates the series’s positioning as a feminist text.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".