“Gay Now”: Bisexual Erasure in Supernatural Media from 1983 to 2003
Bibliographic record
Abstract
Bisexual representation in media has historically lagged behind gay and lesbian representation. Given that bisexual people experience poorer mental health measures when compared to heterosexual and gay people, positive representation could have a significant impact on bettering bisexual people’s lives. Additionally, examining historical trends of bisexual representation may help us better contextualize the current state of bisexual representation. This paper conducts a thematic analysis of three bisexual women from two texts: Miriam and Sarah from The Hunger, a 1983 movie, and Willow from Buffy the Vampire Slayer, a 1997–2003 television show. Although Miriam, Sarah, and Willow all exhibit attraction toward both men and women, they are commonly referred to as lesbians. The erasure of potential readings of their sexualities as bisexual occurs through three streams: downplaying attraction to men, describing erotic scenes as “lesbian,” and formulating bisexuality as an invisible identity. Further, the supernatural context of these texts creates a connection between bisexuality and monstrosity. However, these texts occasionally subvert traditional methods of erasure and are thus praised as progressive, rather than criticized, by reviewers. These texts imply that potential bisexual readings of characters in the 1980s and 1990s were erased by both the texts themselves and their reviewers, in favor of characterizing progression of lesbian representation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".