The privilege of knowing better: Female millennial demographics and the representation of homophobia on teen TV
Bibliographic record
Abstract
Abstract The 2010–11 seasons of 90210 (2008–13), Degrassi (2010–15), Glee (2009–15) and Pretty Little Liars (2010–17) represent homophobia as arising from closeted teens, cisgender male ‘jocks’, racialized characters and immigrants. Rather than locating homophobia and heteronormativity within the social fabric and minds of all who have been steeped in American and Canadian hegemonic beliefs, homophobic characters are framed as rare, anachronistic and out-of-step with the seemingly post-homophobia ethos they exist within. Drawing on media trade publications, I place these patterns for representing homophobia in their market context, arguing that profit motives encourage representations of gay teens and homophobia that suggest homophobic beliefs are the domain of ‘others’, apart from the privileged viewer of teen TV: affluent, educated, female, white and non-white millennials aged 18–34. The target viewers are invited to see themselves as innocent and enlightened in relation to homophobic others, while prescribing a cure to homophobia that emphasizes individual change over social change.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".