Our televisions, our selves: popular (in)visiblity, marginalized identities and the politics of Queer as folk
Bibliographic record
Abstract
What happens when groups who have been marginalized within popular culture become privileged enough to gain complex televisual representation? The U.S. cable television show Queer As Folk (QAF) aired in Canada from 2000 to 2005 depicting a White, middle-class community of gays and lesbians. The show's popularity makes it a promising site to study gay men's emergence into complex televisual representation. First, I outline a brief history of gay and lesbian representation on television and explore tensions that arise when popular visibility of marginalized identities is entangled in commodity culture---when communities of resistance become "niche markets." I then conduct a critical textual analysis, using Hall's notion of the preferred reading, to argue that QAF offered a depiction of White, middle-class gay men that transgressed against the ideal sexual citizen, while couching its transgressions within White supremacy, the superiority of the middle and upper-classes, and male privilege. Finally, to counter this relatively closed reading of the series, I offer an audience reception study of forty avid QAF viewers who participated in this study through an email-circulated survey, focus groups and personal interviews. I explore how viewers "use" QAF outside the time-space of viewing to build their personal identities as gays, lesbians, queers and gay-positive straights, to participate in "conversational communities," and as a source of knowledge about communities or practices they do not have personal experience with. I trace the negotiations viewers make as they view the show as simultaneously "over-the-top, unreal entertainment" and "a real depiction of queer life" that acts as a valid source of information about "gay culture." Additionally, I highlight how viewers read "critically" in rather different ways, and interpret the same QAF image as hegemonic or counter-hegemonic depending on the intertextual comparisons they make and the "real world" knowledge they bring to bear on the representation. This dissertation explores the political economy of "gay TV" in the early 2000s, offers a critical and qualitative textual analysis of QAF, and details viewers' readings of the series that exceed and complicate the binaries of oppositional and dominant, hegemonic and counter-hegemonic, demanding a more complex frame for analysis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".