Homophobia, heteronormativity, & internalized homophobia: Queer emotion management in mainstream romantic comedies
Bibliographic record
Abstract
In many cases, movie audiences internalize the values they see expressed on-screen (Hall, 1997; Raley & Lucas, 2006; Sutherland & Feltey, 2013). For North American audiences, this often means internalizing heteronormative values (Benshoff & Griffin, 2006; Chung, 2007; Sutherland & Feltey, 2013). This does not mean queer characters are excluded from North American film and television, but when they are included, the queer community is presented from heteronormative perspectives (Chung, 2007; Raley & Lucas, 2006). Despite this, queer audiences watch these performances and may learn how others expect them to cope when facing similar struggles, conflicts, or intolerances (Chung, 2007; Raley & Lucas, 2006). While many studies examine the representation and reception of the queer community in media (e.g., Cooley & Burkholder, 2011; Raley & Lucas, 2006; Sink & Mastro, 2018), fewer studies investigate or recognize the role of emotions in queer discourse. To address this, the following study conducted a thematic decomposition analysis (e.g., Bower et al., 2002; Stenner, 1993; Wollett et al., 1998) of seven North American films that were cross-listed as both gay/lesbian and romantic comedies, and were produced and released between 1996 and 2018. In combination with the analysis and a symbolic interactionist approach to understanding emotions (e.g., Armon-Jones, 1988; Hochschild, 1983; Goffman, 1959; Scheff, 1977, 1988), I proposed five coping strategies used by queer film characters: humor, conforming, avoiding, ignoring, and accepting. While some characters are able to accept their sexual orientation despite intolerances, other characters struggle to overcome shame associated with their identity. While these films may validate the queer community by providing visibility, with only a few examples of pride, these same films suggest that there is an abundance of shame associated with being queer.
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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 | 0.005 | 0.011 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".