Heteronormativity and Toxic Masculinity in Stephen Dunn’s Closet Monster
Bibliographic record
Abstract
Premiering at the 2015 Toronto International Film Festival to great acclaim (it won the award for the Best Canadian Feature, and was eventually included in the IFF’s annual Canada’s Top Ten), Stephen Dunn’s Closet Monster employs monsters metaphorically, primarily in order to express the psychological damage of violent homophobia and to comment on toxic masculinity. Yet monstrosity is not merely a metaphor but also a strategy: the protagonist, a closeted teenager named Oscar, appropriates both monstrosity and heroic narratives in order to manage life as a homosexual person in a deeply homophobic environment of contemporary suburban Canada. The magic realist details which permeate Closet Monster – the talking pet hamster, the scenes seamlessly fusing body horror with realism – exemplify the film’s poignant, almost fairy-tale-like approach to “homophobia-related violence” and the effects of PTSD initiated by Oscar’s witnessing of violent enforcement of gender normativity in his childhood. This paper proposes to examine the politics of the film, in particular Dunn’s deployment of monstrosity in the representation and condemnation of violent homophobia and toxic/hegemonic masculinity. As these issues are inextricable from the wider cultural context of normative gender and sexuality, Dunn’s criticism of heteronormativity is discussed as well. It is in this context, also, that the film’s depiction of the production, policing and elimination of “monstrous” (i.e. homosexual) bodies is examined. Article received: March 11, 2018; Article accepted: April 10, 2018; Published online: September 15, 2018; Scholarly analysis or debate How to cite this article: Petković, Danijela. "Heteronormativity and Toxic Masculinity in Stephen Dunn’s Closet Monster." AM Journal of Art and Media Studies 16 (2018): 43−54. doi: 10.25038/am.v0i16.253
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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 | 0.000 |
| Science and technology studies | 0.013 | 0.022 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".