Cinematic Inclusiveness: Horror Cinema’s Portrayal of Mental and Physical Disabilities
Bibliographic record
Abstract
The relationship between disability and horror cinema has been complicated. The majority of horror films have associated disability with monstrosity, and represented it as a phenomenon to fear or destroy. Paul Longmore, a leading academic scholar in disability studies, states that according to Hollywood, “the presence of individuals with visible handicaps would alienate consumers from their products,” and is the leading force behind the lack of minority representation in cinema (14). However, changes in the genre are taking place as horror films have begun representing a range of mental and physical disabilities with compassion and sensitivity. Angela Smith, a disabilities and film studies academic scholar, explains that horror cinema frequently “locate[s] horror less in singular and deformed bodies and more in dominant social structures, including the family and American culture,” because disabilities are a literary device to inform the audience about an underlying issue (“Introduction” 24). Moreover, they purposely “force viewers to confront spectacles of impairment as projections of their own socially, scientifically, and cinematically shaped prejudices” (Smith, “Chapter 3” 133). As the presence of disabilities becomes more prominent in horror cinema, so does the audience’s understanding and awareness about mental health issues and physical impairments. Disabilities are identified as a mental or physical condition that makes it difficult for an individual to interact with society the same way a non-disabled person can. This paper analyzes deafness, blindness, schizophrenia, and depression in films that were released over the last decade. The four recent horror films I base my discussion on are John Krasinski’s A Quiet Place (2018), Jennifer Kent’s The Babadook (2014), Pearry Reginald Teo’s The Assent (2019), and Fede Alvarez’s Don’t Breathe (2016). My goal is to show how in aligning the audience with the character’s struggles, they are normalizing and making the audience consciously aware of disabilities in horror films.
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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 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".