The zombie in the grey flannel suit: Romero’s classic Dead trilogy and metaphors of mass subjectivity
Bibliographic record
Abstract
This article explores the relationship between zombies and ‘mass subjectivity’ through examining the motifs, as well as the critical and scholarly reception, of Romero’s classic Dead movies and their successors. Contrasting the ‘fast zombies’ of later films, Romero’s zombies are withered and decayed versions of everyday people: tattered and frayed at the edges, their colours muted, their skin and clothing rendered in greyed-out tones. They are the mundane dead, animated. Romero’s filmic horror taps an uncanny rendering of the everyday. Gardens, streets and malls are made strange by the homogeneous mob progressing in endless lines, murmuring incoherencies and striving to just be. We can locate the visual character of the zombie within a genealogy of metaphors of mass subjectivity such as the man of the crowd, the badaud figure, constantly searching for a place, but symbolically disarticulated. By considering the sometimes comic, sometimes tragic and often horrific Romero zombie in a lineage of visual and literary figures linked to mass subjectivities – the man in the suit, the monstrous man, the man of the crowd, the badaud – this article answers the question: What does thinking about the relationship between the Romero zombie and mass subjectivity enable us to do, think or observe?
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".