Corpus Christi, Corpus Cyborgensis, and the Body Politic: The Passion Play of <i>RoboCop</i>
Bibliographic record
Abstract
Director Paul Verhoeven describes his RoboCop (1987) as “an American Jesus,” but he also notes that “I don’t believe in the resurrection of Jesus in any way.” His irreverent satire echoes the “ironic blasphemy” of Donna Haraway’s “A Manifesto for Cyborgs” (1985) and other specifically postmodern theological readings of cyborg as saviour. Haraway’s more optimistic outlook is indirectly challenged by John O’Neill, who in his Five Bodies (1985) warns about losing human semiology to a capitalistic mechano-morphic society. Peter Travis (1987) uses O’Neill’s thesis to address the notion of the corpus Christi as the metaphor for the body politic in the late medieval English Corpus Christi pageants, and 1970s and 1980s scholarship on the famous Corpus Christi cycle plays of later medieval England generally focused on the role that having enacted Christ figures in the plays served to reunify a civic society devastated by economic and social turmoil following the Black Death. Verhoeven’s Christological imagery in RoboCop thus builds upon a long tradition of dramatic performances of the life of Christ. In close adherence to the larger contemporary social issues presented in the late medieval dramatic milieu, RoboCop successfully represents a Christ figure whose broken body reflects Regan-era civic weakness and decay while simultaneously possessing a revolutionary salvific power.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".