The end of times, the end of signs? Cyberpunk novels, nuclear war, and virtual realities
Bibliographic record
Abstract
This thesis examines the representation of virtual reality and nuclear apocalypse in three cyberpunk texts – Neuromancer by William Gibson, Snow Crash by Neal Stephenson, and Tea from an Empty Cup by Pat Cadigan – and finds that each novel uses virtual and nuclear imagery to explore signification. Each text’s vision of virtual reality is informed by either a Platonic or Baudrillardian theory. Neuromancer and Snow Crash both suggest that the virtual world is the world of Forms because its signs (graphics and code) are wholly commensurate with their referents (aspects of the virtual world itself). Tea from an Empty Cup, however, suggests that the virtual world consists of empty signs whose original referents (an absent framing world and an untold nuclear history) are missing and beyond recovery, because nothing exists outside of the simulation. Each novel’s depiction of virtual reality as a space of either ideal truth or endless simulation correlates (through accordance or opposition) with its conception of nuclear apocalypse. Neuromancer follows Derrida in suggesting that the a-symbolic nuclear referent is the only possible true referent, as the apocalypse represents a simultaneous moment of truth revealed and reference lost. In contrast, both Snow Crash and Tea align with Baudrillard’s reading of the nuclear as the height of simulation, and the attendant implication that simulation is always already post-apocalyptic. Whether the nuclear event is figured as a moment of revelation or pure simulation, each text points to the impossibility of imagining (even science fictionally) a post-nuclear future, and thus, each reflects on its own end (in both senses of the word) as a representational work. Accordingly, I read cyberpunk as a metafictional reflection on the life and death of a novel.
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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 | 0.003 |
| 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 | 0.023 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.003 |
| 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".