Human-Viral Hybrids as Challenge to the Outbreak Narrative and Neo-Liberal Biopolitics
Bibliographic record
Abstract
The article starts with Jean-Luc Nancy's recent supposition that the Covid-19 pandemic has revealed the precarious foundations of the Western developed and progressive societies, laying bare the mechanism of their biopolitical regime.Following Nancy's argument, the article draws first on the example of a few recently published French Corona Fictions which depict contagion as one of many, tightly entangled factors, mostly of an anthropogenic nature.From this perspective, the article then offers a close reading of two speculative pandemic fictions fabulations of the turn of this century: the novel The Blood Artists (1998) by American novelist and screenwriter Chuck Hogan, and Rifters trilogy (1999)(2000)(2001)(2002)(2003)(2004)(2005) by Canadian SF author Peter Watts.Both revisit and morph the outbreak narrative, introducing a new type of protagonist -the human-viral hybrid -to reveal the workings of biopower and geontopower as yet another form of structural violence inherent in the late liberalism.1 The article was written within the framework of the project 'Epidemics and Communities in Critical Theories, Artistic Practices and Speculative Fabulations of the Last Decades' (UMO-2020/39/B/HS2/00755), which was funded by the Polish National Science Centre (NCN).2 Although well over 100 countries worldwide had instituted either a full or partial lockdown and many others had recommended restricted movement for some or all of their citizens by the end of March 2020, not all of the world 'froze' in the same way, see e.g.
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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 | 0.005 | 0.019 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".