(Un)Human Relations: Transhumanism in Francesco Verso’s <i>Nexhuman</i>
Bibliographic record
Abstract
Transhumanism is an international movement which espouses the idea that any human organ, function, sense, ability, can be augmented and ameliorated with the judicious use of technology. The ethical, cultural, social, biological, economic implications for this view are far-reaching and point to a number of complex questions whose solution eludes researchers so far. One of the possible sources for answers to these is found in science fiction. While transhumanism is a relatively recent phenomenon (last 25 years or so), science fiction published in English that mirrors some of its issues and ideas has been flourishing for at least as long. In Italy, science fiction is starting to enjoy popularity and critical depth in no small measure due to the untiring abilities of a number of authors. This article analyzes the intersections between human and machine as they are portrayed in Francesco Verso’s Nexhuman. Francesco Verso has published 4 award-winning science fiction novels and a number of short stories. Nexhuman offers a considerable narrative construct which paints a dystopian future where trash is formed and re-formed, sold and reworked; however, strong emotions are not absent, since love may flourish in this “kipple”-laden setting, as well as violence and obsession. Transhumanist ideas explicitly dealt with in the novel include the end of death, the question of the soul, mind uploading, limb prosthesis, the co-existence of humans with mind-uploaded beings. The amalgam between human and machine does away with the Self and the Other(s) as separate entities and constructs a completely different Weltanschauung. Nexhuman is not only a transhumanist trailblazer within the flourishing arena of Italian science fiction, but also a springboard for deeper understanding of what makes us human and the extent to which binary categories need to be overcome in order to create a more accommodating world.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".