Climates of Mutation: Posthuman Orientations in Twenty-First Century Ecological Science Fiction
Bibliographic record
Abstract
Climates of Mutation contributes to the growing body of works focused on climate fiction by exploring the entangled aspects of biopolitics, posthumanism, and eco-assemblage in twenty-first-century science fiction. By tracing out each of those themes, I examine how my contemporary focal texts present a posthuman politics that offers to orient the reader away from a position of anthropocentric privilege and nature-culture divisions towards an ecologically situated understanding of the environment as an assemblage. The thematic chapters of my thesis perform an analysis of Peter Wattss Rifters Trilogy, Larissa Lais Salt Fish Girl, Paolo Bacigalupis The Windup Girl, and Margaret Atwoods MaddAddam Trilogy. Doing so, it investigates how the assemblage relations between people, genetic technologies, and the environment are intersecting in these posthuman works and what new ways of being in the world they challenge readers to imagine. This approach also seeks to highlight how these works reflect a genre response to the increasing anxieties around biogenetics and climate change through a critical posthuman approach that alienates readers from traditional anthropocentric narrative meanings, thus creating a space for an embedded form of ecological and technoscientific awareness. \n \nMy project makes a case for the benefits of approaching climate fiction through a posthuman perspective to facilitate an environmentally situated understanding. By mapping the aspects of bare life, posthuman becomings, multispecies community, and environmental agency that situate these texts within their climate-focused twenty-first-century contexts, my dissertation models its own series of entanglements. It also reveals areas of concern that include infectious agencies, subversions of biopolitical containment, and the co-constitutive transformative powers of the environment and nonhuman life. Climates of Mutation addresses the ways that these contemporary science fiction narratives have responded to cultural and scientific developments to invite critical engagement from readersespecially in terms of embracing concepts of environmental assemblage and imagining potential multispecies futures. By taking an assemblage approach to these works of posthuman ecological science fiction, my project draws attention to how they critically subvert anthropocentrism by privileging nonhuman and environmental agencies in which humans are an entangled part of biopolitical forces, multispecies collectives, and ecological assemblages.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.031 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".