Bibliographic record
Abstract
Speculative fiction opens doors for imagining beyond what is possible, conventional or acceptable. Speculative fiction has an acute ear for the social, the scientific and for political developments and change, all of which are prominent topics. Reproduction and parenthood are pertinent social questions that are constantly renegotiated in various arenas. By investigating representations of family-making and reproduction in speculative fiction, the research presented in Populating the Future: Families and Reproduction in Speculative Fiction not only adds to the field of speculative fiction scholarship, but also contributes to the more general discussion about reproduction and parenting. Speculative fiction operates as thought laboratories that make connections between discourses visible. It highlights power structures that can be difficult to detach and represents difficult and abstract issues more concretely. As such, speculative fiction demonstrates the complex entanglement of reproduction with issues of gender, power and agency. By facilitating thought experiments and illustrating alternatives, speculative fiction also enables the representation of new family structures and reproductive technologies, thus paving the way for discussions about various practices and their possible consequences. Due to its multidisciplinary approach, this book will be of value to scholars and students of various disciplines, such as literature studies, philosophy, ethics, political science, the social sciences and gender studies. It will also be a useful resource in teacher training programmes, as well as to a more general audience interested in speculative literature, politics, society, gender and ethics.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.029 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".