Sex-Bots Revisited: Bioethics and Parody in Margaret Atwood’s The Heart Goes Last (2015)
Bibliographic record
Abstract
Margaret Atwood, one of Canada's most celebrated and iconic writers, has shown an interest in exploring issues relevant to contemporary audiences in her fiction since the publication of her first novel, The Edible Woman (1969). Atwood's diverse body of literary work addresses important current concerns such as gender inequality, technology, consumerism, and the climate crisis. In her more recent dystopian novel, The Heart Goes Last (2015), Atwood imagines the US as a wasteland devastated by economic crisis. Within this fictional landscape, a social experiment emerges as a seemingly ideal social model, while the survivors must navigate new and complex circumstances. The novel contains several instances of parody and satirical commentary on contemporary consumerist practices and the obsession with technology and artificiality. Sex dolls, referred to as prostibots in The Heart Goes Last, play a pivotal role in Atwood's exploration of technological progress and its implications for humanity. Drawing on theories of posthumanism, bioethics, and narratology, this paper aims to analyse Atwood's inherently parodic construction of sex dolls as Gothic embodiments of artificial others. These prostibots not only redefine what it means to be human but also draw attention to the anxieties associated with the emergence of posthuman replicas, which, in turn, raise various biological and ethical issues.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.041 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".