Garden Politics in Margaret Atwood’s Selected Speculative Fiction Novels
Bibliographic record
Abstract
Following Shelley Saguaro’s belief that the incorporation of a garden in a text is reflective of ideological aesthetic premises, this paper intends to study the representation of gardens in two speculative fiction novels by the prominent Canadian writer, Margaret Atwood: “The Handmaid’s Tale’ (1985) and “The Year of the Flood” (2009). In her books Atwood presents the readers with an apocalyptic vision of an environmental crisis resulting from profit maximisation in capitalist societies. The patriarchal domination over nature in the novels is intrinsically connected to the domination over women. The female protagonists’ bodies are represented in terms of marketable value, as every part of their body can be described as a resource for extraction. Referring to ecofeminist critics including Carolyn Merchant and Karen J. Warren, as well as the works of ecocritical scholars such as Lawrence Buell, the paper examines the way Atwood’s literary gardens reflect on the complex issues of environmentalism, religion, technology and gender politics. Special attention is paid to flower imagery as well as to the animals living in Atwood’s literary gardens and their connection to the female protagonists. Since the paper discusses novels that were published over 20 years apart, it reveals the way Atwood’s perspective on the above-mentioned issues has evolved over time.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".