“Those who suffer the ecstasy of the animals”
Bibliographic record
Abstract
This paper takes as its starting point the notions of blending and conceptual metaphors in order to advance a new reading of Atwood’s fiction, one which sees it as parabolic stories projecting the conceptual metaphors “man is a wild animal” and “nature is a victim of injury”. Atwood’s Wilderness Tips (1991), The Tent (2006) and the MaddAddam trilogy not only develop their own detailed blueprints of the Canadian fauna, but they also reveal Atwood’s eco-animalism blending together men and animals, and leading to genetic mixing of species. By spending her childhood in the bush among wild bears, silver foxes, otter, weasels and muskrats, Atwood experienced the horrors of animal abuse. I intend to track through these references and look at the issues – attitudes to human crimes against nature, question of animal representations in narrative writing, historical and personal past related to eco-animalism etc. – which they raise. But my central purpose will be to re-read Atwood’s eco-animalism from a cognitive perspective, projecting Atwood’s thoughts on the Canadian waste land, inhabited by genetically modified animals and by Gothicized animal figures. In line with T. S. Eliot’s The Waste Land, in which thoughts are an entangled mass of animals, Atwood seems to employ new animal metaphors to convey their eco-bond with nature and to denounce all forms of animal exploitation. Through wild bears, aquatic birds, glow-in-the-dark rabbits, friendly, scentless rakunks (half-skunk, half-raccoon), wolvogs, rakunks, liobams, and so forth, I suggest, Atwood attempts to build into her works a kind of eco-warning which T. S. Eliot’s The Waste Land extols with important socio-cultural consequences for the Canadian outcasts denouncing in Eliot’s words “those who suffer the ecstasy of the animals”.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".