Bibliographic record
Abstract
When describing a landscape, ocularcentric approaches tend to dominate human’s understanding of their surroundings while disregarding alternative ways of conceiving the world through other senses which have often been more associated with the “animal-side” given their apparent subjectivity. To challenge this anthropocentric perspective, this chapter undertakes a close reading seven of Atwood’s novels—Surfacing (1972), Lady Oracle (1976), Life Before Man (1979), Cat’s Eye (1988), The Robber Bride (1993), Alias Grace (1996) and The Blind Assassin (2000)—to analyse how the landscape is reflected, particularly to comprehend if these passages go beyond a traditional visual representation. Thus, the chapter studies how Atwood transports the reader to the Canadian landscape through the presence of nonhuman animals and how they shape human’s understanding of space and time. To do so, it applies the theories of Canadian composer and environmentalist Murray R. Schafer in his book The Soundscape: Our Sonic Environment and the Tuning of the World (1977) and Ben De Bruyn’s reenvisioning of the concept of “soundscape” in The Novel and the Multispecies Soundscape (2020) to survey how literature can become a medium through which landscapes can be aesthetically experienced through the different senses of humans. To better illustrate the interactions between human and nonhuman animals in shaping the landscape and how they are perceived by Atwood in her works, the analysis distinguishes between mammals, birds and arthropods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.163 | 0.001 |
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; both teacher heads agree on what is shown here.
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".