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Record W7058599114

Nonhuman Animals in Margaret Atwood's Fictional Worlds

2024· dissertation· en· W7058599114 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of Digital Objects for Teaching Research and Culture (University of Valencia) · 2024
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipRhetorical questionContext (archaeology)ForgettingObject (grammar)NarrativeField (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

From the very origins of human civilization, nonhuman animals have been used as endless literary tools, in some cases as part of rhetorical figures, in others as substitutes of humans, or even as the object of discussion. Despite their prominence, what most narratives seem to lack is the voice of the actual nonhuman animals, oftentimes forgetting to give them the possibility of being individuals with their own biological and emotional interests and needs. This tendency has slightly changed amongst writers in the last decades due to the awareness raised by the critical field of Animal Studies and its resistance to see nonhuman animals as a collectivity that is deprived of language, reason, soul, or individuality. A writer who has acknowledged the potential that nonhuman animals have and frequently incorporates them in her oeuvre is the Canadian author, Margaret Atwood. She offers an engaging insight into how nonhuman animals are perceived within her Canadian context and has even challenged the common roles assigned to them in her extensive literary career. The ecological revindications and feminist elements that are integrated in her works make Atwood an author of considerable interest to study from new perspectives. Thus, this dissertation borrows from the most recent scholarship on (Critical) Animal Studies and Ecofeminism to address the analysis of how nonhuman animals are represented in Atwood’s novels and graphic novels. To do so, the corpus encompasses the seventeen novels that have been published by Margaret Atwood, ranging from the late sixties until the most recent one in 2019, and her two graphic novels. Additionally, I examine whether nonhuman animals are presented as sentient beings and if Atwood incorporates the theories from animal rights movements that surfaced in the seventies and have evolved into the discipline of ethics to the present day. Moreover, by placing the focus on the transversal role that nonhuman animals have within the novels published throughout seven decades, I analyze if an evolution can be appreciated in their treatment. Lastly, I investigate how she frames the animal question within the perspectives of gender and feminism given the importance that these themes have in Atwood’s literary works. Consequently, the analysis of Atwood’s novels and graphic novels is classified into six different categories regarding the representation of nonhuman animals. I begin by studying the construction of the Canadian identity of Atwood’s characters through the wildlife that surrounds them and their identification with nonhuman animals. Then, I analyze how nonhuman animals are framed into cultural beliefs and folklore, with a special focus on religion. Subsequently, I apply Carol J. Adam’s theory of the absent referent to examine the connections between the exploitation and silencing of women and nonhuman animals. Next, I explore the dominance and commodification in nonhuman animals’ death, which includes their employment in artistic creations or within the scientific community. Following this, I focus on how nonhuman animals are represented in Atwood’s dystopian narratives by incorporating concepts such as slow violence, rewilding, ustopia and zoopolitical citizens. Lastly, I draw on Josephine Donovan’s concept of aesthetics of care to examine the interspecies entanglements found between human and nonhuman animals.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.289
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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