Bibliographic record
Abstract
In Pet Projects , Elizabeth Young joins an analysis of the representation of animals in nineteenth-century fiction, taxidermy, and the visual arts with a first-person reflection on her own scholarly journey. Centering on Margaret Marshall Saunders, a Canadian woman writer once famous for her animal novels, and incorporating Young’s own experience of a beloved animal’s illness, this study highlights the personal and intellectual stakes of a “pet project” of cultural criticism. Young assembles a broad archive of materials, beginning with Saunders’s novels and widening outward to include fiction, nonfiction, photography, and taxidermy. She coins the term “first-dog voice” to describe the narrative technique of novels, such as Saunders’s Beautiful Joe , written in the first person from the perspective of an animal. She connects this voice to contemporary political issues, revealing how animal fiction such as Saunders’s reanimates nineteenth-century writing about both feminism and slavery. Highlighting the prominence of taxidermy in the late nineteenth century, she suggests that Saunders transforms taxidermic techniques in surprising ways that provide new forms of authority for women. Young adapts Freud to analyze literary representations of mourning by and for animals, and she examines how Canadian writers, including Saunders, use animals to explore race, ethnicity, and national identity. Her wide-ranging investigation incorporates twenty-first as well as nineteenth-century works of literature and culture, including recent art using taxidermy and contemporary film. Throughout, she reflects on the tools she uses to craft her analyses, examining the state of scholarly fields from feminist criticism to animal studies. With a lively, first-person voice that highlights experiences usually concealed in academic studies by scholarly discourse—such as detours, zigzags, roadblocks, and personal experience—this unique and innovative book will delight animal enthusiasts and academics in the fields of animal studies, gender studies, American studies, and Canadian studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.387 | 0.106 |
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".