Bibliographic record
Abstract
W W W' , readers intuited that Atwood was portraying a delicate negotiation between science and art." e scientifi c imagination balances the mythic imagination, " wrote Eleanor Cook in a review, "as in the two epigraphs, one from Hawking and one from a mythical Genesis." But when critical interpretations of science in the novel began to appear, that readerly intuition was challenged as some critics concluded that science was a negative force in the novel-an extension of an empiricist and racist patriarchy.Molly Hite, for example, calls the physicist character Stephen "a representative of the white, Western, male oppressor class" who suff ers simultaneously from an "unawareness of the disciplinary system and of his own visibility within that system" (, ).June Deery writes, "Atwood concludes that what links science, imperialism, and patriarchy is control of the body.…Western scientists … have traditionally been depicted as subduing nature as female.… ey share some of the same attitude as colonists: conquer, map, know, and sell" ().Susan Strehle suggests that the patriarchy is active in Cat's Eye in the strictest sense, attributing all forms of Elaine's suff ering to "the fathers" in the novel who enact "hierarchies of value that place women at the bottom and girls below them." She identifi es the "paternal authorities" as "home,
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 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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.081 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".