Bibliographic record
Abstract
In Margaret Atwood’s fiction, homes are places of coercion, danger, and dread: Rennie’s apartment in Bodily Harm (1981), invaded by a stranger who leaves a threatening rope; the Commander’s house in The Handmaid’s Tale (1985), where women are categorized and used according to their function; Elaine’s childhood home in Toronto in Cat’s Eye (1988), suffused with anxiety over the endless imperfections her friends detect in her; the apartment in The Robber Bride (1993) where Karen’s mother beats her and the basement room where her Uncle Vern sexually abuses her; the apartments of Jane and Vincent in “Age of Iron” from Wilderness Tips (1991), full of “purposeless objects adrift in the physical world” (162); the Kinnear house in Alias Grace (1996), scene of two brutal murders; or the deserted houses of Oryx and Crake (2003), containers for the unburied dead. While Atwood’s own childhood homes were by all accounts happy, though impermanent places, 1 the homes in her fiction threaten or stifle their inhabitants, especially women. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".