Magna Mater : women and eugenic thought in the work of H.P. Lovecraft
Bibliographic record
Abstract
H.P. Lovecraft is considered one of the most influential and important speculative writers of the 20th century. Despite the eugenic concerns inherent in many of his stories, much of his output has not been analyzed against the pervasive “scientific racism” of his time. This thesis looks at Lovecraft’s depictions of women and sees them as strongly related to eugenic thought, representing in various ways the biological dangers associated with unfit women. Lovecraft’s women embody the worries of miscegenation, show the results of the unfit giving birth, and ultimately showcase the collapse of society under the weight of monstrous Others. Therefore, though Lovecraft does not feature many women in his stories, he nevertheless manages to construct them as agents of biological chaos, much in the same way eugenicist thought commonly portrays unfit women as highly dangerous to the fabric of the nation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.024 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".