Bibliographic record
Abstract
In Tolstoy’s artistic pursuit of the meaning of human life, femaleness plays a crucial, if not always enviable, role. Especially in the first half of his writing career Tolstoy created female characters who often embodied the potent and volatile emotions aroused by love. Studied both as individuals and as a chronological aggregate, these heroines rehearse and refine over time a quest to find and put into practice the elusive concept of “true love.” This search almost invariably assumes transgression. A major impediment to a full reading of Tolstoy’s fiction, especially to his writing on women, centers on a tendency to equate his art and his life, that is to say, to interpret his art as a barely disguised annotation to his personal beliefs. According to one such view, Tolstoy’s contempt for women’s liberation (called in nineteenth-century Russia “the women question”) finds fictional expression in his ideally virtuous mothers - most conspicuously Natasha in War and Peace and Kitty in Anna Karenina - whose preoccupation with their children satisfies all needs and desires and exhausts all creative potential. Following this line of thinking, Anna Karenina – despite any sympathetic traits she may possess – is condemned because she subverts her biologically determined maternal role and destroys the sanctity of her family. For this violation of natural law, she must die.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".