EVOLUTIONARY DISCOURSE AND THE CREDIT ECONOMY IN ELIZABETH GASKELL'S<i>WIVES AND DAUGHTERS</i>
Bibliographic record
Abstract
When Elizabeth Gaskell died inNovember 1865, she left unfinished her final novel,Wives and Daughters(1864–66). TheCornhill Magazine's editor, Frederick Greenwood, published a tribute to Gaskell with the novel's final installment. Her fiction, he wrote, pulls you from “an abominable wicked world, crawling with selfishness and reeking with base passions into one where there is much weakness, many mistakes, sufferings long and bitter, but where it is possible for people to live calm and wholesome lives . . .” (Gaskell 685–86; ch. 60). As Linda K. Hughes and Michael Lund observe, Greenwood shaped Gaskell's reputation for a hundred years “as an author whose work captured . . . the idyllic charm of a lost era” and took “readers away from unpleasant realities” (158). Notably, Greenwood's list of “unpleasant realities” (wickedness, selfishness, and base passions) implicitly refers to capitalism — that is, to the economic world of the 1860s from which Gaskell ostensibly encouraged her readers to retreat.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 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".