The "Impassable Gulf" and the Epistemology of Ignorance in Mary Barton
Bibliographic record
Abstract
Abstract: What do the wealthy and powerful know about the sufferings of the poor in Elizabeth Gaskell's Mary Barton ? The answers that Mary Barton offers are, variously, that the wealthy and powerful do know of the suffering of the poor, that they do not know but can be educated, and that they cannot be educated and thus will never know. This paper argues that this last possibility—that education may be unavailing and that the rich and the middle classes may remain in ignorance about the suffering of the poor—is at the centre of a crisis of epistemology in the novel. This crisis is specifically articulated in the novel's allusions to Jesus's parable of Dives and Lazarus, in which the rich man Dives seems not to see the hungry man Lazarus at his very gate. The parable is alluded to twice by John Barton, who is seized by its powerful representation of the relationship of rich and poor, and it provides a focal point for an investigation into the production not of knowledge but of ignorance. Employing the epistemologies of ignorance of Robert N. Proctor, Londa Schiebinger, Charles W. Mills, and Nancy Tuana, this paper investigates the making of ignorance in Mary Barton .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".