Moral Adaptations: How Ann-Marie MacDonald’s <i>The Arab’s Mouth</i> became <i>Belle Moral</i>
Bibliographic record
Abstract
For an artist to return to and successfully revise work that has been completed years before can be tricky. To be sure, there are examples – such as James Joyce’s early novel, Stephen Hero, revised to become Portrait of the Artist as a Young Man, or John Fowles’s novel The Magus, first published in 1966 but re-published in a revised version in 1977 – where there seems to be a general agreement that the mature artist’s revisions have yielded a more powerful and satisfactory work. But, for every such example, we may find at least one or more in which the older artist’s revisions are deplored as meddlesome intrusions by those who know and cherish the younger artist’s work. For instance, W.H. Auden’s attempts to transform his early poems into works he could stand by in maturity seem, from this distance, both a little desperate and ultimately futile.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".