Bibliographic record
Abstract
Jane Urquhart's remarkable novel The Stone Carvers (2002) imagines a young woman, of European wood-carving ancestry, travelling to Vimy in northern France from a village near Hamilton, Ontario. Disguised as a man, she obtains work on the Canadian monument and early one morning she steals into the workshop to carve the face of one of Walter Allward's allegorical figures in the image of her dead lover Eamonn. When Allward discovers her, he is angry that she has ‘ruined’ his torchbearer, explaining ‘he had wanted this stone youth to remain allegorical, universal, wanted him to represent everyone's lost friend, everyone's lost child’. Allward, we are told, ‘wanted the stone figure to be the 66,000 dead young men who had marched through his dreams when he had conceived the memorial’. But the face Klara was carving ‘had developed a personal expression’, it was ‘becoming a portrait’, and this had ‘never been his intention’. Confronted by this determined young woman, Urquhart's fictional Walter Allward realises that she has ‘allowed life’ to enter his monument and relents: ‘you can finish carving his face’, he agrees. Klara Becker's desire to impose the face of one particular young man onto the body of Allward's universal young man can be seen as a metaphor for the philosophy of commemoration that prevailed on the Western Front, and in Europe generally, after the war.
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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 | 0.001 | 0.001 |
| 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 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".