"Memorization and Memorialization: 'The Burial of Sir John Moore after Corunna' "
Bibliographic record
Abstract
This article addresses the rubric of "memory and materiality" by considering how works of literature held within individual minds might have contributed to material changes in the world at large. For a good proportion of both the nineteenth and twentieth centuries, the most important relationship between literature and millions of English-speaking people was created by one particular pedagogical regimen: the memorization and recitation of short poetic pieces. I take as my test case a single work from the schoolroom canon—Charles Wolfe's 1817 poem, "The Burial of Sir John Moore after Corunna"—and examine the various ways in which lines and phrases from these verses were explicitly or implicitly cited by people caught up in the bloody turmoil of the American Civil War, the conflict which first witnessed the widespread development of state-sponsored practices to commemorate the corpses of common soldiers. I argue here that the presence of Wolfe's poem in the minds of ordinary individuals played its part in creating the social expectations that led to the establishment of the National Cemeteries in the United States, and thus, in due course, the mass memorialization of World War I.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".