Bibliographic record
Abstract
Lynda Van Devanter’s politicising the private grief of the mother as a protest against war is employed again in a Vietnam nurse veteran’s response to the First Gulf War. In her poem ‘The Muslim Mother’, Bobbie Trotter takes the images of war beyond American mourning on the home front to include the mourning of ‘the other’. Trotter brings together the iconic Christian image of mother (the Pieta) with ‘the other’ Muslim mother as a way of uniting two opposing cultures in the single image of a mother’s plea against war: ‘The Muslim / mother went / to the grotto / clutching her son’s / picture to her aching breast’. The poem strips away the public and, by implication masculine, rhetoric that divides nations and sends them to war: ‘it wasn’t her faith in Allah / it wasn’t her faith in Jesus / that led her there’. This specific Muslim mother thus becomes the universal image of maternal grief, ‘before the statue / of the Virgin / Mary she fell / prostrate’, through whom Trotter can reject constructions of meaning that sustain the binaries essential to the perpetuation of war. For a mother war can be understood only in terms of personal loss and grief: ‘and begged / mother to / mother / please / end / this / war’ (Van Devanter and Furey (eds)., 1991, p. 180). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.371 | 0.117 |
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".