Bibliographic record
Abstract
"An Equal Burden forms the first scholarly study of the Army Medical Services in the First World War to focus on the roles and experiences of the men of the ranks of the Royal Army Medical Corps (RAMC). These men, through their work as stretcher bearers and orderlies, provided a range of labour, both physical and emotional, in aid of the sick and wounded. They were not professional medical caregivers, yet were called upon to provide medical care, however rudimentary; they served in uniform, under military discipline, yet were forbidden, as non-combatants, from carrying weapons. Their service as men in wartime, was thus unique. Structured both chronologically and thematically, this study examines both the work that RAMC rankers undertook and its importance to the running of the chain of medical evacuation. It additionally explores the gendered status of these men within the medical, military and cultural hierarchies of a society engaged in total war, locating their service within the context of that of doctors, female nurses and combatant servicemen. Through close readings of official documents, personal papers, and cultural representations, both verbal and visual, it argues that the ranks of the RAMC formed a space in which non-commissioned servicemen, through their many roles, defined and redefined medical caregiving as men’s work in wartime."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.056 | 0.014 |
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".