Lifesavers and body snatchers medical care and the struggle for survival in the Great War
Bibliographic record
Abstract
"The perception of medical care on the Great War battlefield recalls scenes from the American Civil War fifty years earlier: blood-soaked surgeons hacking off limbs with grim determination as broken men crawled into their dirty operating rooms. This couldn't be more wrong. Medical care in almost all armies, and especially in the Canadian medical services, was sophisticated and constantly evolving, with vastly more wounded soldiers saved than lost. After the war, the hard lessons learned by civilian doctors who were temporarily in military uniform were brought back to Canada. A new Department of Health created guidelines in the aftermath of the 1918-19 Spanish flu pandemic, which had killed 50,000 Canadians and millions around the world. In a grim irony, the fight to save soldiers' lives and improve civilian health was furthered by the most destructive war up to that point in human history. But medical advances were not the only thing brought back from Europe: Life Savers and Body Snatchers exposes the shocking story of the exploitation of human body parts during the Great War. Tim Cook has spent over a decade investigating the hidden history of Canadian medical doctors harvesting the body parts of slain Canadian soldiers and transporting their brains, lungs, bones, and other tissue or bones to the Royal College of Surgeons (RCS) in London. At least 1,200 individual Canadian body parts were removed from dead soldiers and sent to London, where they were stored, treated, and some put on display in exhibition galleries at the RCS. After being exhibited there, the body parts were displayed several times in both Montreal and Hamilton in the early 1920s. Life Savers and Body Snatchers will be the definitive medical history of the Canadian forces in the Great War, and a broader look into the medical advances that came from the carnage."--
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".