;If I had thousands of Victoria Crosses;: Stretcher Bearer Training in the Canadian Army Medical Corps in the First World War
Bibliographic record
Abstract
In the First World War, the Canadian Army Medical Corps (CAMC) went from a small force of twenty Permanent Force officers to staffing a professional and exceptionally dedicated Medical Corps.Canadian doctors, nurses, orderlies, dentists, optometrists, ambulance drivers, x-ray technicians, and others are lauded for their achievements during one of the bloodiest conflicts in human history.Yet very little is written about the stretcher bearer, often the first man to come upon a wounded soldier in the field.These bearers could be the difference between life and death for the fighting force.This thesis examines how bearers were trained and how their training evolved as the war went on.It argues that these men were instrumental in saving lives at first contact with the wounded, and that, as the war went on, their training expanded to better lifesaving techniques.iii Table of Contents iv List of Photographs vAbbreviations viii even if they were a distinct territorial force.This means that the medical arm of the CEF used British training material and only during the war did they, as other territorial forces did, develop their own style and techniques for treatment of patients by trial and error.3 This is also true when it comes to the CEF's organization.4 By examining training material, soldier's diaries, available academic and archival material, this thesis will focus on two main subjects.The first will be pre-war training undertaken by stretcher bearers, which will be examined by looking at training material, diaries, and archival sources.In the first chapter, I consult surviving training manuals that imparted medical knowledge and contain drill exercises that were used to ready these unarmed soldiers to undertake their important role.The second chapter will delve into battle lessons.This will be done by looking at the survival rate of soldiers turned patients, triage and first steps taken by the stretcher bearers when finding a wounded comrade, and medical developments that were then implemented and taught to stretcher bearers by medical officers.Both chapters will incorporate first-hand accounts from stretcher bearers themselves, as well as their patients and the Medical Officers who taught the stretcher bearers their lifesaving techniques.The main subject is the Canadian stretcher-bearer but because of availability of material, it will be supplemented by information on British and other Dominion forces.The goals of this thesis are three fold.The first is to review the selection process of stretcher bearers and their pre-war training; the second goal is to show that, as the war dragged on, the training received by bearers evolved and 3 L. Bruce Robertson, "Further Observations on the Results of Blood Transfusion in War Surgery,"
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".