Army Supplies in the Forward Area and the Tumpline System: A First World War Canadian Logistical Innovation
Bibliographic record
Abstract
Editorâs Note: In British Logistics on the Western Front, 1914â1919 (Praeger, 1998), Ian M. Brown documents the problems of maintaining an army in the field; throughout that war, supply lines were strained to get food, equipment and ammunition forward. Early problems of adequate supplies were replaced by an inability to get the items from depots to where they were required. Some of these latter problems were blamed on âestablishmentsâ and other force-structure problems caused by stripping logistical-support units to meet the manpower needs of the fighting units. The decision to dramatically reduce the size of the BEF divisions in France helped reduced pressures. By stripping a battalion out of each brigade, and using the men freed as replacements, the BEF maintained its paper strength in divisions (though, in fact, the strength went considerably down) and, more importantly, also reduced its overall logistical requirements. But, as Brown writes: The Canadian Corps successfully resisted this âdownsizingâ as its commander opposed the reduction vehemently. In fact, he managed to increase the effective size and strength of his divisions by using the manpower from the two [sic] Canadian divisions forming in Britain. This gave Haig a single very strong corpsâfour overstrength divisions amounting to some one hundred thousand men (forty-eight thousand infantry)âbut it also gave his administration a supply problem, since the standard divisional pack could not supply a Canadian division. In spite of this trouble, it did not appear to cause great difficulty on the lines of communication. Indeed, it gets no mention in either the QMGâs or AGâs diaries.... (pp.165-166)\nBuried in this passage lay two secrets. The four-battalion brigades perhaps (too simply?) explain the use of the Canadian Corps as Haigâs âshock troops.â But as Brown notes, how the Canadians maintained these larger formations is not clear from British sources (p. 177). The answer to this secret must be sought elswhere. One answer in F.R. Phelanâs âtumpline.â
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".