British cavalry on the Western Front 1916-1918
Bibliographic record
Abstract
This thesis examines the activities and effectiveness of the British, Indian and Canadian cavalry which formed part of the British Expeditionary Force in France and Flanders (The ‘Western Front’) during the First World War. The study concentrates on the period from January 1916 to November 1918, focusing on four major Allied offensive battles; The Somme, July-November 1916 Arras, April 1917 Cambrai, November-December 1917 Amiens and the ‘100 Days’, August-November 1918 Other episodes of cavalry fighting associated with these offensives are also considered. It is argued in this study that the contribution of cavalry to the fighting on the Western Front has been consistently underestimated by historians, a trend which began with the Official History of the conflict and continues in even the most modern scholarship. The arm has been characterised as vulnerable to modern weapons, out of date, of little use in combat, and an unnecessary burden on scarce resources. Through analysis of the performance of mounted units in these battles, using data principally obtained from the unit War Diaries, as well as other primary sources, it is argued that cavalry were both much more heavily involved in fighting on the Western Front, and more effective, than has previously been acknowledged. The problems which constrained the performance of the cavalry are also exa mined. These included the limited understanding of their potential among senior officers, as well as command and control problems at lower levels. Issues concerning tactics, equipment, and interaction with other arms, (in particular tanks) are also examined. The evolution of the cavalry arm is also considered in the context of the evolution of the B.E.F. as a whole, and its part in the changing face of the conflict is examined, both as an agent of change, and as a beneficiary of wider developments in how the war was fought.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".