“Every inch a fighting man:” a new perspective on the military career of a controversial Canadian, Sir Richard Turner
Bibliographic record
Abstract
Lieutenant-General Sir Richard Ernest William Turner served Canada admirably in two wars and played an instrumental role in unifying veterans’ groups in the post-war period. His experience was unique in the Canadian Expeditionary Force; in that, it included senior command in both the combat and administrative aspects of the Canadian war effort. This thesis, based on new primary research and interpretations, revises the prevalent view of Turner. The thesis recasts five key criticisms of Turner and presents a more balanced and informed assessment of Turner. His appointments were not the result of his political affiliation but because of his courage and capability. Rather than an incompetent field commander, Turner developed from a middling combat general to an effective division commander by late 1916. His transfer to England was the result of the need for a proficient field commander to reform the administration. Turner proved to be an excellent administrator, a strong nationalist, and was crucially responsible for improvements in administration and training in England. Finally, the conflict with Sir Arthur Currie, the commander of the Canadian Corps, rather than being motivated by obstructionist jealousy was the outcome of competing institutional imperatives and Currie’s challenging personality.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.049 | 0.021 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".