Bibliographic record
Abstract
The capstone document Land Operations 2021: Adaptive Dispersed Operations presents the Canadian Army's doctrinal vision for its forces to be relevant and decisive in the near future. This monograph situates itself as a contribution to the development of the optimal doctrinal configuration of the Canadian Light Infantry Battalions of 2021. It reviews key Canadian Department of National Defense documents and establishes basic historical facts surrounding the organization of light infantry forces, primarily through the writings of John English and Basil Liddell Hart. It then explores various theories of allied organizations built for similar environmental settings and for various operational contexts. The structures of the United States Army, United States Marine Corps and Australian Defense Forces light infantry companies are respectively explored and then compared to the current Canadian infantry companies. The case studies are deliberately used to represent parts of the envisioned 2021 problem and this paper posits that the best structure for the light infantry forces to meet the Adaptive Dispersed Operations' requirements is at the confluence of each set of capabilities. Thus, the proposed structure maximizes its capability to disperse and aggregate through an increased number of basic maneuver elements, such as the basic Canadian 4-man assault group. It also provides for enhanced air "'deployability"' through a pure light organization with the option to add formed light vehicles sub-units to provide protected mobility without being tied to a specific platform. The structure provides for enhanced lethality through an increased number of light support weapons. Its inherent modularity ensures its ability to fall on various weapons systems and mobility platforms while maintaining small unit integrity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".