Sorry we're late, eh? Paradigms for Canadian mobilization.
Bibliographic record
Abstract
The fundamental tensions for the Canadian Army are to retain forces of sufficient mass and capability to be effective in operations, to deploy and sustain these at intercontinental distances, and to have these forces ready in time to effect change. This tension is described in modern readiness theories and exemplified in the Canadian experience in the Korean War. Based on flawed assumptions after the Second World War, Canada was embarrassingly unready for conflict and deployed forces to Korea only after pressure from allies and two spectacular operational reversals on the peninsula. Since the end of the Cold War, the doctrine for mobilization retains some of the same flawed assumptions. This study examines Canada's preparation for the Korean War, compared against Cold War readiness theories, current doctrine, and futures studies to make recommendations for updates to Canadian Forces Joint Doctrine for Mobilization from an Army perspective. The conclusions recommend parameters for a complementary Force Generating Concept study. Ultimately, this study is relevant for any national army which can imagine a need to be ready for a future expansion.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.027 | 0.020 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".