The Canadian Armed Forces Primary Reserves and Aid to the Civil Power: Maximizing Service and Minimizing Risk for Canadians
Bibliographic record
Abstract
Abstract: Over the past twenty years, domestic military operations in Canada have seen a dramatic increase in the employment of the Primary Reserve (PRes) alongside the Regular Force. This raises an important question regarding how, in an evolving environment, the PRes can be successfully employed in future aid to the civil power roles? This paper argues that the current organization and terms of service for the PRes are not properly structured and mandated to support any large-scale and sustained aid to the civil power operation - and that this forces Canadians to accept risk when it comes to domestic national security. Theoretically, Canadians have relied for decades on what Sokolsky and Leuprecht have defined as an easy rider approach; where the government contributes just enough resources to ensure that the Canadian public respects and values the military effort. As demands increase, future domestic operations may now have to adapt to a new approach where the criteria for success becomes crisis resolution rather than crisis contribution. By examining the current roles and framework under which the PRes operates, the legal obligations that are currently in force, and the proposal that the PRes assume primary responsibility for domestic response operations, this paper concludes that assigning new roles and responsibilities to the PRes without additional legal obligations will not set the conditions for success should a large scale or lengthy call out be required. (230 words)
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".