Second Prize: Contractors in Kandahar, eh? Canada’s ‘Real’ Commitment to Afghanistan
Bibliographic record
Abstract
This paper will examine the Canadian Force's growing utilization of private military firms on international operations, focusing primarily on the use of the Canadian Forces Contractor Augmentation Program (CANCAP) in Kabul from 2003-2005 and their current use at Kandahar Air Field (KAF). This paper will demonstrate that personnel reductions in the 1990's and a persistently high operational tempo have forced the Canadian Forces to increasingly rely on commercial support options on operations abroad. It is argued here that while the Canadian Forces' use of privately provided logistics functions has remained modest to date, the Canadian military will continue to accelerate the rate at which it relies on non-military support options. In particular, this paper will demonstrate that the personnel demands of the current mission in Afghanistan will require Canada to continue, if not increase, its reliance on private support options at KAF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".