Bibliographic record
Abstract
Canada's statebuilding efforts in Afghanistan are not well documented. After fourteen years of significant investments in humanitarian causes, there are still questions about the impact of these projects and whether they delivered as promised or fell short. In Canada as Statebuilder? Laura Grant and Benjamin Zyla analyze over one hundred and thirty Canadian-led development projects in Afghanistan to illustrate that Canada has a limited capacity to effectively run humanitarian efforts in unstable, insecure, or inaccessible environments. Canadian or Canadian-sponsored development projects were ambitious and highly productive in terms of outputs in the short term, especially in the areas of security, women and gender, health, and education. However, when their outcomes and overall impact are assessed, the authors argue, Canada's record is less impressive. Their analysis contributes to evidence-based discussions of one of Canada's most important foreign policy activities in recent years. Reflecting on Canada's engagement in Afghanistan, Canada as Statebuilder? asks whether Canadian peacekeeping efforts in the region were ultimately worth the economic and human resources invested.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".