Bibliographic record
Abstract
On August 22, the Canadian forces in Afghanistan suffered a major setback. Just outside their fortified camp in the centre of Kandahar, a suicide bomber targeted a small supply convoy returning from a Provincial Reconstruction Team base. The resultant blast killed one soldier, injured three others and left two armoured vehicles blazing fiercely. As the ammunition stored in the Canadian vehicles continued to cook off in the aftermath of the attack, the rapid response team from Camp Nathan Smith deployed to secure the ambush site. It was several hours later that Canadian soldiers fired on an approaching motorcycle, seriously wounding the 17-year-old driver and killing his 10-year-old passenger. The news that our soldiers had shot and killed an Afghan child – albeit under the belief that they were acting in self-defence – sent shockwaves across Canada. Over and over again we had been told that our troops were deployed to Afghanistan to protect the weak and the vulnerable and now that logic had been stood on its head. Once again Canadians began asking exactly what we hope to achieve in Kandahar, and whether or not our soldiers sacrifice can be justified in the long run.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.058 | 0.034 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".