Bibliographic record
Abstract
In coming months, Canadians will decide their policy towards Afghanistan. That decision will be political. One hopes it also will be rational, involving an assessment of our national interests, and the balance between gain and loss. Nor should our decision be determined by the weight of past sacrifices or policy. If we have been doing the wrong thing at a cost, why repeat the error and the sacrifice? The past, however, does show the need to treat the issue seriously, more than we did before we first decided to enter Kandahar in 2003, or to stay on there in 2006. There were good reasons to question the idea of going to Kandahar, when first we went there, and so also today. But many of the prevailing arguments on the topic are inadequate. The icky-pooh school of the left assails our involvement as “Stephen Harper’s war”, or “George Bush’s war”, when all political parties and virtually all Canadians advocated our involvement in Afghanistan during 2001, few opposed or even questioned our subsequent move to Kandahar, while both Barack Obama and The Guardian support staying the course today. Perhaps we should call it “The Guardian’s war”? The Don Cherry school of Canadian public policy insists that we should support the war just like we back the team, without asking whether we are in the right series. The political parties castigate each other as cowards or warmongers,
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.062 | 0.019 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.016 | 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".