Bibliographic record
Abstract
„If there is any one area of foreign and defence policy in which Canada did unquestionably make a difference, it is surely in the area of peacekeeping“(Granatstein 1992: 222). Das schrieb der kanadische Militärhistoriker J. L. Granatstein 1992, als er die Ursprünge dessen untersuchte, was er „idea of Canada as peacekeeper par excellence“nannte. Der Ost-West-Konflikt war erst kurze Zeit vorüber, und der Sicherheitsrat hatte seitdem stärker als bisher seine Hauptverantwortung für die Wahrung des Weltfriedens wahrgenommen. Die Zahl der Friedensoperationen der Vereinten Nationen war stark angestiegen. „Zwischen 1945 und 1987 sind dreizehn Friedensoperationen durchgeführt worden; seitdem weitere dreizehn“(SEF 1992: 45), merkte der damalige UNO-Generalsekretär Boutros Boutros-Ghali im Juni 1992 in seiner Agenda für den Frieden an. Kanada, das sich seit Lester B. Pearsons Engagement in der Suez-Krise 1956 an jeder Peacekeeping Operation beteiligt hatte, stellte zu diesem Zeitpunkt mit über 4.000 Soldaten mehr als zehn Prozent des Personals der UNO-Friedenstruppen. Die Armee warnte, dass sie an die Grenze ihrer Belastungsfähigkeit gestoßen sei.
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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 | 0.001 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".