Bibliographic record
Abstract
In The Lamb and the Tiger, Stanley R. Barrett explores the broad implications of Canada's transformation from a peacekeeping to a war-making nation during the Conservative Party's recent decade in power.Funds were poured into the Canadian Forces, and a newly militarized nation found itself entrenched in conflicts around the globe.For decades, Canada had played a leading role in UN peacekeeping, and when the Cold War ended the prospect of international harmony was infectious.Yet in short order hostilities erupted in the failed states of Rwanda, Somalia, and the Balkans; terrorism -including 9/11 -raised its head; and Iraq and Afghanistan became war zones.In the face of these immense challenges, the UN was dismissed by its opponents as irrelevant.Structured around an anti-war perspective, The Lamb and the Tiger critically examines the ageless genetic and more recent cultural explanations of war and includes a close look at the impact of war and right-wing politics on women and Indigenous peoples.The Lamb and the Tiger encourages Canadians to think about what kind of military and what kind of country they really want.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.562 | 0.293 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".