Leaders in Conflict: Diefenbaker, Kennedy, and Canadaâs Response to the Cuban Missile Crisis
Bibliographic record
Abstract
While the Cuban Missile Crisis has received a tremendous amount of attention from American scholars, in Canada the historiography concerning the Crisis is quite limited, with few monographs devoted to it. Typically the Crisis might receive a few pages of attention, perhaps a chapter in a book concerned with other topics. This historiographical “blind spot” has allowed misconceptions concerning Canada’s diplomatic and military participation in the Crisis to persist in this country’s collective memory of the Crisis, which is a disservice not only to Canada’s national heritage, but to the thousands of men and women who strove to prepare Canada for the possibility of thermonuclear war against the Soviet Union and its allies.\nMaking use of the most recent document declassifications and all available secondary scholarship, this thesis examines the true nature of Canada’s oft-overlooked contributions to continental security, and the increasingly hostile personal relationship between President John F. Kennedy and Prime Minister John Diefenbaker. Particular attention is paid to how understanding of these events has evolved with the release of once-classified materials over the nearly five decades since the Crisis.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".