Bibliographic record
Abstract
In the timeless tradition of international politics, “Send a gunboat” is a common response to crisis. The June 25th, 1950 invasion of South Korea from the North evoked a similar response. In a relatively short time, the ill-equipped, shrinking, post-war Royal Canadian Navy (RCN) deployed a force of three destroyers to Korea for operations under the auspices of the United Nations; well in advance of any army or Royal Canadian Air Force commitments. Despite the prevailing economic and domestic political climate, the anaemic RCN managed to maintain three destroyers on station in Korea and meet the new North Atlantic Treaty Organisation commitments, as well as begin an unprecedented period of “peacetime” expansion. This paper reviews these events and will, in particular, look at: how the RCN involvement in Korea came about and the major political factors affecting this commitment; the extent of the RCN involvement in Korea; the effect of the Korean involvement on Canadian participation in the fledgling NATO alliance; and how the RCN expansion came about and what influence the NATO alliance and Korea had on its expansion. Although the continuous deployment of three destroyers to the Korean theatre critically stretched the RCN’s resources, the commitment was met and the RCN managed to expand and develop an entirely new, and enviable, class of warship to meet its unique needs. In the end result, the RCN rose to the challenge of its motto of “Ready Aye Ready” and went one better than merely sending a gunboat. They sent three.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.014 | 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".