Bibliographic record
Abstract
The British Commonwealth air training plan was created to address the critical shortage of trained flyers that existed at the outbreak of World War II. As the expansion of existing training facilities in areas likely to be subject to enemy attack was unlikely to be satisfactory, an agreement was reached between Great Britain, Canada, Australia and New Zealand to provide training facilities in Canada. Initial requirements were for 58 airfields, one to be complete by May 1940, 37 by the end of 1941 and the remaining 20 by April 1942. The extent of this civil engineering challenge is highlighted by the fact that, in 1939, the Royal Canadian Air Force possessed only five airfields. However, not only were the original targets achieved, they were surpassed in both scope and time. On completion, 88 ‘main’ airfields were in use; as most of these airfields required at least one ‘satellite’ field with many of the facilities of the main fields, the grand total was 176 airfields. In the words of President Roosevelt, Canada had become ‘the aerodrome of democracy’. As airfields were constructed in every province of Canada, planning and logistical problems were immense. Standardisation of design for airfield layout, prefabrication of components for hangars and other airfield structures, a centralised management organisation and the application of what, today, we would describe as modern construction project management techniques all helped Canada's civil engineers to successfully complete this Herculean task.
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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 | 0.014 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".