The 46th Reconnaissance Squadron: Arctic Exploration and Questions of Sovereignty in the Early Cold War
Bibliographic record
Abstract
In the early Cold War, the Arctic emerged as a key region in American military planning. In 1946, the newly formed US Strategic Air Command deployed the 46th Reconnaissance Squadron to Alaska to improve navigational and cold weather flying capabilities. Major projects assigned to the squadron included the search for undiscovered land masses in the polar region, should any exist, and the establishment of an air route between Ladd Airfield, Alaska and the US base at Meeks Field, Iceland, which involved overflights of the Canadian Arctic Archipelago. This paper will explore the core projects within this initiative and how the US sought to manage Canadian sovereignty interests as it pursued its strategic objectives against the Soviet Union. Au début de la Guerre froide, l’Arctique est devenu une région clé de la planification militaire américaine. En 1946, le nouveau Strategic Air Command des États-Unis a déployé le 46e escadron de reconnaissance en Alaska pour améliorer les capacités de navigation et de vol par temps froid. Les principaux projets assignés à l’escadron comprenaient la recherche de masses terrestres non découvertes dans la région polaire, s’il en existait, et l’établissement d’une route aérienne entre l’aérodrome de Ladd, en Alaska, et la base américaine de Meeks Field, en Islande, qui supposait des survols de l’Archipel arctique canadien. Cet article étudie les principaux projets de cette initiative et les efforts déployés par les États-Unis pour gérer les intérêts de souveraineté du Canada alors qu’ils poursuivaient leurs objectifs stratégiques contre l’Union soviétique.
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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 | 0.002 | 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 | 0.019 | 0.031 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".