Bibliographic record
Abstract
The Newfoundland Airport, in what became Gander, Newfoundland and Labrador, was an area of both conflict and logistics during the Second World War. The airbase served roles as both a stopping point for aircraft to be ferried from production facilities in North America to the war theatre overseas, for convoy escorts and U-boat hunting, as well as mundane deliveries of people and equipment from Canada and the United States. During the war, the airbase was very active, with thousands of aircraft using the runways, and there were aircraft lost, whichremain on the landscape around Gander. For those serving at the Newfoundland Airport, the war may have been ever-present, but at the same time distant; there was no active battle at the airbase, but there were casualties of war. Those who died were filling combat and logistical roles, and post-war rebuilding efforts. Accidents occurred due to mechanical malfunctions, the weather, and human error. Using historical records and archaeological site inventories, this paper will examine the role of this non-combatant space and advocate that the material cultureof aircraft crash sites be conceptualized within the larger context of aviation infrastructure. The result will expand our understanding of the impact and tragedy of war for the airbase at Gander, and for Newfoundland and Labrador.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".