Oral History Interview with Willie Sander, May 22, 2002
Bibliographic record
Abstract
The National Museum of the Pacific War presents an oral interview with Willie Sander. Sander was born in Brenham, Texas on 18 August 1916. After graduating from high school in 1933, he worked as the manager for the A&P Grocery chain. In 1942, he joined the Navy and received pilot training on PBYs. After being commissioned in June, he was sent to Kaneohe Naval Air Station where he received advanced training. Soon after the invasion of Tarawa, he delivered a new plane there and returned to Hawaii with one that had been badly damaged. He comments on the death and destruction he saw. In March 1944 he flew to Fiji where he joined Patrol Squadron 14 (VP-14), which was attached to a seaplane tender. They flew night patrols and rescue missions. In early 1945 he returned to the United States and picked up new PBM Mariners. Sander took the planes to San Diego where JATO equipment was installed. After receiving training in the use of the equipment they flew to Luzon. He recounts a number of missions, including one for which his crew was credited with sinking five Japanese ships and he was awarded the Distinguished Flying Cross. On 15 September 1945, Sander went to Shanghai where he boarded the USS Saratoga (CV-3) bound for San Francisco. He was discharged soon after his arrival.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.015 |
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".