Hayes, Godfrey Harry: my naval experiences (March 25, 2005)
Bibliographic record
Abstract
ABSTRACT: Captain Godfrey Hayes Royal Canadian Navy Born in Winnipeg in 1919, Hayes from a young age desired to travel. Lacking the means to travel as a passenger, after high school he enrolled in HMS Conway, a British training vessel in the hopes of earning his passage as a merchant seaman. Upon graduation from Conway, Hayes received a commission in the RNCR, and was to return for naval training when he had completed his merchant apprenticeship with the Silver Line. Serving as a merchant apprentice, Hayes made numerous trips from the US coast, around the horn of Africa, to India and back, but was mobilized by the RNR before he received any naval training. Experienced as a merchant navigator, Hayes was first assigned to an old ferry participating in the Dunkirk evacuation, where he was sunk on his second trip (see the Hal Lawrence Collection for details of this and Hayes' other pre-RCN experiences). Transferred to the RCNVR because of its better pay rates, and was assigned to HMCS Trillium, one of the first ten Canadian built corvettes as navigator. Initially intended for RN service, Trillium was re-commissioned an HMC ship due to RN personnel shortages. Initial impressions of Trillium and RCN crew compared to RN: a small ship, crew informal in bearing and dress, "rough and ready." Left Trillium in Sept. 1942 to get second mate's ticket in Sept. 1942, strictly civilian, still no naval training. Assigned to HMCS Kenogami as XO, essentially as assistant Captain to aid an inexperienced officer who had requested help on convoy duty. Spent almost a year aboard, left in October 1943 to take Command Course in Halifax, his first true naval course. Discusses details of the course, mostly review, no weapons training, good ASW simulator. Notes that when appointed ASDIC control officer aboard Trillium, didn't know what ASDIC was. Discussion of morale aboard Trillium and Kenogami and factors affecting it. Discusses the equipment aboard Trillium and Kenogami, notes that Trillium (RN owned/maintained although an HMC ship) received upgraded equipment (in Texas) that Kenogami later lacked. Talks about living conditions aboard corvettes, seasickness. Discussion of discipline problems, rare, but often dealt with by "mess deck discipline," sometimes at suggestion of officers. After command course, did five months as workup officer at Pictou, explains the details of a "workup," ASW drills, damage control drills etc. Next assigned to command HMCS Guelph, equipped with hedgehog and advanced ASDIC. Embarrassed to note that Guelph failed her workup, although he conducted it himself. Feels that the RCN has been treated harshly by historians, notes the disparity in RN/RCN equipment. Discusses training issues, believes that it varied from ship to ship depending on quality of officers and senior ratings. Argues that weather was the most difficult factor aside from enemy action. Discussion of importance of dedicated A/S hunter groups (as opposed to escort groups), feels that they played as big a role in the victory over the u-boats as aircraft.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.072 | 0.017 |
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".