Interview with Major (Ret’d) Mark Labrecque: Canadian Maritime Patrol
Bibliographic record
Abstract
Narrator: Major (Ret’d) Mark Labrecque Interviewer: Conor Standen Interview Date and Location 11 March, 2024, Zoom. Synopsis: The Interview with Major Mark Labrecque begins with a discussion on his life before entering the RCAF, his reasoning for joining the RCAF and his education path to become an air navigator. Major Labrecque discusses the responsibilities of the air navigator during a mission, the responsibilities of the Maritime Patrol during the Cold War and his experience with anti-submarine warfare and other surveillance missions. Labrcque continues on to detail how tracking submarines worked using sonobuoys, patrolling fishing vessels, and his experience during the transition from the CP-107 Argus to the CP-140 Aurora aircraft. Finally, the interview discusses Labrecque’s reflection on his career after his time as an air navigator for the maritime patrol. 0:00 - 0:37 - Introduction 0:37 - 2:17 - Life before the armed forces 2:17 - 3:13 - Reasoning for joining the armed forces 3:13 - 4:22 - Goals when signing up for the RCAF and education path when joining the RCAF 4:22 - 5:30 - Knowledge of the Maritime Patrol and aviation prior to enlistment 5:30 - 6:42 - Route to becoming an air navigator and position maneuverability once enlisted 6:42 - 7:57 - Skills necessary for becoming an air navigator 7:57 - 10:29 - Duties and responsibilities of a Maritime Patrol navigator 10:29 - 11:55 - Years working as an air navigator 11:55 - 15:39 - Duties the Maritime Patrol was tasked with during the Cold War 15:39 - 17:59 - Experience with the explosion of Mount Saint Helens 17:59 - 24:56 - Typical day for the Maritime patrol, both flying and non flying days 24:56 - 27:20 - Methods of searching for submarines and frequency of locating submarines 27:20 - 29:42 - Length of tracking a specific submarine and information gathered from tracking 29:42 - 33:14 - flight where the tracking device was dropped directly on top on a submarine 33:14 - 40:19 - Sonobuoys and how they functioned in tracking submarines 40:19 - 42:32 - Non submarine surveillance missions including fishery, search and rescue and northern patrols 42:32 - 43:35 - Anti submarine patrols and when they would occur in relation to other duties 43:35 - 44:37 - The Ocean Institute’s surveillance station, Ocean Station Papa, and providing them with aid 44:37 - 45:17 - Continuation of non submarine surveillance mission, what they were and when they were conducted 45:17 - 47:30 - Pacific Soviet submarine Christmas patrols 47:30 - 53:40 - Patrolling fishing vessels 53:40 - 56:25 - Soviet spy and information gathering vessels 56:25 - 1:05:31 - Transition from the CP-107 Argus to the CP-140 Aurora aircraft 1:05:31 - 1:09:03 - Proudest moments as an air navigator, applying training to reality 1:09:03 - 1:14:21 - Career discussion after Maritime Patrol navigator 1:14:21 - 1:15:11 - Conclusion
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.058 | 0.008 |
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".