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Record W6955569706 · doi:10.58066/c6py-3079

Scotten, Kenneth R.: my naval experiences (November 15, 2006)

2006· other· en· W6955569706 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2006
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCrewRefugeeGovernment (linguistics)ClothingOn boardWorld War II

Abstract

fetched live from OpenAlex

ABSTRACT: Captain Kenneth Scotten Captain Scotten interview.mp3 (0:00) High school education before joining military. University education after joined navy. Initially wanted to fly. Had not seen salt water until he joined the Navy, and decided that was the way to go. (2:30) Brief description of diplomatic mission to USSR. Preserver was one of the first ships there since 1936. Boat people were somewhat common in the 80's though a rescue operation was not expected. (4:20) Crew offered own clothes and toys to the Boat people. The government was very supportive of the operation by way of diplomatic assistance. Scotten communicated with Ambassador in Manila all the time. Tripartite group formed in Ottawa created to deal with problem. (7:40) Ship had Doctor and Dentist, though the Doctor was away during the arrival of the boat people. In the meantime Senior Medical Assistant and his assistant dealt with the sick refugees. The doctor returned with more supplies later on. (13:19) Pros and cons of the Preserver for this operation; facilities were overwhelmed yet other merchant ships couldn't have done this. Preserver had space, medical expertise, and numbers of people capable of providing care. (17:24) Explains how ship was divided up. (20:34) Explains burial at sea, which was the best option for dealing with refugee casualties. (24:45) Crew morale was huge. The crew gave toys, sang songs etc. 3 teams were formed to keep watch over refugees. Preserver was the only ship with women onboard. (28:27) Concerned with not being able to land refugees at next port, which is normally the case with rescue missions, because refugees are a chronic problem in the Philippines. Description of different communication systems. (35:59) Tropical storms Nathan and Ophelia cause problems. Ophelia causes him to go 8 hours off course and anchor for one night outside of the port in Manila. (38:30) Refugee morale is a mix of being grateful for life and apprehension. The Filipino government decides it, for the time being, will only accept the severely sick and their family members. (43:55) Description of the difficult docking process. The eventual Canada-Philippine compromise is that the Philippines will accept the Vietnamese boat people as long as Canada takes responsibly for the legitimate refugees and the repatriation of the others. Tearful departure with refugees. (50:57) Successful mission because of the lives saved. It's a good news story about the military that people like to see. Involved risky decisions. (56:07) Brief description of contact with people after 1990. There was a 1, 5, and 10 year reunion. Refugees consider the Preserver their 'mother' because she gave them a second life. (59:50) Received Meritorious Service Cross and was honoured, though he felt he received it on behalf of the entire crew. Mention of his son being on ship. (1:01:24) Concluding comments. (1:04:42)

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.002
Scholarly communication0.0050.005
Open science0.0020.006
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0780.016

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.

Opus teacher head0.021
GPT teacher head0.269
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2006
Admission routes1
Has abstractyes

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