Hughan, Helen oral history interviews
Bibliographic record
Abstract
Helen Hughan is a resident of New Westminster who worked as a secretary for Mercer Shipyards in New Westminster from 1944 to 1949. Her parents immigrated to New Westminster from Scotland in 1929 when she was three years old. She lived on the corner of Mowat St. and 3rd Avenue, and her father worked at Mohawk Lumber Company. She went to F.W. Howie Elementary School and Trapp Tech High School. In 1944, when she was senior in high school, she left school early because there was a demand for secretaries. During that time businesses would go to high schools to look for secretaries. Her major duties as a secretary were recording timesheets from the employees, typing letters, ordering supplies, and interacting with office visitors. Starting out at 18 years old, she believes that working at Mercers opened up to a lot of new things and experiences that she was never exposed to, living a sheltered life as an only child. Hughan reports that she was very happy working at Mercers because her job was challenging and exciting. She married in 1949 and moved to Burnaby, where her children were raised, and moving back to New Westminster in 1971. Prior to her secretary position, in high school she worked at Copp’s Shoe Store on Columbia St. on Saturdays. Throughout the interview she tells stories about the Mercers (father Ed, and sons Gordon, and Art (Arthur)) who she worked with, and speaks enthusiastically about her experience working for them.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.021 | 0.007 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.064 | 0.006 |
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".