Here today, here tomorrow: A history of Port Alberni
Bibliographic record
Abstract
Audio recording and transcript of Jan Peterson's February 2001 presentation to the Nanaimo Historical Society about the history of Port Alberni. Peterson, an author of multiple books about the Alberni Valley, focuses her talk on the area’s history from 1856, when Adam Grant Horne was the first white person to explore the region, to 1967, when the “twin cities” of Alberni and Port Alberni amalgamated to form a single municipality. Peterson chronicles the region’s long standing involvement with the forestry industry, starting in 1860, when workmen arrived to build the Anderson sawmill. Early settlers, transportation, newspapers, politics, mining, and fishing in the area are also covered. Peterson details several notable event’s in Port Alberni’s history including: the “Great Trek” of 1934, where striking loggers marched from Parksville to Great Central Lake; the June 23, 1946 Vancouver Island earthquake; and the devastating March 27, 1964 tsunami. Peterson discusses the lead up to amalgamation between Alberni and Port Alberni, including the tenure of the first woman mayor on Vancouver Island, Mabel Anderson of Alberni, who opposed the merger. Peterson concludes her talk with a brief update about Port Alberni since amalgamation, focusing on the challenges in the forest industry, including decreased demand and environmental and Indigenous opposition.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.005 |
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".