Making Teacher Union History “Public”: The British Columbia (Canada) Teachers’ Union, and Its “Online Museum”
Bibliographic record
Abstract
The British Columbia Teachers’ Federation (BCTF), founded in 1917 with a present membership of 43,000 teachers, is but one of seventeen independent educator unions in provinces and territories across Canada. However, BCTF stands out in relation to the emphasis, and resources, it has placed over past decades in researching, developing and mounting a public record of the history of the organization and its very diverse activities. Now very much webbased, this public history reaches out to a wide audience - in addition to its own members (present and retired), it is also accessible to schooling officials, academics, students, policy researchers, legislators and the public at large. Its portal is located at https://wayback.archive-it.org/16900/20210707181403/ https://bctf.ca/history/. This chapter consists of three main sections. It starts with a history of the union, placing an emphasis on its activities at the community, national and international levels, particularly those related to their collaborative struggles for social justice and solidarity. The second section explores the background to the development of this “public record,” both the historical and contemporary aspects. Finally, I provide a survey and brief description of the various sections of the overall web portal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.023 | 0.008 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".