“When Blue is Green”: Towards a history of workers as environmentalists in British Columbia and beyond
Bibliographic record
Abstract
This dissertation examines the history of working-class environmentalism. It investigates the relationship between work and the environment and between workers and environmentalists. It presents five case studies that focus on the relationship between workers and the environment in British Columbia from the 1930s to the present, with particular emphasis on the forestry industry. Each case study examines how the interests of workers both intersect and conflict with the interests of environmentalists and how this intersection of interests presented itself throughout the twentieth and twenty-first centuries. Additionally, this dissertation examines how the working class has historically been constructed as the adversary of nature or wilderness and aims to explore how the working class, resource workers in particular, have come to symbolize that adversarial relationship. As well, it hopes to answer more epistemological questions about why working class environmentalism has not entered our lexicon and how lacking a sense of the working-class environmentalist serves to shape a discourse in which the history of worker environmentalism has been largely passed over. This study also explores how the collective memory of environmentalism has been constructed to exclude notions of class, and thus how environmentalism and the working class have been constructed as mutually exclusive categories. While this dissertation explores the exclusion of working class environmentalism it also attempts to write the worker-environmentalist back into history and show how teaching working class and labour history can help remedy this exclusion.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.040 | 0.022 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".