Promoting Climate Literacy in British Columbia’s Apprenticeship System
Bibliographic record
Abstract
This research paper examines the efforts of the BC Insulators union to promote climate literacy within British Columbia via the a ‘Green Awareness’ course it provides as part of the apprenticeship training for all mechanical insulation trades’ workers in the British Columbia. The two-module course was introduced in 2011 and is taught over the course of the first two years of the four-year program. After conducting a review of the ‘Green Awareness’ course content, the research team performed qualitative interviews with a cohort of 2nd and 4th year apprentices to determine how effective the training had been. These findings indicate the need for further refinements in the content and delivery of the ‘Green Awareness’ course material. The authors conclude that incorporating climate change-related course content into the training process is an important step in fostering climate literacy within the industry and should be encouraged in other trades. However, its degree of impact will be limited unless more sweeping changes are made to the organization and culture of the construction industry itself. This paper was first presented in April 2017 at the International Labour Processes Conference, Sheffield, U.K..
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".