Nature's Past Episode 047: Pollution Probe and the History of Environmental Activism in Ontario
Bibliographic record
Abstract
Environmental activism has a long history in Canada. Like others around the world, in the late 1960s and early 1970s, Canadians became involved in a number of environmental non-governmental organizations. Picking up on a prevailing spirit of protest during the era, several environmental problems surfaced as popular political issues: air pollution, water pollution, solid waste disposal, among many others. \n \nOut of this came one of the first ENGOs in Canadian history, Pollution Probe. Born at the University of Toronto in 1969, the nascent group focused its efforts on new concerns regarding air pollution in Canada. It would go on to become one of the most influential environmental groups in Ontario and even shape a national environmental movement in Canada. \n \nScholarly research on the history of the environmental movement in Canada is limited. A couple of years ago, we published two episodes of Nature’s Past on the history of the Canadian environmental movement. \n \nNow there are a handful of new books on the topic, including the recently-published The First Green Wave: Pollution Probe and the Origins of Environmental Activism in Ontario. On this episode of the podcast, author Ryan O’Connor joins us to discuss Pollution Probe and the early years of environmental activism in Canada. \n \nPlease be sure to take a moment to review this podcast on our iTunes page.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.040 | 0.011 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".