Wild Smoke: Managing Forest Pollution in Northern British Columbia since 1950
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Almost every year, ash drifts from forest fires in north-western Canada into northern Europe, altering forecasts on both continents, settling in Antarctic ice and turning the skies over the world’s major cities an apocalyptic orange. As smoke drifts from the forests into nearby communities and distant urban centres, it becomes the medium through which most people experience forest fire, leaving traces on memories and bodies. Although wildfires and their associated plumes are getting worse, people have a long and dynamic relationship with forest fire smoke which can be understood through the lens of air pollution and forestry history. Using British Columbia, Canada as a case study, I argue that the difficulty of separating wildfire smoke from other types of air pollution has worked to the advantage of land managers interested in supporting the forestry industry, with negative impacts for northern communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it