Weather Report: Images from the Environmental Crisis
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
In the summer of 2004 I began filming scenes for what I thought was going to be a lyrical and quirky look at weather stories and weather lore across Canada. Climate change, or a section I called 'The Politics of Weather', was obviously going to be included but at that moment I thought it would be confined to one section, interspersed with weather proverbs or amusing bon mots from amateur weather observers. Like most people, I had a vague idea of carbon cycles and a dim appreciation of the complexities of Kyoto and emissions reductions. I was wary of apocalyptic scenarios but susceptible to low-level dread at the steadfast accumulation of international weather disasters, not to mention the increasing summer temperatures and smog days in my own city of Toronto. I left lights on, I used my dryer, I drove to work (I love my car). But the climate crisis is an issue that gets under your skin; ask any climate activist. That's because its dimensions are so all-encompassing and the task of addressing the issue is so urgent. It's a geopolitical issue as much as it is a local issue. It connects to the immediate materiality of our individual bodies, as much as it implicates energy regimes, models of development, how we organize cities, suburbs and transportation systems, public utilities and private corporations. It crosses issues of social justice in the global south and the crisis of democracy just about everywhere, and it puts the future on the agenda for all of us, in a way, as Andrew Ross suggests, that has not been seen since the mass socialist movements of the 1930s.
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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it