EXECUTIVE SUMMARY................................................................................................................. 3
Bibliographic record
Abstract
Later this year the world will come together in Copenhagen in a desperate attempt to finalize a new global climate agreement. As recent science makes clear, the stakes could not be higher. Climate change poses a grave threat to us all, and to the world’s most vulnerable people in particular. And though time is running out, we have thus far failed to rise to the challenge. Tackling the climate crisis will require an unprecedented and mammoth effort – both in the scale of the response that the science tells us is necessary, and in the level of international political cooperation that will be required. Frankly, the situation demands an emergency global mobilization, one that must come even while billions of people in developing countries are still struggling to escape poverty. In Canada, climate change policy has been dominated by short-term approaches that have
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.
How this classification was reachedexpand
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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.014 | 0.015 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.018 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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; both teacher heads agree on what is shown here.
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".