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
The development of climate change action plans and strategies is usually done via the policy cycle during the first half of a government’s term. This short-term political process is at odds with the longer-term climate change issue that requires a consistent and sustained effort. Consequently, this often leads to conflicting and ever changing climate plans and strategies that often do not fully move to implementation. Several key strategic questions need to be considered at the policy agenda setting stage. Examples of these questions include: the real impetus for developing the plan, political will to take on policy development at a particular time, the degree of intention to actually implement it, and depth of target vs. costs to the economy. The developmental stage of climate plans in Canada has historically involved five key components (with many variations): 1) background policy and scientific work; 2) consultation process; 3) economic/policy analysis and target setting; 4) building political support for a greenhouse gas target and policy package to meet the target; and 5) refinement and final political approval. Businesses are also responding by developing climate change strategies to either hedge their risk of being regulated, hedge their risk related to severe weather events, and/or to take advantage of climate business opportunities.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.009 |
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