Shifting Mandates and Climate Change Policy Capacity: The Forestry Case
Bibliographic record
Abstract
The original hypothesis is that forests will be a policy subsector in which the challenges of climate change adaptation lead to broader policy mandates but that the declining role of the industry in the Canadian economy will cause departmental resources to be stable or decreasing. The result will be ineffective policy capacity, leading to adaptation policies that are poorly designed, incomplete or missing altogether. This paper provides some evidence to support this hypothesis, though the situation is complicated by the dominant role played by the provinces in both ownership and jurisdiction. While the leading federal department, Natural Resources Canada, has shed other mandates to focus on climate change, provincial agencies are already caught between the added costs of addressing climate change impacts, notably wildfire, and the need to plan for and implement long term adaptive policies with stable or declining resources. Much will depend on coordination between First Nations, the provinces and the federal government in a policy subsector with a history of conflict between the different orders of government.
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 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".