An impact analysis of climate change and adaptation policies on the forestry sector in Quebec. A dynamic macro-micro framework
Bibliographic record
Abstract
Quebec’s forests represent 20% of the Canadian forest and 2% of world forests. They play a major role for habitat preservation, supplying goods and services to the population and hence contributing to the economy of this Canadian province. Climate change (CC) will have an impact on forests through increased droughts, warmer summers and winters or infestations such as the pine beetle (British Columbia and New Jersey). In our study we analyze the economic and distributional impact of CC on the forest industry in Quebec. To achieve this, we simulate two productivity changes in the forestry sector and two potential adaptation programs that could be implemented to help the sector cope with CC direct and indirect effects. Our analysis is performed over a 40 year using a recursive dynamic CGE-micro-simulation framework. We show that the economic impacts on the forest industry are relatively substantial but quite small for the rest of the economy. Moreover, the distributional impacts are present and significant but they are weak (below 0.1%).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".