Economic analysis of a softwood lumber quota regime and a policy to subsidize biomass generation of electricity.
Bibliographic record
Abstract
<title>Abstract</title> The REPA spatial price equilibrium model developed in Chapter 4 is used to investigate the regional welfare impacts of a quota on exports of Canadian softwood lumber to the U.S. In the model, Canada is divided into seven regions and the U.S. into five regions, with the rest of the world constituting a 13th region; the model is calibrated to the bilateral trade flows that existed in 2016 when there was free trade in lumber. Various quota levels are examined in terms of their impact on producers and consumers in both countries. Canadian producers are found to be better off with a hard quota compared with free trade, although the quota leads to a reduction in market share while driving a wedge between Canadian and U.S. prices, both of which are aggravated with harder quotas. Overall, the loss of export sales to the U.S. is not recouped with sales to the rest of the world. The REPA model is also used to examine the impact of EU demand for wood pellets to generate electricity. Results indicate that pellet prices will approximately double.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".