Estimating impacts of resource management policies in the Foothills Model Forest
Bibliographic record
Abstract
This study examines the economic impact of policy changes in a forested region of the province of Alberta known as the Foothills Model Forest (FMF). The effects of policy changes in various sectors are analyzed in terms of all sectors of the regional economy with particular emphasis on the forestry sector. Unlike most analyses of regional policies, this study uses a computable general equilibrium (CGE) framework rather than a fixed-price framework to analyze economy-wide impacts of land use or forest policy changes. The application of this technique on a regional scale is rare in the scientific literature. Model results indicate that a decrease in forestry output somewhat offsets the positive economic impact generated by increased visitor activity. Failure to consider these trade-off impacts in the analysis will result in erroneous conclusions. The outcomes from three timely policy scenarios are examined in this paper. The results from the CGE framework suggest that policy makers face a greater degree of complexity than in current economic impact frameworks.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".