Tradable Disturbance Permits for Old-growth Forest Conservation: Experimental Evaluation of Implementation Options
Bibliographic record
Abstract
Experiments are used to examine the performance of tradable disturbance permits (TDPs) for meeting old-growth targets on public forest land. TDPs are an allowance-based cap-and-trade system for rights to disturb forest for development of timber and energy resources. Treatments compare three market institutions for permit allocation: second-price sealed-bid (SPSB) auction and grandfathering permits to the forest sector with a call or double-auction resale market. The large size of the forest sector creates opportunities for strategic interactions. Additional treatments include banking, uncertainty from forest fires, and adaptive caps. Grandfathering to the forest sector with a double-auction resale market outperformed the SPSB auction, alleviating concerns about market power. Without fire, banking had a negative effect on energy firms and total market surplus. Adaptive caps increased permits during low-fire seasons with a positive effect on surplus to energy firms and total market surplus.
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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 | 0.003 | 0.007 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".