Pricing the social contract in the British Columbian forest sector
Bibliographic record
Abstract
In this paper, we investigate the impact of various socioeconomic conditions on the value of timber tenures in the province of British Columbia. Two timber tenure models were created, one for short-term timber sale licenses and the other for longer term forest licenses. The short-term model revealed that timber sales that were awarded according to a combination of employment, revenue, and manufacturing criteria yielded $8.63/m 3 less revenue than timber sales awarded based on revenue alone. Similarly, the long-term model indicates that manufacturing and employment conditions significantly reduce the bid on forest licenses. In both instances, we suggest that such conditions distort the use of timber, labour, and capital. Therefore, we conclude that recent forest policy changes in the province that removed several of these conditions greatly improved economic efficiency. Nevertheless, distribution impacts are likely to be important because resource rents have potentially been redistributed away from rural communities to the provincial government.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".