Bibliographic record
Abstract
The forest industry is a very important part of the economy of British Columbia. A peculiarity of B.C. is the large percentage of forest land under government control. This situation creates difficulties when trying to attract private investment in forest management. Currently, tenure holders have no equity in future timber and only have rights to harvest timber, therefore, there are no voluntary incentives to invest and to manage the land well. The sale of Crown land to private interests on a large scale is likely not acceptable to the people of B.C. and so an alternative must be found. As the structure of the commercial forest land in B.C. undergoes the transition from old-growth to second-growth, the relationship between the Crown and tenure holder begins to resemble that of landlord and tenant farmer in agriculture. A sharecropping contract may have attributes that are desirable for managing forests. Several examples of silvicultural regimes in both the Interior and Coastal regions of B.C. are used to demonstrate how share contracts can be applied to B.C. forestry. The flexibility of ' share contracts allows the risks of forest management to be shared by both parties and they also provide the incentives to perform that the current command and control approaches do not. The calculations in the examples show positive net present values when discounted at 4% on the Coast and 3.5% in the Interior in real terms. Regimes that do not have positive NPVs with these discount rates may still be viable if non-market benefits are included and the equity shares of each party adjusted accordingly. In this way, government can internalize the benefit to the company of producing these goods. Share contracts also allow the Crown to accept logs as payment for use of the land and those logs could be used to supply provincial log markets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".