Bibliographic record
Abstract
A group of independent small businesses in the area of Quesnel, British Columbia—including logging contractors, sawmillers, and forest industry members—formed the Quesnel Hardwood Co-operative in 1999. The Co-operative's objectives were to utilize the region's neglected birch hardwood resource to create and sustain jobs in the forest industry, provide work for under-employed local people, and help stabilize the area's economy.On behalf of its members, the Quesnel Hardwood Co-operative integrated wood supply and sales to create a larger forest enterprise, thereby making members' products more competitive in the marketplace. The Quesnel Hardwood Co-operative developed an action plan to add value to the hardwood lumber by doing more local processing.While not ultimately successful, the Quesnel Hardwood Co-operative did stimulate individual members to develop or expand businesses, and it stimulated the valuation and utlization of birch. Small birch mills are now operating throughout the region, and birch is being utilized more than it was prior to the formation of the Co-operative.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".