Bibliographic record
Abstract
Summary The Great Lakes Forest Alliance, created by charter in 1987 at the direction of the governors of Michigan, Minnesota, and Wisconsin, is a mutual aid, public/private partnership that integrates global, national and local interests by bridging the gap at a regional level. It expanded in 1997 to include Ontario. Trustees include key leaders of government and industry and citizens from a broad range of forest interests. It was designed to be as learning environment to address the resurgence of forest growth and the increasing demand for conservation, wood products and recreation. The need for the Alliance resulted in part from a perceived underrepresentation of regional forest-related issues in the national arena. The Alliance attempts to consider leading-edge strategies over the long-term in a pro-active manner, and trustees recognize the need to build respect, trust, information exchange, cooperation, coordination and collaboration among diverse interests. Among the projects that demonstrate the bridge role played by the Alliance: a regional forest resources assessment, public and private funding that supports research toward a more frequent forest inventory process, training for communities to use the collaborative learning process to address economic prosperity and environmental protection strategies and the development of sustainable forest management criteria and indicators for the region. A continual challenge is relationships among diverse forest interests across jurisdictional and institutional boundaries in a manner that promotes exchanges that build collective wisdom.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".