The John Prince Research Forest: Evolution of a co-management partnership in northern British Columbia
Bibliographic record
Abstract
The John Prince Research Forest (JPRF) was established as a co-managed forest between Tl'azt'en Nation and the University of Northern British Columbia, as an opportunity for these partners to blend their respective ways of understanding and managing forests to contribute to ecological and social sustainability. Using four criteria of successful co-management reported in the literature as critical to the early stages of partnership — partnership building, institutional structure, decision-making, and capacity — we discuss the JPRF's performance during the first half-decade of its existence. The JPRF's early experience provides an example of the evolution of a co-management relationship that, while facing constraints and challenges in regard to some of the criteria, has provided the foundation for a strong future partnership. Key words: co-management, research forest, Aboriginal, First Nation, British Columbia, criteria and indicators (C&I), community forestry, forest management, joint venture, Tl'azt'en Nation, traditional environmental knowledge, forest tenure, partnerships
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".