Evaluating Collaborative Planning: A Case Study of the Morice Land and Resource Management Plan
Bibliographic record
Abstract
Collaborative planning is widely used in British Columbia, Canada as a decision-making tool for land use management. This study uses a research design synthesized from the relevant literature to evaluate the Morice Land and Resources Management Planning process, which began in 2002. After 18 months of negotiation between local stakeholders, the Morice table produced a consensus agreement for land use in the region. Unlike other processes in BC, a two-tiered negotiation model was used to engage First Nations on a government-to-government basis. This study demonstrates a need to revisit the two-tier process design in a way that continues to respect First Nations’ constitutional rights while also satisfying non-aboriginal stakeholders. Despite room for improvement, the Morice process was an overall success and generated important environmental and socio-economic benefits for stakeholders. This case study joins a growing body of research supporting collaborative planning as an effective land use management practice.
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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 | 0.027 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".