The Role of the State in Managing Common Pool Resources: The Search for Solutions to Manage Non-Timber Forest Products in British Columbia, Canada
Bibliographic record
Abstract
"Institutional and property rights literature on common pool resources (CPRs) describes various conditions under which successful property regimes may evolve. But what happens when this natural evolution does not occur, property regimes dissolve, or competing and detrimental uses have well defined rights that take precedence? The backdrop for this presentation is British Columbia, Canada, where the commercial harvest of non-timber forest products occurs at potentially destructive rates on de facto open access or under-managed public land, amidst a well defined timber tenure system. Appropriators are disorganized and the provincial government struggles to understand if a problem exists, and to identify appropriate policy responses. The research upon which this paper is based seeks to understand why a state should intervene in a CPR market, when a state should intervene, and how a state may intervene and begin to structure the way in which it approaches the management problem? Thus, what is the state's role in managing CPRs? The paper develops an intervention model to assess CPRs under stress and to determine whether or not some form of intervention is necessary. By identifying sources of institutional failure and contextual factors that contribute to the level of potential degradation the model provides a basis to begin to approach the management of a CPR through facilitative, coordinating, or prescriptive approaches. This approach does not start with a particular management paradigm; rather it starts with the CPR social-ecological system and builds the management regime up from the level of the resource and user-community. The commercial harvest of salal in British Columbia is used as a test case. The model indicates commercial salal is at risk and government intervention is warranted."
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".