A community and its forests : evaluating public participation in resource management decisions, Slocan Valley, British Columbia
Bibliographic record
Abstract
This research addresses the question of effective public participation in resource management decisions within the context of resource-based communities. Despite advances in mechanisms for enabling public input, over the past 30 years, public participation remains problematic. Rather than promoting genuine communication and strengthening relationships between government, resource industries and communities, public participation often becomes an exercise in frustration that increases the adversarial nature of public policy decision-making. Evaluations of public participation have been undertaken across a broad spectrum of academic disciplines, with much emphasis placed on criteria relating to the process and outcome dimensions. The majority of approaches intend to provide universally applicable structures for public participation regardless of the socio-economic, cultural, institutional, or political context within which the process takes place. The purpose of this research was to determine whether consideration of contextual factors can enhance the effectiveness of public participation evaluation. Drawing on the experience of the Commission on Resources and Environment (CORE) process in the Slocan Valley, British Columbia, an in-depth analysis of the pre-process (antecedents), process, and post-process (outcomes) phases of the CORE consultations was performed. The qualitative research involved analysis of case-related documents relating to resource use history, community actors, record of public participation, as well as the application of a multi-criteria evaluation framework to the CORE process. The research revealed the iterative connections between antecedents, process and outcomes. A number of contextual factors placed significant constraints on the effectiveness of the public participation exercise. Intra-community factors included the polarization of interests and a legacy of distrust. These antecedent problems were exacerbated after-the process. Extra-com
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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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".