Personal and group forest values and perceptions of groups' forest values in northwestern Ontario
Bibliographic record
Abstract
With the recent involvement of a greater diversity of groups working in forest management planning, the identification and understanding of people's forest values and their perceptions of one another's values may be a promising approach to sustainable forest management. This study identifies and analyzes the forest values and perceptions of the members of four groups, Aboriginal People, Environmental Non-Government Organizations (ENGOs), the forest industry, and the Ontario Ministry of Natural Resources (OMNR), in northwestern Ontario. Conceptual Content Cognitive Mapping (3CM) was used to identify people's forest values and perceptions and dominant forest value themes were created using hierarchical clustering. Inter-group and intra-group similarities and differences among the rankings of participants' forest values and their perceptions were determined through various non-parametric statistical tests. Participants' perceptions about each group were generally similar, which included the two most prominent themes to be similar across all participants' perceptions of each group. Although the perceptions for a particular group were similar across the participant groups, they differed substantially with that participant group's personal ranking of the forest value themes. Key words: forest values, perceptions, stakeholders, cognitive mapping, sustainable forest management, collaborative decision-making
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".