Perceptions of climate change risk to forest ecosystems and forest-based communities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perception of risk or subjective risk is playing an increasingly important role in risk assessment. This paper describes a study that investigated perceptions of climate change risk to forest ecosystems and forest-based communities among a sample of Canadian forestry experts. Data were collected by questionnaire from participants at a climate change and forestry workshop, sponsored by the Canadian Climate Impacts and Adaptation Research Network Forest Sector and the McGregor Model Forest held in Prince George, British Columbia in February 2003. These forestry experts were somewhat concerned about the impacts of climate change, and they appeared unlikely to oppose strategies for preparing for and adapting to climate change. The respondents felt that the effects of climate change on forests and forest-based communities are not well understood by the general public or forest managers. They also felt that there is a relatively high level of uncertainty about the effects of climate change, especially with respect to forest-based communities. These results have important implications, including reinforcement of the need for greater awareness of climate change risks and for increased research and monitoring effort targeted at reducing levels of uncertainty about future impacts at local scales. Key words: climate change, risk perceptions, forest ecosystems, forest-based communities
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it