Scenarios of climate change and natural resource development: Complexity and uncertainty in the Nechako Watershed
Bibliographic record
Abstract
Climate change and resource development interact to have significant impacts on both natural and human systems within watersheds. It is, however, difficult to conceptualize and communicate these intersections, as climate change and resource development are each independently uncertain and complex. We facilitated a process whereby stakeholders created plausible future scenarios for the Nechako Watershed in British Columbia, Canada. This region is reliant upon, and has been significantly affected by, many types of resource exploitation. During a full‐day workshop, 32 stakeholders created scenarios for 2050 envisioning high and low levels of both resource development and climate change. The high and low levels of climate change were based on downscaled projections from global emissions scenarios, and the resource development levels were determined at the beginning of the workshop by the participants. The exercise was educational, and motivated stakeholders to conceptualize plausible future changes and their impacts, and the outcomes should motivate stakeholders to work towards realizing a more desired future. All scenarios (even low‐low) were deemed to have significant negative impacts, suggesting that the Nechako Watershed is in a vulnerable state. The complexity of the exercise suggests that more capacity building may be necessary.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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 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".