Alternative scenarios for the future of the Canadian boreal zone<sup>1</sup>
Bibliographic record
Abstract
In response to global climate change, Canada is transitioning towards a low-carbon economy and the need for policy approaches that are effective, equitable, coordinated, and both administratively and politically feasible is high. One point is clear; the transition is intimately tied to the vast supply of ecosystem services in the boreal zone of Canada. This paper describes four contrasting futures for the boreal zone using scenario analysis, which is a transdisciplinary, participatory approach that considers alternative futures and policy implications under conditions of high uncertainty and complexity. The two critical forces shaping the four scenarios are the global economy’s energy and society’s capacity to adapt. The six drivers of change are atmospheric change, the demand for provisioning ecosystem services, the demand for nonprovisioning ecosystem services, demographics, and social values, governance and geopolitics, and industrial innovation and infrastructure. The four scenarios include: (i) the Green Path, where a low-carbon economy is coupled with high adaptive capacity; (ii) the Uphill Climb, where a low-carbon economy is instead coupled with low adaptive capacity; (iii) the Carpool Lane, where society has a strong capacity to adapt but a reliance on fossil fuels; and (iv) the Slippery Slope, where there is both a high-carbon economy and a society with low adaptive capacity. The scenarios illustrate the importance of transitioning to a low-carbon economy and the role of society’s adaptive capacity in doing so. However, they also emphasize themes like social inequality and adverse environmental outcomes arising from the push towards climate change mitigation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".