Transfer of climate knowledge via a regional climate-change management body to support vulnerability, impact assessments and adaptation measures
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
We provide an overview of how climate-change-science knowledge transfer is achieved at Ouranos in support of vulnerability and impact assessments and adaptation (V&I&A) activities. Ouranos is a Canadian consortium concerned with regional climatology and adaptation to climate change, launched in 2002 by the Government of Qubec, Hydro-Qubec and the Meteorological Service of Canada to coordinate climate-change research in Qubec. Focusing on Ouranos' ongoing V&I&A projects in coastal regions, we describe the current knowledge-transfer environment. We also discuss how climate indices and indicators of vulnerability -which are developed by Ouranos following a 'pressure-state-response' (PSR) framework -form useful knowledge-transfer tools. Two specific case studies exemplify the development of (1) a set of temperature-trend indices for southern Qubec and (2) climate-social indicators for the assessment of risks to public health due to extremely high temperature events. Case Study (1) illustrates how a systematic analysis of climate variability and relevant indices of extremes can be useful for decision makers at regional scales (southern Qubec). Case Study (2) examines the potential, and feasibility, of using a risk-assessment framework for regional climate-change studies that focus on impacts and adaptation.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 it