Fostering climate resilience through northern standards: shaping a resilient future
Bibliographic record
Abstract
Climate-resilient standards and guidelines -those that consider a future-looking climate and account for associated risks -can be powerful resources for professionals, practitioners, and governments in designing and implementing sustainable solutions.By standardizing best practices, National Standards of Canada (NSCs) can streamline and harmonize the field of climate resilience while playing an integral role in improving the overall health and safety of Canadians, and of their environment.The Standards Council of Canada (SCC) is leading the development of climate-resilient standards that can be implemented to adapt communities to climate change and extreme natural events.Since 2011, SCC has been working with communities, standards development organizations, and experts from across northern Canada to lead the development of standards that consider climate change impacts in northern infrastructure design, planning and management.This paper will cover the development of standards and guidelines that support the design of foundations and infrastructure in permafrost regions, namely:• CSA S500:21 Thermosyphon foundations for buildings in permafrost regions • CSA S501:21 Moderating the effects of permafrost degradation on existing building foundations • BNQ 9701-500 Risk-based approach for community planning in northern region • CSA PLUS 4011:19 Technical guide: Infrastructure in permafrost: A guideline for climate change adaptationThe purpose of this study is to highlight standards that will help building owners and operators, as well as those responsible for public and community infrastructure, build and maintain infrastructure in a changing climate in permafrost regions.Further, it is meant to inform northern practitioners on the benefit of building and designing infrastructure with guidance that goes "beyond the building code" under a changing climate. 1
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".