Design for tomorrow: future-proof arctic architecture in cognizance of shifts in climate and regional livelihood
Bibliographic record
Abstract
Accelerating climate change is dramatically altering environments \nworldwide, which also has significant impacts on cultural practices and \nlivelihoods in vulnerable regions. Warming at three times the global average, \nthe Arctic and its Inuit population are in a precarious state. This Thesis \nthus focuses on the future-proofing of the Torngat Mountains National \nPark Base Camp and Research Station (Nunatsiavut, Labrador). Informed \nby predictive climate models and a review of architectural strategies to \nrespond to inevitable and expected climate change, the Base Camp is \nredesigned to ensure short-term and long-term adaptability and resilience. \nThe design is simultaneously informed by land-based ecological and cultural \nlessons, connecting the building back to the people and supporting the \ntraditional livelihood that is intrinsically linked to their land. The meeting \nof researchers, Inuit, and tourists in this place should foster opportunities \nto learn from one another about mitigating and adapting to changes to \npreserve land and livelihood.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".