Warming Arctic and its Cascading Impacts on Water, Energy, and Food (WEF) Systems: A Case Study of Iqaluit, Nunavut
Bibliographic record
Abstract
This paper draws on a case study of Iqaluit, Nunavut, to exemplify the conceptual utility of the water – energy – food (WEF) nexus as a starting point in better understanding the cascading nature of climate change impacts. The case study demonstrates that damage to Iqaluit’s main fuel storage tank caused by instability in the permafrost layer induced a series of cascading impacts that affected Iqaluit’s water, food, sanitation, and health care services. Because of the non-linear nature of cascading impacts, the response was largely reactionary, rather than anticipatory, leaving Iqaluit residents exposed to heightened and extended periods of WEF insecurity. Given the relatively weak state of WEF security in Arctic regions, coordinated policy action is needed to increase the resilience of Arctic WEF systems. We suggest the WEF nexus can support those coordinated efforts by avoiding siloed responses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".