A survey of interventions to actively conserve the frozen North
Bibliographic record
Abstract
Abstract The frozen elements of the high North are thawing as the region warms much faster than the global mean. The dangers of sea level rise due to melting glacier ice, increased concentrations of greenhouse gases from thawing permafrost, and alterations in the key high latitude physical systems spurred many authors, and more recently international agencies and supra-state actors, to investigate “emergency measures” that might help conserve the frozen North. However, the efficacy and feasibility of many of these ideas remains highly uncertain, and some might come with significant risks, or could be even outright dangerous to the ecosystems and people of the North. To date, no review has evaluated all suggested schemes. The objectives of this first phase literature survey (which can be found in a separate compendium ( https://doi.org/10.5281/zenodo.10602506 ), are to consider all proposed interventions in a common evaluation space, and identify knowledge gaps in active conservation proposals. We found 61 interventions with a high latitude focus, across atmosphere, land, oceans, ice and industry domains. We grade them on a simple three-point evaluation system across 12 different categories. From this initial review we can identify which ideas scored low marks on most categories and are therefore likely not worthwhile pursuing; some groups of interventions, like traditional land-based mitigation efforts, score relatively highly while ocean-based and sea ice measures, score lower and have higher uncertainties overall. This review will provide the basis for a further in-depth expert assessment that will form phase two of the project over the next few years sponsored by University of the Arctic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".