Is the Arctic Human Environment Moving to a New State?
Bibliographic record
Abstract
This collaboration of Kruse, University of Alaska, Anchorage (0638408, LEAD) and Hamilton, University of New Hampshire (0638413) is part of the Arctic Observation Network (AON), initiated as part of the International Polar Year, and will implement phase one human dimension priorities of the Study of Arctic Environmental Change (SEARCH) program. This Human Dimension Observation System is designed to become part of a network of measurement systems developed within SEARCH. The goal of the researchers is to understand how socio-economic systems respond to rapid environmental change, and how local response interacts with broad forces of development and government policies to affect the well-being of Arctic residents. They will integrate existing data for key variables identified by the Committee: population size and structure, births, deaths, migration, health measures, cultural diversity, education, and economic indicators, including employment, subsistence, and government structure. For this study, they have identified stakeholder groups in each of the "arenas of climate-human interaction" (i.e., marine mammal hunting, fisheries, resource development) and have formed an advisory group made up of representatives of the following indigenous organizations: RAIPON, Inuvialuit Regional Corporation, Saami Council, Maniilaq, North Slope Borough, Makivik Corp., and the Labrador Inuit Association. The project will focus on four arenas likely to involve climate-human interactions: marine mammal hunting; oil, gas, and mineral development; tourism; and fisheries. A fifth project focus is on indicators of social outcomes of human interactions with environmental change. As part of AON, the project is designed to foster integrated analysis across the physical, natural, and social sciences.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".