Evaluating the Floe Edge Service: how well can SAR imagery address Inuit community concerns around sea ice change and travel safety?
Bibliographic record
Abstract
In response to increasing environmental and social changes in the past few decades, some Inuit hunters have been turning to scientific tools to help evaluate sea ice conditions. Simultaneously, there has been more scientific interest in understanding local scale processes through Inuit knowledge in order to develop a broader comprehension of dynamic sea ice conditions and implications of long‐term change. Building on several years of collaborative research with Inuit sea ice experts in Cape Dorset, Igloolik, and Pangnirtung, Nunavut, and local expressions of interest in increased access and availability of satellite imagery of sea ice, the Polar View Floe Edge Service was expanded to each community in the spring of 2007. Follow‐up workshops in November 2007 helped to evaluate and improve the service by considering previous local uses of satellite imagery and tailoring Floe Edge Service regions of interest to local areas of sea ice use. Through workshop discussions, several opportunities for the use of synthetic aperture radar (SAR) imagery emerged, including: seeing what is on (or within/under) the ice; monitoring seasonal and long‐term sea ice changes; hazards assessment; planning travel routes; and facilitating search and rescue operations. A number of challenges were also identified, such as: SAR image interpretation; image spatial resolution; frequency of image acquisition; SAR image representation capabilities; and technological limitations. The workshops also provided some insights into intercultural and intergenerational exchanges and led to a number of recommendations to continue expanding and improving the Floe Edge Service. This case study shows how remote sensing can be incorporated into the suite of traditional indicators and technological tools that hunters draw upon in their evaluations of complex human‐animal‐environment assessments. In the face of declining and unpredictable sea ice conditions, bridging scales and knowledge systems will be essential in developing integrated monitoring systems to respond to increased political and economic pressures as well as safety concerns for travelling on or within ice‐covered oceans .
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".