Mapping the risks of sea ice change, shipping, and Peary and Dolphin-Union caribou movements to Inuvialuit and Inuit well-being in the Western Arctic
Bibliographic record
Abstract
The Arctic is changing. Its physical and geopolitical landscapes are rapidly transforming due to increasing temperatures and loss of sea ice—both of which present new risks to the Western Arctic in particular, where the corridors of the Canadian Arctic Archipelago are shared by Inuvialuit and Inuit communities, the Peary and Dolphin-Union caribou herds. Due to warming temperatures, there has also been an increase in the number of shipping vessels in this space. Currently, concerns at the intersection of caribou movement, sea ice change, Arctic shipping, and Inuvialuit well-being are unaddressed in risk assessments, which inspect risks as independent from each other, and it is difficult to illustrate the nexus of the four issues on a map. To more accurately understand these concerns and explore possibilities for more comprehensive mapping of risk, I used the methodology of Community-Based Participatory Research to design this project and research questions. A participatory mapping workshop was planned in collaboration between the research team and Inuvialuit leaders and used narrative inquiry to link stories to ArcGIS data documentation. Comparing the literature review on caribou, sea ice, shipping, and Inuvialuit use with the workshop results, I concluded that the risk at the nexus of the four issues depends on overlapping seasons and locations which are not explored by assessments that compartmentalize individual risk factors. Participatory mapping has the potential to illustrate risks as interconnected; I reflect on the method’s capacity to express Indigenous observations and oral histories. While the participatory mapping workshop increased data access for the Inuit and knowledge exchange between actors through interactive touchscreen technology, it did not fully capture the impacts of overlapping seasons and locations. To support increased knowledge exchange, I recommend holding a similar workshop in Inuit and Inuvialuit communities and focusing on cartographic methods informed by Indigenous concepts of space and time. Knowledge exchange of risks in the Arctic—of critical importance for adapting to the ongoing ecological and geopolitical change in this region—can be improved if Inuvialuit have access to the data and the tools used in decision-making. Risks can be more accurately understood if participatory mapping in the communities is used to incorporate Indigenous Knowledge and Indigenous conceptual frameworks in the study of risk.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| 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".