Inuit Qaujimajatuqangit in community-based monitoring of ecological changes in Igluligaarjuk (Chesterfield Inlet)
Bibliographic record
Abstract
Studies have shown that climate change and other anthropogenic activities like infrastructure developments, shipping, and mining have changed the Arctic ecosystem. Such changes have cumulative impacts on the social and ecological system related to the Inuit. Indigenous Knowledge (IK) and Community-based monitoring (CBM) are crucial in monitoring the changes and their impacts. This research identifies the ecological changes and their impacts on the Chesterfield community. It documents how the community uses Inuit Qaujimajatuqangit (IQ) indicators to monitor the changes. Next, it discusses the challenges and implications of knowledge integration during CBM. Community-based qualitative research was used as a methodology including interviews with fifteen Inuit hunters, Elders, and knowledge holders, and two workshops. Recommendations from Indigenous research frameworks and tools were incorporated throughout the research. This research finds that the community has observed changes in sea ice, rivers, lakes, land, animals, and marine ecosystems. Climate change, shipping, and mining in Baker Lake are the primary reasons for the changes. These stressors have impacted the social, cultural, economic, and ecological aspects of the community. Some of these impacts (for example, a decrease in the abundance of seals) are tangible whereas others (for example, impact on knowledge) are intangible. Changes in the sea ice and increasing shipping are the main concerns of the community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".