Co-management institutions, knowledge, and learning: Adapting to change in the Arctic
Bibliographic record
Abstract
How vulnerable are Arctic Indigenous peoples to climate change? What are their relevant adaptations, and what are the prospects for increasing their ability to deal with further change? The Intergovernmental Panel on Climate Change makes little mention of Indigenous peoples, and then only as victims of changes beyond their control. This view of Indigenous peoples as passive and helpless needs to be challenged. Indigenous peoples, including the Canadian Inuit, are keen observers of environmental change and have lessons to offer about how to adapt, a view consistent with the Inuit self-image of being creative and adaptable. There are three sources of adaptations to impacts of climate change: 1) Indigenous cultural adaptations to the variability of the Arctic environment, discussed here in the context of the communities of Sachs Harbour and Arctic Bay; 2) short-term adjustments (coping strategies) that are beginning to appear in recent years in response to climate change; and 3) new adaptive responses that may become available through new institutional processes such as co-management. Institutions are related to knowledge development and social learning that can help increase adaptive capacity and reduce vulnerability. Two co-management institutions that have the potential to build Inuit adaptive capacity are the Fisheries Joint Management Committee (established under the Inuvialuit Final Agreement ), and the Nunavut Wildlife Management Board.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".