Arctic Peoples, Culture, Resilience and Caribou
Bibliographic record
Abstract
The three-year program is comprised of twelve projects in Nunavut, Northwest Territories, the Yukon, Nunavik and Nunatsiavut. Most projects are community-based case studies (Aklavik, Tutoyaktuk, and Deline) which allow for indepth collaboration and inquiry. Another group of projects allows researchers to learn about cross cutting themes of resilience relevant to all communities in ACRC regions of Nunavut, Yukon and Northwest Territories. A third group of projects is aimed at synthesizing and compiling data gathered from the project in ways that will enable partners to meaningfully interpret and communicate the knowledge and experience of northern communities dealing with caribou population variability and decline. The perspectives of northern communities on environmental change vary significantly by region; while some communities have significant knowledge and capacity to deal with variability and change in resources such as caribou, others have had limited experience, knowledge and skills for coping, mitigating or adapting to change. Even within communities, the perspectives can be diverse depending on such variables as: income and education, age, gender, knowledge/experience in land-based activities, social networks (for knowledge and resource sharing), and role in governance (e.g., representation on co-management boards). ACRC has engaged with Inuit, Dene and Gwich'in communities from Nunavut, Northwest Territories and Yukon. Multiple methods from archival to oral history research, individual interviews to large format workshops, desktop to on-the-land activities have provided researchers with opportunities to learn about resilience from caribou hunters (men and women), community leaders, resource managers, elders, adults and youth from more than nineteen arctic and subarctic communities.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".