Well-being and environmental change in the arctic: a synthesis of selected research from Canada’s International Polar Year program
Bibliographic record
Abstract
The social and cultural dimensions of arctic environmental change were explored through Canada’s International Polar Year (IPY) research program. Drawing on concepts of vulnerability, resilience and human security, we discuss preliminary results of 15 IPY research projects (of 52) which dealt with the effects and responses of northern communities to issues of ecological variability, natural resource development and climate change. This paper attempts to determine whether the preliminary results of these projects have contributed to the IPY program goal of building knowledge about well-being in the arctic. The projects were diverse in focus and approach but together offer a valuable pan-northern perspective on many themes including land and resource use, food security, poverty and best practices of northern engagement. Case study research using self-reported measures suggests individual views of their own well-being differ from regional and territorial standardized statistics on quality of life. A large body of work was developed around changes in land and resource use. A decline in land and resource use in some areas and consequent concerns for food security, are directly linked to the effects of climate change, particularly in coastal areas where melting sea ice, erratic weather events and changes in the stability of landscapes (e.g., erosion, slumping) are leading to increased risks for land users. Natural resource development, while creating some new economic opportunities, may be compounding rather than offsetting such stresses of environmental change for vulnerable populations. While the IPY program has contributed to our understanding of some aspects of well-being in the arctic, many other issues of social, economic, cultural and political significance, including those unrelated to environmental change, remain poorly understood.
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 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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.016 | 0.051 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".