Vulnerability of Inuit women's food system to climate change in the context of multiple socio-economic stresses - a case study of Arviat, Nunavut
Bibliographic record
Abstract
Nunavut has the highest incidence of food insecurity in Canada, where 56% of Inuit households are believed to experience difficulties in obtaining sufficient food. Food insecurity occurs when food systems are stressed such that adequate nutrition is not accessible, available, and/or of insufficient quality. Inuit food systems comprising traditional and store food components are affected by economic, social and cultural transformations, and ecological changes, most notably associated with climate change. Inuit women have been identified to be particularly vulnerable to food insecurity, a condition that can be exacerbated by climate change stresses on their food system. This research identifies and characterizes the key factors determining Inuit women's food system vulnerability and adaptability to climate change and human stressors, and the factors contributing to food insecurity. This research was conducted in collaboration with the community of Arviat, Nunavut, using a community-based participatory research approach. Arviat is experiencing a high level of food insecurity, particularly among women. Photovoice, semi-structured interviews with Inuit women (n=42) and key informants (n=8), focus groups with women (n=7), elders (n=3) and hunters (n=2), and participant observations were used to collect in-depth qualitative data. Findings show that Inuit's food system in Arviat is sensitive to climate-related risks and changes, but climate change was not identified as affecting women's food security. Human factors such as financial resources and budgeting skills, store food knowledge, decrease in the transmission of country food knowledge, decrease in traditional training, substance use and gambling and high cost of living, negatively impact Inuit women's food security. On the other hand, a strong sharing network, governmental financial support and local educational initiatives help strengthen the food system and improve food security.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| 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".