Understanding the impacts of climate change on the Northern Inuit community
Bibliographic record
Abstract
he increasing rate of anthropogenic climate change has a serious impact on weather and temperature, wildlife and vegetation patterns, and food and water availability. The dramatic effects of climate change are also experienced by the Indigenous communities of the North, making them the primary victims of this existential global health threat. While it is recognized that climate change can cause emotional and mental distress to a general population, the effects of climate have significant impacts on the Northern Inuit community who use the land to hunt, harvest, and practice their cultural beliefs. With the Indigenous population already at a higher risk and susceptibility to health disparities, climate change is an additional factor that further exacerbates the land-based relationality. Inuit mental health relies on the stability of land-based associations which allows the community to connect with their ancestors, nature, and history. A disconnect in relationality to the land, an involuntary diminishment of important cultural ties, and relocation are all involuntary environmental stressors that were thrust onto Indigenous communities due to climate change. While the impacts of climate change may contribute to re-traumatization, stress, and negative mental health, there is also strength found within the changes which demonstrate cultural resiliency. This paper aims to understand the impacts of climate change on the Indigenous communities of the north, with a key focus on Inuit mental health and land-based relationality within Inuit mental health.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".