Community Interventions to the Food Insecurity Crisis Inuit Currently Face in Nunangat
Bibliographic record
Abstract
Inuit living in Nunangat, a northern territory in Canada, are facing unprecedented rates of food insecurity. The increasing impacts of anthropogenic climate change are rapidly changing the Arctic landscape in Nunangat, posing challenges to Inuit hunters who hunt and live completely self-sufficient off of the land. This lack of access to country foods and the impacts these conditions are having on Inuit communities are forcing Inuit to consider aid propositions from the Canadian government. Due to a long history of conflict with white settlers during the colonization of Canada, there is a feeling of distrust and cultural distaste between Canada and Inuit today. Furthermore, these relations and the processes associated with colonialism have created circumstances over time such as increased grocery prices, decreased hunting capabilities and food storage challenges, which are both damaging to Inuit food security as well as directly linked to colonist actions. Without intervention, food insecurity poses a direct and imminent threat to the survival of Inuit culture in the Nunangat region. Outside aid has proven unsuccessful and insulting to Inuit cultural values. Given this, Inuit are relying on self-representation technologies such as community freezer programs and an increasingly strong presence on social media platforms in order to both educate the world on their culture and current struggles as well as directly address food insecurity within Inuit communities across Nunangat.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".