Bibliographic record
Abstract
The Inuit Tapiriit Kanatami, the national organization for Inuit in Canada, has voiced serious concern about the food insecurity crisis in Inuit Nunangat, the Inuit homeland comprising Nunavut, Nunavik, Nunatsiavut, and the Northwest Territories (Inuit Tapiriit Kanatami, 2019). The widespread and disproportionate experiences of food insecurity in Inuit Nunangat requires critical examination, especially when access to adequate food has been identified as a human right (OHCHR, 2010). My research paper aims to explore this topic of food insecurity as a human rights concern in Inuit Nunangat. A human rights approach acts as both a pathway to investigate, and a tool to inform, policy development. Such an investigation is especially relevant given Canada’s international reputation and constitutional mandate to grant equal protection of rights to all citizens. In this essay, I review international and domestic human rights frameworks that intersect with Inuit food insecurity, in addition to evaluating Canada’s current interventions. I ultimately argue that, based on Canada’s commitments to uphold rights to food, health, and Indigenous self-determination, the government must increase the enforceability of food rights in domestic policy and, second, there must be strengthened collaboration between the government and Inuit partners to more appropriately conceptualize, and respond to, food needs in Inuit Nunangat.
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 | 0.002 | 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 | 0.018 | 0.024 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".