Nouvelle production alimentaire menée par la communauté au Nunavut
Bibliographic record
Abstract
New community-led food production in Nunavut New community-led food production in NunavutAccording to a recent study, 57% of households in Northern Canada have experienced food insecurity.Since these are areas where the ground is frozen for all or part of the year, Inuit communities could not, until recently, turn to conventional agriculture for help in addressing this issue.The Inuit community of Gjoa Haven, Nunavut partnered with Agriculture and Agri-Food Canada (AAFC) researchers, in collaboration with other federal agencies and the Arctic Research Foundation, to pool their expertise with the traditional knowledge of the community to rise to the challenge.Together, they created the "Naurvik Initiative" which means "the growing place" in Inuktitut.The science team initially sought guidance from the Inuit community, including many Elders, to identify their needs and expectations and build a climate of trust.Working closely together, they then designed and set up a sustainable, community-driven food production system that can be used in the challenging conditions of Canada's North.The team adapted 20-foot recycled shipping containers to become growing places for fruit and vegetables, powered by Canada's northernmost solar and wind energy systems.When daylight gets short, the wind tends to pick up and generate energy.A diesel generator on-site can supplement energy when needed.These highly innovative plant production systems:• capture, store, and use renewable energy; • grow traditional and non-traditional plants chosen by the community; and • aim to recycle and reuse biomass, nutrients, and water resources making it a closed, zero-emission ecological system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".