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Record W2792251447 · doi:10.11575/prism/30044

Nutrition North Canada: A Solution to Northern Canadian Food Insecurity?

2015· article· en· W2792251447 on OpenAlexfundaboutno aff
David F. Bray

Bibliographic record

VenueOpen MIND · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersAboriginal Affairs and Northern Development Canada
KeywordsFood insecurityFood securityGeographyPolitical scienceAgricultureArchaeology

Abstract

fetched live from OpenAlex

Canada is a relatively wealthy country and issues of food security do not appear to be a major problem. In Northern Canada, however, many individuals find it difficult to access the foods they need to satisfy healthy diet requirements. Food prices in Northern Canada are considerably higher than they are in the South. The costs of transporting food to Northern Canadian communities are high, due to their isolation and distance from shipping routes. The Canadian government has enacted policies to lower food costs: Nutrition North Canada is the current result of these efforts, and it is the second iteration of the Food Mail program enacted in the 1960s. Millions of dollars in subsidies are provided to Northern Canadian retailers to offset the high food transportation costs. Recently, however, a Report from the Auditor General of Canada raised doubts as to whether the program was working to lower food costs. In addition to high food costs, many individuals in Northern Canada, in territories such as Nunavut and the Northwest Territories earn low incomes. These regions also experience food insecurity at much higher rates than the rest of Canada. To ensure all Canadians have access to a proper diet, a more effective Northern food policy is needed. This Capstone provides background of food security in Northern Canada; examines past and current Northern food subsidies, and presents an alternative: providing low income Northerners with a food stamp style subsidy to ease the negative effects of the high costs of food. Enacting this policy would provide stability to low income Northerners and decrease food insecurity in Northern Canada.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.064
Threshold uncertainty score0.464

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0230.004
Scholarly communication0.0060.003
Open science0.0030.005
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0180.001

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.

Opus teacher head0.112
GPT teacher head0.360
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2015
Admission routes2
Has abstractyes

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