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Record W2560882694 · doi:10.32396/usurj.v2i2.145

Addressing a Northern Food Crisis: Process Evaluation of Nutrition North Canada

2016· article· en· W2560882694 on OpenAlexvenueaboutno aff
Lauren Dawn Achtemichuk

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidyGovernment (linguistics)Context (archaeology)Program Design LanguageBusinessPopulationProcess (computing)Food insecurityFocus groupMarketingFood securityPolitical scienceGeographyAgricultureEnvironmental healthEngineeringMedicineComputer science

Abstract

fetched live from OpenAlex

Inflated food costs are a contributing factor to food insecurity in isolated communities of Canada’s North. To increase the affordability and accessibility of healthy food in Northern communities, a federal government program Nutrition North Canada (NNC) offers retail-based subsidies on select nutritious foods shipped by air. In this paper, I integrate methods of process evaluation to determine whether or not the program components of NNC, such as the defined target population and subsidy design, are sufficient to achieve the intended program outcomes of increased affordability and accessibility of nutritious foods. A literature review drawing on government documents and journal articles outlines the setting of northern food insecurity and defines an inventory of NNC program components. Media articles published between 2011 and 2015 provide context and draw focus to specific implementation issues drawn from the NNC program. The process evaluation for this paper examines these documents for examples of inconsistency within the NNC program’s target, design, and structure that will affect successful program implementation and delivery. My results focus on inadequacies in the structure of the community eligibility target, subsidy design, and compliance reports. I conclude with recommendations on revising and strengthening these components, to ensure that the Nutrition North Canada program can reach its key goal of increasing the affordability and accessibility of healthy foods in isolated northern communities that do not have year-round marine and/or ground transport.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.133
GPT teacher head0.389
Teacher spread0.255 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueUSURJ University of Saskatchewan Undergraduate Research JournalSame topicIndigenous Studies and EcologyFrench-language works237,207