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Record W270681587

Comparing food costing approaches in British Columbia and Nova Scotia

2008· dissertation· en· W270681587 on OpenAlexaboutno aff
Clarissa Dawn Jones

Bibliographic record

VenueSummit (Simon Fraser University) · 2008
Typedissertation
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaActivity-based costingFood securityPublic healthDieticiansBusinessEnvironmental healthWork (physics)GeographyEnvironmental planningMedicineEngineeringMarketingNursingAgriculture
DOInot available

Abstract

fetched live from OpenAlex

Food security is a determinant of health and a basic human right. Food insecurity is associated with a variety of negative health outcomes varying from nutrient deficiencies to chronic conditions such as cardiovascular disease and cancer. Therefore, the availability and affordability of a basic nutritious diet is a public health concern. Food costing is one method used to address affordability of a basic nutritious diet and is completed annually across Canada. In British Columbia, dieticians who work in public health conduct food costing. In Nova Scotia, trained community members who are or have been food insecure conduct food costing. This paper compares food costing approaches in British Columbia and Nova Scotia, exploring the strengths and challenges of each. Both systems have made important contributions to help address food security. The Nova Scotia model, using a participatory approach has an added benefit of building capacity within the local community.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.001
Scholarly communication0.0020.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.153
GPT teacher head0.329
Teacher spread0.177 · 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 designObservational
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

Citations0
Published2008
Admission routes1
Has abstractyes

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