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Record W7024972183

Taking Stock of Canada's Approach to Food Insecurity

2019· dissertation· en· W7024972183 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2019
Typedissertation
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsSummitStock (firearms)Government (linguistics)Food policyFood securityPublic policyAction planFood systemsAction (physics)
DOInot available

Abstract

fetched live from OpenAlex

In 1998, the Department of Agriculture and Agri-food published a document entitled Canada’s Action Plan for Food Security, outlining seven commitments stemming from a 1996 World Food Summit in Rome. The goal was to reduce the number of undernourished people in the world by half by the year 2015. Instead, Canada witnessed a slow but steady growth of those identifying as food insecure in the two decades following the publication of the Action Plan. There are many hypotheses as to why that is the case, with the bulk of the literature focusing on a policy environment characterized by government inaction and \noverburdened civil society organizations. This thesis argues that this policy environment was not an accident, but the result policy tools selected to address this social issue by successive federal governments. To that end, the thesis employs a policy tools analytical framework to categorize the types of tools chosen as either procedural or substantive in nature, and in doing so it assesses the amount of priority placed on household food insecurity. It quantifies the number of tools chosen to address food industry concerns versus those aimed at frontline service providers, and illustrates why the recently published National Food Policy was necessary to address an issue identified as worthy of government intervention two decades earlier.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.172
Threshold uncertainty score0.961

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0340.029
Scholarly communication0.0160.004
Open science0.0020.005
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.155
GPT teacher head0.399
Teacher spread0.244 · 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
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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