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Record W4407577256 · doi:10.4337/9781035326570.00035

North American food security: integration and conflict

2025· book-chapter· en· W4407577256 on OpenAlexaboutno aff
Elizabeth Smythe

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2025
Typebook-chapter
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsFood securityPolitical scienceComputer securityGeographyComputer scienceArchaeologyAgriculture

Abstract

fetched live from OpenAlex

This chapter argues that food is not a typically traded commodity in that it is necessary for life and deeply tied to culture and community. Thus, efforts to liberalize trade and harmonize regulations related to food have led to resistance and conflict despite the emergence of a global corporate food regime. Food security, as defined by the Food and Agricultural Organization, continues to be a concern as access to healthy, nutritious food remains problematic. This is evident, as the chapter indicates, in North America, where, despite increased integration in the food system since the signing of the NAFTA agreement, conflict over food persists. Despite liberalization under NAFTA, the US has continued to heavily subsidize corn production, dumping surpluses into the Mexican market and impacting agricultural livelihoods there. The benefits of this integration were not evenly shared, nor have they necessarily resulted in better access to healthy food. The chapter uses cases of conflict over biotechnology, food labeling, and public health measures to address the unhealthy neo-liberal diet, rising levels of obesity, and chronic diseases. It argues that with the renegotiation of NAFTA and the emergence, since 2016, of Mexican efforts to regulate biotechnology and move to more self-sufficiency in key crops, policy divergence and conflict between Mexico and the US and Canada will continue. Despite the disruptive impact of Covid-19 on supply chains and food security, the US and Canada continue to push to maximize food exports and not address food supply vulnerability.

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)0.001
metaresearch head score (Gemma)0.002
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: Other
Teacher disagreement score0.951
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0090.006
Scholarly communication0.0090.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.099
GPT teacher head0.370
Teacher spread0.271 · 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
Published2025
Admission routes1
Has abstractyes

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