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Record W3104194793 · doi:10.15353/cfs-rcea.v7i2.413

“Ditch red meat and dairy, and don’t bother with local food”: The problem with universal dietary advice aiming to save the planet (and your health)

2020· article· en· W3104194793 on OpenAlexaffvenue
Ryan Katz-Rosene

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSustainabilityFood systemsInclusion (mineral)Food securityBiologySociologyEcologySocial science

Abstract

fetched live from OpenAlex

In recent years there have been increasing calls for “global dietary transition” in order to save the planet and improve human health. One troubling development associated with this is the attempt to delineate in universal terms what constitutes a sustainable and healthy diet. This perspective takes issue with this development, and specifically refutes one increasingly popular dietary narrative which calls for people to avoid red meat and dairy, and which portrays the local food movement as a romantic distraction. In contrast, the paper provides evidence of a range of sustainability and health benefits associated with both local food systems and the agri-food system’s inclusion of ruminants (the suborder of mammals from which humans mostly derive red meat and dairy). Finally, the perspective calls for a pluralist and multi-scalar approach to the multifaceted challenges associated with food production.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.394
Threshold uncertainty score0.793

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0110.031
Scholarly communication0.0070.005
Open science0.0020.003
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.203
Teacher spread0.181 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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