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Record W3209684520 · doi:10.15353/cfs-rcea.v8i3.515

Wayne Roberts: Food systems thinker, public intellectual, “actionist”

2021· article· en· W3209684520 on OpenAlexafffundvenueabout
Patricia Ballamingie, Charles Z. Levkoe

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsLakehead UniversityCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaMinistry of Education, India
KeywordsSociologyPower (physics)PoliticsPolitical scienceGovernment (linguistics)Public relationsLawPhilosophy

Abstract

fetched live from OpenAlex

Wayne Roberts (1944–2021) was a food systems thinker, public intellectual, and “actionist.” This text was developed from a series of oral history interviews conducted between December 2020 and January 2021. It touches upon several of the key themes Wayne addressed during the interviews: adopting a food systems approach; employing the power of ideas; identifying solutions and being propositional; acknowledging progress for political credit; enhancing impact through media, old and new; working strategically to “seed” then “tip”; playing ball to influence government; and, forming alliances with academics and other champions. In addition, we provide selected links to additional resources from Wayne himself. In this article, which inaugurates the Interviews section of Canadian Food Studies/La Revue canadienne des études sur l’alimentation, we aim to do justice to the gift of Wayne’s experiences and knowledge by sharing a selection and synthesis of his words.

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)0.005
metaresearch head score (Gemma)0.009
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.694

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0190.023
Scholarly communication0.0100.007
Open science0.0010.002
Research integrity0.0040.005
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 head0.074
GPT teacher head0.227
Teacher spread0.153 · 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
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
Published2021
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Food Studies / La Revue canadienne des études sur l alimentationSame topicCulinary Culture and TourismFrench-language works237,207