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Record W3027446054 · doi:10.13140/rg.2.2.10891.23840

Policy Brief 3: Research and Innovation Supporting the Farm to Fork Strategy of the European Commission

2020· article· en· W3027446054 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVU Research Portal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsAthena Sustainable Materials Institute
FundersEuropean Commission
KeywordsFood securityFork (system call)Food systemsBusinessCitizen journalismLeverage (statistics)European commissionSustainabilitySustainable developmentCommissionParticipatory action researchMarketingPolitical scienceEconomic growthEconomicsEngineeringEuropean unionAgricultureInternational tradeGeography

Abstract

fetched live from OpenAlex

The EU Think Tank(as part of theFIT4FOOD2030 Coordination and Support Action) strongly supports the development of the Farm to Fork Strategy as a key component of the European Green Deal, recognising the need to transform the food system as a whole. This policy brief calls for innovative approaches tothe Farm to Fork Strategy to provide practical answersto two central questions: i) how can a shift towards healthier and more sustainable diets be facilitated?;and ii) how can all actors in the food system be empoweredto adopt more sustainable practices? Answers tothese questions raise the need fornew transdisciplinary, multi-actor and participatory Research and Innovation (R&I)approachesthat enable citizens,farmers, fishers, food processors, distributors, retailers and consumers to contribute to more coherent, cross policy-sector food initiatives that leverage on European food systems to deliver a balance of public goods (including food security and environmental integrity).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.159
GPT teacher head0.382
Teacher spread0.222 · 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