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Record W2062988956 · doi:10.1068/c0724r

Government Support to Regional Food Producers: An Assessment of England's Regional Food Strategy

2008· article· en· W2062988956 on OpenAlexaff
Matthew Gorton, Angela Tregear

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsHeadlineGovernment (linguistics)BusinessQuality (philosophy)Advertising

Abstract

fetched live from OpenAlex

The rationale for, and impact of, government support to regional food producers is investigated through a case study of England's Regional Food Strategy (RFS). The headline target for the RFS is to increase the turnover of the quality regional food sector by 25% over a five-year period. The RFS also seeks to propagate wider benefits such as local economic development and aiding farms to shift to more environmentally friendly methods. The analysis indicates that the headline target is likely to be met comfortably. Producers that have received support under the RFS have performed better than nonbeneficiaries and positive assessments of the business training and advice received are recorded. However, the purported linkages with wider benefits are difficult to establish. Trade-offs between the competitiveness agenda of stimulating growth and meeting some wider policy goals are apparent.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.242
Teacher spread0.211 · 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 designObservational
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

Citations14
Published2008
Admission routes1
Has abstractyes

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