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Record W2346270714 · doi:10.1111/cjag.12107

Economic Experiments as a Tool for Agricultural Policy Evaluation: Insights from the European CAP

2016· article· en· W2346270714 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCommon Agricultural PolicyEuropean unionToolboxEuropean commissionPolitical scienceRegional scienceAgricultural policyAgricultureGeographyEconomicsComputer scienceInternational trade

Abstract

fetched live from OpenAlex

This article assesses the potential contribution of economic experiments to evidence‐based policy making in the field of agriculture, with a special focus on the European Union (EU)'s Common Agricultural Policy (CAP). CAP evaluation mostly relies on standard tools such as farm and market simulation models, calibrated with EU‐wide statistical data; statistical and econometric analysis of survey data; and a range of qualitative methods such as interviews with stakeholders, focus group, or Internet‐based public consultation. Yet, the CAP has changed considerably over the past decades, requiring adaptations of its evaluation toolbox. A detailed review of existing studies using economic experiments for designing and evaluating agricultural policies provides the backbone for a comprehensive assessment of the complementarity of experimental approaches with standard evaluation tools. Based on conclusions drawn from a workshop organized with experts, academics, and policy makers of Directorate‐General for Agriculture and Rural Development of the European Commission, the article further provides recommendations aiming at facilitating inclusion of economic experiments into the CAP evaluation toolbox. Cet article étudie la contribution potentielle des méthodes expérimentales pour l'élaboration de politiques agricoles fondée sur des données probantes, en considérant en particulier le cas de la politique agricole commune de l'UE (PAC). L'évaluation de la PAC repose principalement sur des outils standard tels que des modèles de simulation d'exploitations et de marchés agricoles, calibrés avec des données récoltées à l'échelle de l'UE; des analyses statistiques et économétriques sur des données d'enquête; et une série de méthodes qualitatives telles que des entretiens avec les parties prenantes, des groupes de discussion ou des consultations publiques sur Internet. Pourtant, la PAC a considérablement changé ces dernières décennies, ce qui nécessite d'adapter ses méthodes d'évaluation. Un examen détaillé des études existantes mobilisant les approches expérimentales pour la conception et l'évaluation de politiques agricoles permet d'analyser la complémentarité des méthodes expérimentales avec les outils d'évaluation standards. A partir des conclusions d'un atelier organisé avec des experts, des universitaires et des décideurs politiques de la Direction générale de l'agriculture et du développement rural de la Commission européenne, cet article propose en outre des recommandations pour faciliter l'intégration des approches expérimentales dans les méthodes d'évaluation de la PAC.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.204
Teacher spread0.171 · 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