Effects on Competitiveness of Government Interventions in the Agri-Food Sector in Canada and the United States [A Conceptual Framework]
Notice bibliographique
Résumé
The scope of this project was limited specifically to addressing the impacts of government policies on competitiveness.It must be recognized that competitiveness is only one of a number of goals that should be considered in policy development for the agri-food sector.Many other socio-economic factors must be considered in the development of a comprehensive set of policies to serve the sector's and nation's best interests.Bracketed text and comments are not part of the draft report prepared by the contractor.The impact of various policy types on competitiveness is an important and timely issue none the less and is therefore the sole focus of this study. Method and ProceduresThe method and procedures undertaken to complete the study are outlined in Exhibit 1.1 which also illustrates the three streams which comprised the work plan.One stream involved the preparation of industry profiles to provide an overview of the Canadian and U.S. chicken and pork industries.The profiles were prepared on the basis of published secondary data which was analyzed and interpreted to determine the current structure and performance of the industry, changes in these over time, and likely future trends.These profiles provided background data for the assessment of policy impacts on the competitiveness of the Canadian and U.S. chicken and pork industries.[Profiles are not provided in this abridged version of the report.]A second stream of the work plan involved the identification of policy categories for the classification of policy instruments.Thirteen categories were defined and the policy instruments used in the Canadian and U.S. chicken and pork industries (i.e., the policy set) were classified into these categories.In addition, the relative significance of the policy categories was identified through the economic indicators: net benefits; producer subsidy equivalents (P.S.E's); and expenditures.The sources of policy instruments data were: the 1989 Net Benefits Results; the Hill and Knowlton Study of U.S. interventions; and published data used by the U.S.D.A. in estimating producer subsidy equivalents.Primary research into the specific instruments operating in Canada at the federal and provincial levels was required in order to obtain descriptions of the nature of these instruments so that they could be classified appropriately.In addition, primary research was undertaken to identify policy instruments for the chicken industry in the south eastern United States which was not covered by the Hill and Knowlton study.The core stream of the work plan involved the development and application of the analytical framework for assessing the relative impact on competitiveness of specific policy categories.The framework is composed of two elements: an economic theory perspective and a business systems perspective.The framework was applied to each of the thirteen policy categories.The economic theory perspective was analyzed by the core project team using a spatial equilibrium model with a homogeneous product and two trading regions.The business systems analysis included using a delphi team approach.The delphi team was composed of six agricultural economists (three in academic appointments in the United States and three in academic appointments in Canada).Each team member independently completed a detailed analysis of
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,012 | 0,014 |
| Communication savante | 0,013 | 0,002 |
| Science ouverte | 0,002 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».