Public Policy and Rural Space: An introduction/Politique Publique et Espace Rural: Une Introduction
Notice bibliographique
Résumé
The objective in this Introduction is to present a broad conceptual framework within which the various articles in this special issue devoted to public policy and rural space tan be situated. Furthermore, since the articles deal with French territorial space, a brief discussion is given of the interest presented by the French, and more broadly the European Union, experience for readers of the CJRS from other countries, and particularly those from Canada. The articles do not treat all aspects of rural space and development, but are focused to a large extent on public sector policies, programs and institutions. This necessitates that we broach the issue of governance of development of rural areas. In focusing on rural space, it is important to situate rural space and the policies developed for them in their broader national contexts, a critical dimension of understanding the construction of rural space (see, e.g., Marsden et al (1993) and Benz and Eberlein (1999)). For instance, there are often contradictions in national policies for rural areas because of the overwhelming emphasis given to the metropolitan regions in many countries. Since a major preoccupation of regional and rural development is to reduce disparities between regions, the continued support given to metropolitan regions contributes to maintaining the disparities. First, a simple and broad conceptual framework is presented. This is followed by a discussion of the interest presented by the French and European contexts for North American readers and indeed readers from other continents and countries. Finally, a number of key themes are identified which relate to the broad subject area treated in this special issue, and these are linked into the different articles presented in this special issue. A Conceptual Framework The framework is presented in Figure 1. The population and activities of rural areas have been undergoing significant transformations throughout the 20th century. Urbanization and industrialization have modified the spatial distribution of population and economic activities in all countries. These transformations can be linked to processes of farm consolidation, mechanization, labour withdrawal from farming and generally the substitution of capital for labour. In other primary sectors, such as fishing, forestry and mining, similar processes have been in play, such as technological change and its impacts on labour demand, to which we can also add corporate restructuring and international competition, among other factors. [FIGURE 1 OMITTED] The processes have not been simple and different socio-economic systems of production have responded in different ways, meaning that rural spaces have not followed the same trajectories. Furthermore, other processes such as interregional and international competition and technological change have also created both opportunities and constraints for agricultural production, and for the other activities embedded in rural space, including new ones in some areas. The net result of all this has created a mosaic of rural spaces, as well as a whole series of externalities. Many negative externalities have been associated with these transformations, ranging from the loss of agricultural and rural population from some rural spaces to the negative environmental consequences of the industrialisation of agriculture (Bryant et al 2004). In relation to the negative or undesired consequences of many of these transformations, the public sector throughout the Western World has developed different forms of intervention through a myriad of policies and programs. Their goals have not always been coherent with each other. In the same country, policies and programs of different ministries and central State agencies have oftentimes been at cross-purposes as well. And, through all this, the role and functions of central States, and as well those of other levels of government, have been undergoing rapid change, more rapidly in some countries than in others (Bryant and Cofsky 2004). …
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,010 |
| Communication savante | 0,001 | 0,004 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».