Urban agriculture in northern and southern countries: A conceptualization of dynamics and challenges
Notice bibliographique
Résumé
According to the United Nations Organization, the world's population is expected to increase by more than 3 billion by 2050. This increase will take place directly on the space adjacent to the cities, A peri-urban area where agricultural activity is often dominated. Although the city and its neighboring countryside have always maintained good neighborly relations, it should be remembered that the horticultural belt has long been a source of nourishment for its city and that, as different researchers have pointed out, the master market gardener has played a fundamental role between the city and the countryside. The market gardener was "rural by his work" and "urban by his habitat and his corporate organization". Today, it is incontestable that this configuration has been upset. In the countries of the North as well as in the South, the inexorable progress of the city has nibbled away at the agricultural areas that are constantly receding. This has led to the loss of 32 million hectares over the period 2000/2001 to 2010/2011, according to a report of the Food and Agriculture Organization of the United Nations. Moreover, new relationships are born in these so-called peri-urban spaces, where new functions have been added to that which until recently dominated, i.e. agricultural production. Some researchers speak of "agriculture in the city's countryside" or of "urban countrysides". Indeed, the city and its various functions take root in the countryside and the simple dichotomy between rural and urban areas has tended to disappear around cities of the North, where peri-urbanization continues its work, and in the countries of the south it has accelerated. Agriculture thus has been regaining its original function of "nourishing its city", thus creating ties that had become somewhat reduced. In the countries of the North and the South, many initiatives are emerging in this urban fringe, where each segment of the population tries to take maximum advantage of the opportunities that can arise there. In relation to this, the problem is how the new modes of production of this agriculture (or rather of these agricultures) are apprehended in the countries of the North and of the South. Because of the numerous crises in the agricultural world in northern countries, today more than ever urban dwellers are more likely to want a healthy diet and to know the origins known. Examples abound in northern countries such as France, Canada, Switzerland (Food Guilds), and Belgium with its Solidarity Purchasing Groups for Peasant Agriculture. The challenges and issues associated with all these trends are the focus of this presentation.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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; un appel candidat d’une seule tête enseignante, 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 ».