Urban Health and Healthy Cities Today
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Notice bibliographique
Résumé
Abstract The authors of this article purport that for current understanding of Healthy Cities it is useful to appreciate other global networks of local governments and communities. In a context where the local level is increasingly acknowledged as decisive in designing and implementing policies capable of tackling global threats such as climate change and their health-related aspects, understanding how thousands of cities across the world have decided to respond to those challenges appears essential. Starting with the concept of “healthy cities” in the 1980s, the trend toward promoting better living conditions in urban settings has rapidly grown to encompass today countless “theme cities” networks. Each network tends to focus on more or less specific issues related to well-being and quality of life. These various networks are thus not limited to more or less competing labels (Healthy Cities, Smart Cities, or Inclusive Cities, for instance), but entail significant differences in their approaches to the promotion of health in the urban context. The aim of this article is to systematically typify these “theme cities.” A typology of “theme cities” networks has several objectives. First, it describes the health aspects that are considered by the networks. Are they adopting a systemic perspective on all health determinants, such as Healthy Cities, or are they focusing on “hardware” determinants like Smart Cities? Second, it highlights the key characteristics of the networks. For instance, are they pushing for technological solutions to health problems, like Smart Cities, or are they aiming at strengthening communities in order to mitigate their detrimental effects, like Creative Cities? Third, the typology has the potential to be used as an analytical tool, for example, in the comparison of the results obtained by different types of networks in urban health issues. Finally, the typology offers a tool to enhance both transparency and participation in the policymaking process taking place when selecting and engaging in a network. Indeed, by clarifying the terms of the debate, decisions can be made more explicit and achieve a greater level of congruence with the overall objectives of the city. Indeed, Healthy Cities today need to make alliances with other theme networks, and this typology gives the keys to find which networks are the “natural best allies,” avoiding mutually harmful antagonisms. In that sense, the typology developed should be of interest to any actor involved in health promotion at the city level, whether in an existing “theme cities” policy process or as willing to participate in such a program, and to scholars interested in better understanding the main drivers of “theme cities” networks, a rapidly growing field of study.
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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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,003 |
| 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 découle