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Enregistrement W820979917

Network of Cities Tackles Age-Old Problems: Jane Parry Investigates How Cities around the World Are Catering for the Explosive Growth in the Number of People Aged over 60

2010· article· en· W820979917 sur OpenAlexaboutno aff
Jane Parry

Notice bibliographique

RevueBulletin of the World Health Organization · 2010
Typearticle
Langueen
DomaineHealth Professions
ThématiqueGlobal Health Care Issues
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGovernment (linguistics)UrbanizationEconomic growthPopulationPacePARRYChecklistSocioeconomicsSociologyGeographyPsychologyDemography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The world's population of people aged over 60 will double from 11% in 2006 to 22% by 2050. Even more dramatic will be the growth in the number of the very old. Between 1950 and 2050, the number of people over the of 80 will grow from 14 million to 400 million worldwide. At the same time, the pace of urbanization continues unabated: by 2030 an estimated three in five people will be urban dwellers. All levels of government are starting to realize how important the demographic transition says John Beard, director of the Department of Ageing and Life Course at the World Health Organization (WHO) in Geneva. People have been struggling for a number of years in knowing how to respond. WHO's Age-friendly programme gives them something tangible as a way to address these trends. The programme encourages leaders in cities as diverse as New York and Nairobi to think constructively about how to improve life for older people, a process that has the potential to enhance city life for everyone. To this end, in 2006, representatives from 33 cities in 22 countries met and examined eight areas where cities might influence healthy ageing: outdoor spaces and buildings, transportation, housing, social participation, respect and social inclusion, civic participation and employment, communication and information, and community support and services. [ILLUSTRATION OMITTED] Following the meeting, a guide and checklist were produced for cities to use to assess their age friendliness. Involving older people in assessing age-friendliness and identifying measurable indicators to demonstrate progress ensures it's not just a feel-good exercise says Beard. The next step was the establishment of the Global Network of Age-friendly Cities, which connects participating cities from around the world. The network gives member cities access to technical support and training from WHO, as well as the opportunity to share information and experiences. When a city joins the network, it commits to an initial five-year programme. In the first phase it needs to establish mechanisms that involve older people; conduct an assessment of the city's age-friendliness; develop an action plan and measures that will show if it is making a difference. It then has three years to implement its plan and demonstrate its progress. If the city wishes to stay in the network, it must show continuous improvement through cycles of implementation and evaluation. A distinguishing feature of the network's approach is the way that it extends far beyond the traditional sector. We see healthy ageing as being inextricably linked to an individual's social context, rather than social context being just a factor that affects health says Beard. Remaining socially engaged is just as important a component of an older person's as the absence of diabetes. We're hoping to get information through the network on what cities have learnt, what are best practices, what challenges they faced and whether or not they found solutions explains Simone Powell from WHO's Department of Ageing and Life Course. Cities can serve as role models and show that some of the achievements may not cost a lot. Unsurprisingly, many measures that make a city age-friendly also make it friendlier for other groups; outdoor seating, accessible public toilets and pedestrian crossings timed with slow walkers in mind also benefit pregnant women, carers of small children and people with disabilities. The programme team has been contacted by many additional cities that are now initiating age-friendly city projects, such as Donostia-San Sebastian in Spain and Berne in Switzerland. In other countries, national initiatives are emerging. France, for example, has 30 cities signed up to its National Programme on Ageing. The concept has taken off in Canada and Ireland and WHO is also talking to China's National Committee on Ageing about a scheme that might help more than 400 million Chinese citizens who will be aged over 60 by 2050. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,012
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,105

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,012
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0050,002
Communication savante0,0040,009
Science ouverte0,0030,007
Intégrité de la recherche0,0050,009
Charge utile insuffisante (le modèle a refusé de juger)0,0310,010

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.

Tête enseignante Opus0,033
Tête enseignante GPT0,324
Écart entre enseignants0,291 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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Même revueBulletin of the World Health OrganizationMême sujetGlobal Health Care IssuesTravaux en français237 207