Towards a just transition: enabling older populations to mitigate the impact of climate change and maintain wellbeing
Notice bibliographique
Résumé
<b>Background and Objective:</b> The COVID-19 pandemic demonstrated the vulnerability of older adults through the number of excess deaths across the globe. However, this finding has also demonstrates the importance of building resilience in older communities and has shown the strength, and capacity of older people although this varies widely across geographies, and social and economic determinants. There is now a need to re-imagine a response to social and environmental challenges as experienced and perceived by older adult populations. The ‘just transition’ is a reference to systems thinking required to engage and enable older populations and communities to de-carbonise, contribute to greener living solutions and participate fully in sustainable development of communities and cities, especially in relation to digital technology as an enabler to health and wellbeing. AGE-WELL is a unique Canadian network that brings diverse stakeholders together to develop technologies and services for healthy aging and the Advanced Wellbeing Research Centre (AWRC) in the UK is developing implementation method focussed on population health, wellbeing, and reducing inequality and the impact of climate change. Combining expertise and experience of both these internationally reputable organisations and its members, the aim of the workshop is to identify capability and assets for further transformative learning and research that recognise the environment as a prerequisite to living well in old age and is based on UN Sustainable Development Goals and ecocentrism. <br/><b><br/>Methods:</b> This workshop will use appreciative inquiry [AI] to identify assets through questions and dialogue that help participants identify how older populations engage through their communities, organisations, or households to understand the causes and consequences of climate change. AI is based on a recognised process (the 4D’s model) to enable constructive critical thinking and clarity about opportunities for social and policy development. Reference will be made through different scenarios, to climate change and climate shocks in the global south and to variation in social and economic determinants that differentiate older adult circumstance and environmental impact. <br/><b><br/>Results: </b>The workshop will identify a ‘minimum-specification’; a vision and set of principles by which researchers and public health professionals will engage with older populations and to identify mechanisms and outcomes for environmental and social sustainability. This can related to a range of continuing participation in communities and households and user need including health and care services. The outcome of the workshop will be shared across participants’ networks and published as an implementation strategy for research that implements the ‘just transition’ for and with older adults. We hope to foster academic networking and further academic collaboration on digital and technological development for population wellbeing. <br/><b><br/>Conclusions: </b>The workshop aims to contribute to support transformative transdisciplinary research that enables implementation and informs planetary and public health and wellbeing. The focus on assets and whole systems approaches that promote inclusion and participation are aligned to the minimum requirements for the social and environmental determinants of health alongside clean air, safe drinking water, sufficient food and secure shelter in old age.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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 ».