THIS EVENT HAS BEEN POSTPONED. NEW DATE TO BE ANNOUNCED SOON.
Thank you for your interest and sorry for any inconvenience caused.
This webinar for the UN General Assembly and New York Climate Week will present results of a major survey of G20 countries by Ipsos MORI commissioned by the Global Commons Alliance and partners.
About this event
In August, the Global Commons Alliance and Ipsos MORI published a major survey on attitudes to planetary stewardship and transformation among G20 countries. Findings include:
1. Three in four people are aware Earth is approaching tipping points.
2. 83% of people in G20 countries want to do more to protect nature.
3. 74% of people support a shift towards “wellbeing economies” that prioritise health, wellbeing and the planet above profit.
4. People in emerging economies are more willing to do more to protect the global commons than those in the wealthiest economies.
This is just the tip of the iceberg. The survey provides rich detail on attitudes to: the media, the pandemic as a transformative moment for society, and the costs and benefits of action to protect our global commons. Join this one-hour event for a deep dive into the data.
Speakers:
Bridget Williams, Research director Ipsos MORI
Sophie Thompson, Research executive, Ipsos MORI
Owen Gaffney, Global Commons Alliance (Earth4All and FAIRTRANS)
The analysis comes at a critical moment as nations discuss climate and biodiversity goals. The survey provides a richly detailed picture of public attitudes across G20 countries, including the UK, United States, Brazil and China. The results give leaders a strong mandate for bold action. The results will be presented as part of activities around the United Nations General Assembly and New York Climate Week.
Who should join?
- NGOs
- International organisations
- Media
- Policy and public attitudes analysts
This event is in partnership with Earth4All and FAIRTANS.
Read the full report: https://globalcommonsalliance.org/wp-content/uploads/2023/11/Global-Commons-G20-Survey-full-report.pdf