Ceres2030’s new research reveals that donor governments must spend an additional USD 14 billion a year on average until 2030 to end hunger, double the incomes of 545 million small-scale farmers, and limit agricultural emissions in line with the Paris climate agreement. This means roughly doubling the amount of aid given for food security and nutrition each year, and must also be accompanied by an additional USD 19 billion a year from low- and middle-income countries’ own budgets.
Their innovative AI/ML topic classification and modelling tool led syntheses of 500k agricultural development evidence literature pieces coupled with multi scalar complex CGE economic modelling led by 78+ researchers, 23 countries and illustrious evidence board team led them to 10 donor oriented tightly coupled recommendations across 3 pillars (#EmpowertheExcluded | #OntheFarm | #FoodontheMove ) with scope to embed new /emerging research in near real time for effective and efficient policy synthesis by country, funding or intervention typologies among others.
The ground-breaking AI/ML led work prima-facie presents interesting scope for further enhancements in the directions of a)catalytic intervention modeling b) intervention templates mapping c) CGE scaling and parameterization to cater to various SD /country specific contexts d) SDGs correlation mapping and e) co-benefits modelling
Learn More at : https://bit.ly/3iUMZ7l