Previous week: Resources for workshop #2
Thanks @ekoner, unfortunately I will be only be on the call for the first 30mins. My day has become very full of meetings
No worries John, it happens!
Thanks for sharing the early childhood development data with me. I’ve added an Early Childhood Development folder to our shared drive. Please add your spreadsheet when you’re happy with it.
Early Childhood Development is a massive topic and the UK government seems to use the phrase “Early Childhood Development” when talking about “developing countries” rather than in the UK itself. So this makes it a little trickier to map the WHO definition to the UK context.
So my first thoughts are to pin down some of the WHO definitions and find corresponding charitable grants and statutory programmes that cover similar areas.
“Early childhood” is defined as the period from prenatal development to eight years old. So as a starting point, we’re looking for programmes that fund pre-natal, maternity, health (including nutrition and well-being), education (including preparing for school, school meals, and other support), and support for families with young children. I think this could include child poverty and safeguarding.
In the UK, some of this will be devolved (England, Wales, Scotland, and Northern Ireland) each running their own programmes. So you’re looking at statutory programmes from Public Health England (PHE), Department of Education (England), and others.
As it’s such a broad area with many stakeholders, you could try creating an ecosystem map of the stakeholders and the keywords they use to describe early childhood development in the UK. You’ve started that really well by categorising the grants you shared. Here’s a Child Well-Being Ecosystem Map created for St Louis, USA for inspiration.
So much for the future, what can you do this week? I think it’s interesting to add another category to your grants. This time of the funders: public bodies (e.g. big lottery), local / central government and charitable funders. Then sum up the amount awarded by year, category and type of funder. This should provide some interesting preliminary insight into how grants are changing over time.
Alternatively, sum up the amount awarded by your category to get an idea of how much is targeted to ECD, learning, etc. These are preliminary figures of course as there may be grants missing because we haven’t included those keywords in the search.
I think the ecosystem mapping will give you a good overview of the area, so ultimately may prove more useful. Summing up the grant money will give you some idea of outliers - especially where there is a lot or very little funding. This can help you narrow down areas to dig for more information.
The categories you’ve created could also be useful as a training data set to categorise other grants using machine learning. So great work overall! You’ve certainly picked an interesting and challenging topic!