Today has been a particularly good day. One of the days where I had a bit of freedom--meaning I didn't have a face-to-face meeting scheduled either in person or remotely. I like keeping my camera closed all day.
There are books to be read and more than a few presentations to finalize. Just like makeup over 50--less is more. I prefer to seed the ideas and then switch over to conversations.
I feel the same way about exploring categorical variables in spaces where we reflexively rely on numerics. What can they tell us about a population, community, or individual?
data & donuts
My business model is simple. When I am on the road I am listening to conversations around the halls of the National Press Club, Brookings Institute, and recently attended Applying Big Data to Address the Social Determinants of Health in Oncology: A National Cancer Policy Forum Workshop In Collaboration with the Committee on Applied and Theoretical Statistics.
When I am lucky enough to be working out of my home office I start most days with a morning run with Fred--my. hound. I queue up podcasts from a broad range of interests and arrive home filled with new "sprinkles".
I am waiting to share a full post as I am holding a workshop this week--you can sign up here Big Data on a Less Big Budget (meanwhile, I don't want to give away the goods) and speaking at Women In Tech Summit next week. But the serendipity of my chosen topic from the Tableau Fringe Festival and a common thread of data skill workshops was surprisingly realized in both the National Cancer Policy Forum and this morning's podcast from my 9-mile run.
The LSE Public Lectures are a dynamic series of timely topics where I am able to consider at length discussions around economics and political science serving about global discourse on a wide variety of topics. Today the discussion was around ordinal citizenship or even better--eigencapital.
I imagine this as an application of eigenvalues and vectors--"An eigenvalue is a number, telling you how much variance there is in the data in that direction, in the example above the eigenvalue is a number telling us how spread out the data is on the line."
My undergraduate students have been having a tough time understanding qualitative ordinal and nominal data types. I was gobsmacked and more than just a little interested to listen to a podcast on ordinal citizenship. I found it compelling and a novel foundation to introduce variable selection when measuring and defining relationships like poverty, race, and yes--even citizenship.
"As digital technologies have enabled a broadening of economic and social incorporation, the possibilities for classifying, sorting, slotting and scaling people have also grown and diversified. New ways of measuring and demonstrating merit have sprung up, some better accepted than others. Institutions, both market and state, find themselves compelled to build up and exploit this efficient, proliferating, fine-grained knowledge in order to manage individual claims on resources and opportunities.
This process, she argues, creates new social demands for self-care and individual fitness that possibly erode the universal and solidaristic basis upon which the expansion of citizenship historically thrived."Professor Marion Fourcade--London School of Economics (LSE) Public Lectures & Events.
But are we prepared to explore the social risk factors that influence patient outcomes beyond the type of care the patients receive?