Uncategorized – RE-DESIGN

COVID-19 and mobility around the world

Published by demetriodor on February 2, 2021

2020 has been a crazy year with unprecedented changes in what we do, where we go, and how much time we spend at home. The Google Community Mobility Reports data provides a great resource for tracking changes in mobility since the beginning of 2020 in various countries, provinces and cities around the world. But the data is not easy to use in order to compare changes in mobility between different places. That’s why I built two interactive web applications that allow the user to select the countries and time periods of interest, and get directly a plot comparing the trends. Moreover, I coupled the mobility data with data from the Oxford COVID-19 Government Response Tracker to show the impact of policy changes on mobility. The first app compares countries around the world. The second one compares Dutch provinces. I update the apps when new mobility data becomes available. Comments and feature requests are welcome.

The origins of the digital universe

Published by demetriodor on March 27, 2013

Just finished Turing’s Cathedral – a fine and stimulating book about the origins of the computer, the interlinked history of the first computers and nuclear bombs, the role of John von Neumann in all that, the Institute of Advanced Studies (IAS) in Princeton, and much more. It is a very thoroughly researched volume based on archival materials, interviews, etc. Actually, if I have one complaint it is that it is too scrupulous in presenting the background of all primary, secondary and tertiary characters in the story of the computer and in documenting the development of the various buildings at the IAS. For that reason I found the first part of the book a bit tedious. But the later chapters in which the author allows his own ideas about the digital universe to roam more freely are truly inspired and inspiring. It was also quite fascinating to learn that one of the first uses of the digital computer, apart from calculating nuclear fusion processes and trying to predict the weather, has been to run what would now be called agent-based modeling (by Nils Baricelli). Here is my favorite passage from the book: ‘Books are strings of code. But they have mysterious properties – like strings of DNA. Somehow the author captures a fragment of the universe, unravels it into a one-dimensional sequence, squeezes it through a keyhole, and hopes that a three-dimensional vision emerges in the reader’s mind. The translation is never exact.’ (p.312)

After Google Reader

Published by demetriodor on March 15, 2013

As you might have heard already, Google slashes Reader. That’s terrible news since I have based a very large part of my internet experience on Google Reader: not only following blogs, but collecting links, catching up with general news, and even keeping up to date with academic journals. For some insight into why Google dumped the Reader read here. There is a good discussion of alternatives RSS platforms here. Let’s hope a new and better feeder will soon appear to fill the gap. Postscript: There is a petition to save Google Reader which already has close to 100 000 signatures here. Post-postscript: And I thought I am pissed…

Hyperlinks

Published by demetriodor on December 21, 2012

Philip Tetlock on political forecastingInterview with Pearl on causal inferenceBrian Jones on the possibility for change in American gun (safety) policyFights over evidence in medicineThe Mayan Doomsday’s Effects on Survival Rates

Intelligence and Politics

Published by demetriodor on November 27, 2012

“Intelligence can let you solve harder problems, but some problems are just resistant, and you get to a point that being smarter isn’t going to help you at all, and I think a lot of our problems are like that. Like in politics – it’s not like we’re saying that if only we had a politician who was slightly smarter all our problems would go away.” Peter Norvig, director of research in Google, Guardian

Explanation and the quest for ‘significant’ relationships. Part I

Published by demetriodor on February 17, 2012

The ultimate goal of social science is causal explanation*. The actual goal of most academic research is to discover significant relationships between variables. The two goals are supposed to be strongly related – by discovering (the) significant effects of exogenous (independent) variables, one accounts for the outcome of interest. In fact, the working assumption of the empiricist paradigm of social science research is that the two goals are essentially the same – explanation is the sum of the significant effects that we have discovered. Just look at what all the academic articles with ‘explanation’, ‘determinants’, and ’causes’ in their titles do – they report significant effects, or associations, between variables. The problem is that explanation and collecting significant associations are not the same. Of course they are not. The point is obvious to all uninitiated into the quantitative empiricist tradition of doing research, but seems to be lost to many of its practitioners. We could have discovered a significant determinant of X, and still be miles (or even light-years) away from a convincing explanation of why and when X occurs. This is not because of the difficulties of causal identification – we could have satisfied all conditions for causal inference from observational data, but the problem still stays. And it would not go away after we pay attention (as we should) to the fact that statistical significance is not the same as practical significance. Even the discovery of convincingly-identified causal effects, large enough to be of practical rather than only statistical significance, does not amount to explanation. A successful explanation needs to account for…