Trust and Transparency

My most recent Qualia post:


I have spent the last couple of days trying to decide what I think about the most recent Wikileaks dump.  On the one hand, I think that transparency and a free press are vital elements of functioning democracy.  On the other hand, I do not have much confidence in the ability or willingness of our media and other social institutions to be nuanced in their reactions to the material.

My deepest concern related to this latest episode is that it will unnecessarily erode hard won trust among diplomats and politicians whose job it is to make the our planet a safer place to live (this concern is nicely captured in a recent TNR article by James Rubin).  Climate science experienced its own analogous brouhaha with the release of emails among prominent modelers.  The subjects of that leak did not always come off as particularly nice folks, but who among us does not have moments of lesser discretion?  And while the climate science has been vindicated, it is less clear that relationship between the scientific community and others has come away unscathed.

I have reached the following conclusions so far:

• each of us should all strive to be the best human that we can be, 
• each of us is indeed human and with that comes a set of foibles and flaws which brings a need for nuance and forgiveness in our trust building, and finally,
• well-deserved and robust trust enhances our ability to the create the communities we need in order to address the complex challenges that we face going forward.

On the demise of the Mean

Perhaps I should call this On the demise of the Normal.  More and more these days I encounter distributions where the median is a much better descriptor than the mean.  Of course if things are distributed normally then the median and the mean (and the mode) are all the same number.  But if things are abnormal then those definitions start to point to different parts of the distribution.

My first encounter with non-normal distributions came in graduate school as I was thinking about the distribution of elevations in topographic profiles.  Turns out that those things have a lot in common with power-law distributions.  So does the distribution of sizes of earthquakes.  And all sorts of other things in nature as well.  Then of course there were arguments about the differences between log-normal distributions and power-law distributions and how you might be able to tell in which was which by measuring things.  In the context here, it doesn't matter; neither one in normal.

I have been pondering this lately because I have been trying to write about proxies for the state of the human system part of the Earth system and central tendency indictors and variability around those have come up with considerable strength.  And now I am wondering if that most archetypal of all normal distributions - heights of humans - will stand up as normal over all of Earth.  Or does that example really only work in a suburban middle class classroom in the mid-1970s.

Which in turn makes one wonder whether in fact it is the normal distribution that is abnormal...

(ain't I clever!)