mono-layer crisis?

Is the national debate about suicide in South Korea, in spite of economic growth, a symptom of media-promoted single-layer thinking that greater emphasis on the value (and challenge) of niche-network layer-multiplicity might help out with?

data & models paired

Are folks tempted in the quantitative sciences to present too much theory sans observation, reflected e.g. implicitly in this recent article? This counterpoint on poorly designed high school tests suggests a need for more robust content at the high school level as well.

One fix may be to introduce inverse (algorithm-selection) challenges in parallel with the usual forward (algorithmic-reasoning) challenges. In other words, give students data to measure and interpret while they are also learning the models used to predict what's going to happen, so they at least know there's a science of choosing (as well as of using) models in the subject at hand.

This would help close the loop on concreteness, and call into play complementary skills that deserve attention during the crucial period in which students are deciding their major. Our NanoScience Practicals course is example of a cross-disciplinary offering designed to explicitly confront students each week with new data, as well as with topic-specific concepts & models.

This is also consistent with recent requests in the biological sciences for the development of better principle-based as distinct from informal reasoning skills. The importance of principle-based tools for selecting models is perhaps even more obvious in life-science than in physical science areas.

amazing humans

Prairie dog barks about foxes afoot may be a timely reflection of danger, but who would pretend that reality is a pale shadow of their bark?

exciting possibility

Prokaryotic microbes are the ideologues of the cell-biology world, in that they express their amino-acid codes willy-nilly.  The eukaryotic cells of multi-celled organisms, on the other hand, are cell-biology's experts at model-selection, having learned to inform the codes that they express to the traffic in their organism's bloodstream.

Microbes will survive long after our sun makes this planet inhospitable for metazoan life.  However, without the chance to evolve... (i) intra-organism circulatory-systems, (ii) regulated gene-expression and hence (iii) multi-celled life as we know it, the story of planet Earth would (I think) be much less interesting. 

Electronic-communication networks open up the possibility of intra-community idea-expression, i.e. the use of organization-internal ideastreams on the level of pairs, families, communities, & cultures as well as worldwide.  Should we seize this opportunity to become experts at model-selection on the level of idea codes, or shall we follow the example of ideologues who will likely be here long after our electronic ideastreams dry up?

bovine bents

It's easy to imagine that large mammals capable of domestication, in context of their preference for a hierarchical social structure as discussed by Jared Diamond in his book Guns germs and steel (W. W. Norton, 1999), might be preoccupied with royalty (e.g. their selection as savior, or their behavior as distraction) even if that meant ignoring issues that were impacting tens, thousands, or even hundreds of thousands of closer community members.

I'm sure glad we don't act like that...

the answer to...

..."What's the most important question?" is often not "How do we answer the obvious?" but rather "In what terms can the problem be most simply addressed?".

In math, this is the challenge of finding the right variable. In science this is the inverse problem of selecting a model given observational data, as distinct from the forward problem of prediction with model in hand.

The forward problem is easier to do and to teach. Moreover ability to solve it has survival value, so it's no surprise that ideologues abound in all walks of life.

As a result we may spend too few neurons implementing (and developing) ways to choose our questions with care. According to Sharon McGrayne's The theory that would not die (Yale University Press, 2011) there is a whole science of model selection for making the most of limited data.

This science, namely Bayesian inference, has a spectacular track-record of practical problem-solving. There is also a long tradition of idealogue disinterest.

Even today methods for idea-selection in a given field oft fall through the cracks of higher ed, in spite of their relevance to everyday life. That's the way things work, so expect it & adapt e.g. with ways to compensate for this tendency.

quality of life tests

News of the day tends to focus on one layer of organization at a time, whether it be e.g. public health, family life, the state of the economy, or cultural beliefs.  When you are only thinking about one layer at at time, it's often easy to cartoonify things in terms e.g. of good guys and bad guys.

Life's quality of course involves simplification, but it also involves subsystem-correlations that look in and out from the physical boundaries of skin, family and culture.  Folks who are greedy on one layer (e.g. in their job) may be acting prudently on another (e.g. for their family).  Hence multi-layer thinking about community health is more likely to be about the balance between different (and sometimes competing) perspectives than it is about good versus bad.

How can we: (i) track what we can know about the health of all six of these correlation layers, and moreover (ii) use that information to optimize quality of life across the board?  This might make for some fun (and constructive) regional competitions in the process.