Consider this observation from Charlie Cook, a noted political observer and commentator.  He’s analyzing the Obama Administration’s struggles.

. . . And then when unemployment numbers started proving to be much, much tougher and it started becoming more clear that the stimulus package hadn’t worked properly, they just kept plowing ahead on health care. And this isn’t a communications problem. This is a reality problem. And I think they just made some grave miscalculations and as it became more clear that they had screwed up, they just kept doubling down their bet.

The interesting question here is to understand why Presidents make grave miscalculations that smart observers can see, but they cannot, then exacerbate their problems with a double down bet on the miscalculation.  We could frame this problem in other terms:  When people suffer for their choices, then tend to love that for which they suffer.  Dissonance, in other words.

Now, quickly and of course, this tentative hypothesis is not restricted to the current occupant of 1600 Pennsylvania Avenue.  Remember Mr. Bush’s miscalculation with that War of Choice in Iraq.  And, Mr. Bush certainly doubled down following his suffering from that miscalculation with the Surge.  That was, dissonance, too, right?

As outside observers, we can see the Suffering of Presidents for their Miscalculations and when we are correct, dissonance and the pursuit of its reduction is likely a strong explanation.  Why do Presidents persist in their miscalculations?  The suffering caused by the miscalculation causes dissonance, an unpleasant psychological state, and is removed by loving the source of the suffering even more which then motivates doubling down.

Of course, the analysis depends not on what the Presidents are doing or thinking, but rather upon the accuracy of our assessment of Miscalculation, Suffering, and Doubling Down.  Only the most impervious zealot argues today that Mr. Bush’s bet on the Surge failed.  Most see the Surge as the success that made following success more likely.  So, was Mr. Bush merely in the throes of dissonance when he doubled down and is supremely lucky that the Surge worked?  That’s what a dissonance analysis would support.  Or, did he simply see the problem in a different light and make the Surge as a rational solution that might actually succeed?  That’s just smart decision-making.

We should think the same way about understanding President Obama right now.  If we’re right – he Miscalculated, Suffered, and is now Doubling Down to more failure – then maybe dissonance is at work here.

But, can’t he just be rational rather than dissonant or even foolish?  He thinks his policies are Good Things and is trying to make Them happen.  Maybe his analysis of Goodness is flawed, maybe his political skills are weak, maybe his opponents are stronger, and maybe he’s like Terry the boxer in On The Waterfront, and tonight is just not his night (at 3:50 in).

All this turns on another persuasion concept, Attribution, stated in a nice turn of phrase:  Where you stand depends on where you sit.  Like Charlie Cook, we are not sitting in the President’s chair looking at the problem.  We are sitting around at our computers, perhaps in our underwear, looking at the guy in the President’s chair.  We conclude that Obama is an idiot, doubling down on a miscalculation when, if we were wearing a suit and sitting in that chair, we’d probably be doing the same damn thing, realizing that it’s always going to be a Close Run Thing that cannot be avoided.

Shocking news!

The Insurance Institute for Highway Safety released a study of vehicle crashes that compared states with laws banning cell phone usage while driving to states without such laws.  Even if you don’t know much about history or time series statistics, if you just look at the figures in the report, you can see the Headline:  the Laws Have NO Effect.

Everyone is baffled.

“Absolutely, we were surprised by these results,” says Adrian Lund, president of IIHS and HLDI.

“The study raises as many questions as it answers,” says GHSA executive director Barbara Harsha.

Before we get into the merits of the case, just think about the science and the persuasion behind all of this.  We cannot randomly assign drivers to different conditions, most importantly here, cell phone usage, then observe what happens.  The absence of control is fatal to the quality of the science and the inferences we can confidently draw.  Yet, smart people persistently believe in the Observational Research Tooth Fairy and so we get Laws and Regulations, Nudges and Nags from well intentioned folks who say more than they really know; the sign of FauxItAll.

Worse still is the unscientific orientation of many researchers in Observational Research.  Most strain to confirm a hypothesis and design data collection and analysis to find anything that supports the hypothesis and almost never actively pursue disconfirming evidence.  There’s nothing wrong with entertaining alternative explanations, unless, of course, you already know the true answer and you’re just trying to convince the yokels.

Now, take uncontrolled Observational Research, a confirmation bias, and then add Small Effects and you’re ready for disappointment.  You don’t need an Excel spreadsheet to tell you that traffic accidents are extremely rare events compared to the amount of total driving and further that people drive and talk A LOT and that accidents while driving and talking are also extremely rare events compared again to the total.  Thus, people drive A LOT, but rarely have accidents; people drive and talk A LOT, but rarely have accidents.  The difference between Driving+Phones versus just Driving is a Small Effect.

Thus, we have the commonplace Perfect Storm for failure.  People using science as persuasion in their use of Observation, avoidance of contrary evidence and explanations, and those small effects.   Now, put that persuasion to work in State legislatures and you’ve got Laws and Regulations that produce no effect.

There is no doubt that conversation produces cognitive load and hence distraction for drivers.  Whether on a cell phone or just yackety-yak with a passenger, mere talk requires mental effort and capacity.  It’s just not that important for vehicle crashes.  There is a clear break in the scientific chain of effect between the obvious distraction and the actual wreck.  People tried to draw a straight line from distraction to crashing when it is clear from these data that there are intervening steps and processes that mitigate the distraction.  Nobody looked for those intervening steps.

It’s rather like the silly FDA and Food Police efforts with various kinds of warning labels – whether portion size, calorie count, any other information.  They expect that Warning Labels like this will cause people to eat less and lose weight as if a Warning Label functions like a double-wrapped strip of duck tape over a hungry mouth.  It doesn’t, it won’t, and it can’t.

But, if you’re doing FauxItAll science, nothing else matters.

Here’s Mr. Obama pitching persuasion for health care reform on October 6, 2009.

And, here’s Mr. Obama six months later pitching persuasion for health care reform on March 3, 2010.

Ohhh.  I get it.  The blue scrubs make all the difference!

Get yourself in the mood . . .

Persuasion loves the heat.

Uncertainty?  Fear?  Confusion?  Peithos lights up, “Is someone calling my name?”  The Ancient Attendant prepares for affairs of the heart or affairs of the state.  It’s all the same, you know.

Science loves the light.

Uncertainty?  Fear?  Confusion?  Galileo smiles, returns to the lab and breaks the problem down, step by step until knowledge replaces ignorance.

Except today.  Science has a new companion, Persuasion.  And Science won’t go anywhere without Her, especially in Public.

. . . perhaps Fever at a higher pitch . . .

Need Persuasion for the Science of Health Care Reform?  Let me show you how to spend one trillion dollars to reduce mortality by 1% and make people think we’ve Fixed It.

Need Persuasion for the Science of the FDA?  Let me show you how mandatory menu calories counts will produce a 30 calorie reduction and fool people into thinking it is the End of Obesity as We Know It.

Need Persuasion for the Science of Global Warming?  Here’s how you hide statistically insignificant data in a pretty chart to convince the People.

Need Persuasion for the Science of Selling News?  Here’s how you market Science to people so they get all that great knowledge you’d have to suffer through in lectures, labs, and libraries, but without that annoying peer review.

. . . or Fever with the King . . .

Great times for Peithos, my friends, and it’s only going to get better.  The last time Science came courting like this was during the Clinton Administration.  Democrats are smart people in case you haven’t talked with one lately.  You don’t even have to ask; they’ll tell.  Especially the progressive ones.  You know, the ones that use Science to inform Policy.  Here, it’s good for you.  Trust us.  We’re smart.

Peithos loves them the best.  Progressives don’t mind throwing Science overboard in a storm when you need to lighten the load.  Is the data messy, complicated, and inconsistent?  Pitch it and use this simple chart.  Results disconfirm the original hypothesis?  Let me adjustment myself in private and we’ll call it Post Hoc.  Got folks who disagree?  Frame them as Deniers.

Don’t worry about the Science.  Persuasion will fix that.

. . . that’s all there is . . .

Imagine two health care reform plans.

The first one will save 275,000 lives over 10 years.

The second one will lower the annual US death rate from 811 deaths per 100,000 people to 802 deaths per 100,000 ( 0.00811% to 0.00802%).

Which is the better plan?  It’s obvious.  The one that saves 275,000 lives, right?

Consider this:

There will be a cost in lives, too. Mr. Pollack’s organization estimates that as many as 275,000 people will die prematurely over the next 10 years because they do not have insurance.

While 275,000 is a large number of people and you and I would prefer to not make this list over the next 10 years, what does the number mean?  Let’s go High WATT on it.

Turns out that the two options I gave you at the top of the post are equivalent.  Whether you say it is 275,000 over 10 years or a change from 811 to 802 per 100,000, you are describing the same amount.

So, why don’t the researchers in the NY Times story use the rate style (811 versus 802)?  It’s obvious.  The change is ridiculously small.  Gee whiz, let’s spend nearly a trillion dollars and move the death rate from 811 to 802.

Even 27,500 doesn’t sound that big, so pump it up to a ten year total and now we’ve got a Scary Number.  275,000 deaths is a lot of dead people to those of us who count on fingers and toes.

Yet another way of saying “275,000 over 10 years” is to say, “27,500 a year.”  In 2006, the last year that the CDC has final statistics, it claims that 2,426,264 Americans died.   Thus, the annual number of “27,500″ is just a little more than 1% of the annual death total for 2006.

One percent.

Thus, the most favorable estimate of the mortality impact of health care reform is a 1% improvement.  In Windowpane terms this is one tenth of a Small Effect (a 45/55 effect).  Now, we are talking mortality, so it is serious.  But one tenth of a Small Effect?  For a trillion dollar investment over the same time period? And given how very small the Effect Size is and how it was figured, isn’t it possible that it would actually be even smaller?

But, you obscure High WATT thinking and analysis when you persuade with numbers like this.  Combine very small effects over long time periods and make a big deal about the Total, but not the Accumulation.  It is an effective persuasion play because it looks like a serious, High WATT Central Route examination of the Facts, but really it is a Cue, a Peripheral Route shortcut that makes you the reader think you are Serious and Well Informed, when you are just the Target for an Advocate.

Remember:  All Bad Persuasion Is Sincere.

Okay.  The oceanography guys called the Chilean tsunami wrong.  They made dire predictions of killer waves and then the tide actually ran out in some locations.  So, they should have said nothing?

“It’s a key point to remember that we cannot end the warnings. Failure to warn is not an option for us,” said Dai Lin Wang, an oceanographer at the Pacific Tsunami Warning Center in Hawaii. “We cannot have a situation that we thought was no problem and then it’s devastating. That just cannot happen.”

And that false choice between either saying nothing or else exaggerating is exactly the wrong belief to hold and yet entirely characteristic of the Expert.  As I’ve recounted numerous times in this blog, Experts in one area tend to think they are Experts in communication, persuasion, or behavior change as if those things are the easy part compared to Molecular Genetics, Advanced Global Concepts, and now, Wave-ology Studies.  Without criticizing the science (and that’s another issue), I can confidently assert that Dai Lin Wang and other oceanography experts I’ve read in the past day or two know next to nothing about the communication problem they face.

You see their ignorance in that false choice they perceive.  Either we don’t say anything (and make no public errors in our science or our communication) or we exaggerate (to save the foolish public from themselves).  Consider other options.

Just say exactly what you know.  If you know something to the decimal, nanosecond, or angstrom, then say it that precisely.  If you know something with a confidence interval a mile wide and a day long, then say it that with that range.  Say what you know and stick to that.  If someone asks for more precision, repeat your original warning and add that is the best science can do right now.  Above all, do not exaggerate the claim in the name of communicating risk to stupid people.

If a scientist cannot do this or something similar, then hire someone to the team who can.  Please consider the limitations to your Expertise.  You do know what you know, but you do not know what you are doing here.

Listen, scientists.  This is exactly how climate change science got into the public mess it now faces.  Scientists did not stick to their science.  They assumed more expertise in areas they clearly lacked.  Just do your science.  That’s the best thing you bring to the world.  Your science.  Just do that.

Remember the Rules.

If You Can’t Succeed, Don’t Try.

You Cannot Persuade a Falling Apple.

Consider this Figure from the IPCC (through the Wall Street Journal), the UN climate change panel that is driving the international conversation on policy.  If a problem can be fairly expressed in one Figure, this is it.

All you see are the colored lines in the middle of the Figure that meander like Old Man River until 1900 when they take off like a rifle shot with a couple of ricochets in 1950 and 1995, but then return to a trajectory that looks like escape velocity from Planet Earth.

Houston, we’ve got a problem!

A persuasive problem.  Those colored lines draw your eyeball, your attention, and your evaluation.  Zig-zag, zig-zag for thousands of years, then the rocket shot.  Just follow the colored lines . . . like Homer Simpson.

Now, let’s turn up the light a bit and make that gray background more noticeable.  Didn’t really see it, did you?  Of course not.  It’s designed to read like Background when it is actually Foreground.  That dull, plain, and unimportant gray contains the most important Numbers in this Figure, but the IPCC hid that from you to Simplify the data.

Notice two important perceptual qualities about the gray mass.  First notice how wide it is, especially compared to the range of the zig-zagging lines.  The lines essentially are the mid point of Old Man River while the gray background is the banks of the river.  Thus, the Old Man River of global temperature is wide and wanders mightily.

But, second, now note how no colored line at any time ever jumps the banks of the river’s width anywhere.  In scientific terms this means that the wandering of the lines across all points and all times is within the Random Variation or the banks of Old Man River; the lines never jump the banks of Old Man River and that means there is no scientific evidence of any temperature change in the last one thousand years this Figure displays.

Any one trained in statistics can see the mean variation of the colored lines never exceeds the 95% confidence band of the gray background.  Unless one chooses to be Fooled by Randomness and find meaning in the tea leaves, the best scientific data we have shows all that zig-zagging is just the normal variation of Old Man River.

And the IPCC hid that fact in plain sight which is always most persuasive.  Make the Favorable Argument Obvious and make the unFavorable Argument Plain.

I’ll give the IPCC credit as persuaders.  They understand the Rule:  All Bad Persuasion Is Sincere.  There is an obvious lack of sincerity when you persuade with statistics like this.  However, since the IPCC bills itself as a scientific unit, I’d have to caution them on another rule:  All Insincere Science Is Bad.