Even if you are the least interested fan about the 2010 World Cup soccer tournament, you know that there were serious problems with the referees.  They made a lot of whopping bad calls that even the most casual of observers could spot.  What to do?

Nudge, baby.

1.  Add Referees.

2.  Add Technology.

3.  Increase Scoring.

4.  Redefine “Offside.”

5.  Rethink Penalties.

6.  Reduce Faking.

Really.

This is Nudging.  Those little things that make big differences.  Little things like adding more key personnel, changing primary rules, spending more money.  Subtle.  Nuanced.  Bright in a deep way.  Deep in a bright way.  Nudge.

And, not that there’s any bias in Nudge:

Consider the Consumer Financial Protection Bureau now being established. Above all, I’d urge the head of this agency to devise rules under the assumption that, someday, he or she will be succeeded by a nitwit.

Gee, the Obama appointee to this new Bureau (yet to be named and confirmed) won’t be a nitwit?

Nudge as Oracle!

I’ll probably lose my setting at the Cool Table for this, but I have access to the Nudge for Democrats in the November elections.  If you are a Republican or some other nitwit who isn’t voting for Democrats, stop reading this, otherwise Nudge Along!

1.  Add Democratic Voters.

2.  Delete Republican Voters.

3.  Hire Nudge Consultants.

All Bad Persuasion Is Sincere.

Persuaders Can Either Be Famous or Effective, But Not Both.

There’s a Difference between Persuasion, and Smoke and Mirrors; With Persuasion the Illusion Lingers.

The New York Times is reporting the tip of the iceberg.

Now a hard-nosed effort by the federal government to forge tougher advertising standards that favor more healthful products has become stalled amid industry opposition and deep divisions among regulators.

The Times even quotes a communication expert, so you know things are getting desperate.

“All of a sudden everything is dead in the water,” said Dale Kunkel, a communications professor at the University of Arizona who is an expert on children’s advertising. “I have heard no arguments to slow this down other than that the industry doesn’t like it.”

Even a former research partner is called for comment.

“With obesity rates the way they are, it’s no longer acceptable for companies to be marketing foods to kids that contribute to obesity and heart disease and other health problems,” said Margo G. Wootan, director of nutrition policy of the Center for Science in the Public Interest, an advocacy group.

How do those Evil Forces do it?  The Good People pass Good Laws then hand them to the Executive Agencies led by President Obama and what do those agencies do?  Nothing.  Clearly the Evil Forces have Evil Powers that Good People cannot yet overcome.

Or.

Passing a regulation is one of the least effective tactics for creating change.  Once Congress passes a law that describes regulation, relevant Federal Executive agencies must then begin to create and enact the regulation.  There is also a long public comment period as all citizens of the country voice their opinions and concerns about the regulation.  Agencies then meet among themselves and with Congressional staffs to discuss how to write the regulations in ways that do not contradict Congressional intent, coordinate with all affected Federal agencies, and will survive judicial review.  Change cannot happen overnight as reporters, academics, and zealots expect.  Government does not operate that way.

[Sidebar:  Every citizen should be required to follow the regulatory process for just one new regulation.  Create a Google alert that sends you a daily email with key terms like "regulation" "advertising" and "children" and read what you get.  You'll be tested over your comprehension and will be fined depending upon your score on the Race To The Top Regulation Education Test.  I mock, but you should spend 40 days and 40 nights in the Wilderness of Regulation.  You think you're tough.]

Eventually, a regulation will get implemented and then you will have the Deepwater Horizon oil rig disaster where a Federal agency led by an Obama appointee repeatedly cleared work standards as meeting relevant regulations.  And, then, you will have the public hue and cry on all sides of the issue, calling for more regulations and the circus will circle around on itself, a serpent eating its own tail.

Regulations tend to function more like informal norms of conduct.  When people internalize them, things change.  When people don’t, enforcement of regulations becomes a diverting game of “Gotcha; No, You Don’t” where everyone is Evil or Good, but nothing changes.

To my zealot friends who truly wish to make the world a better place and save people from themselves:  these Regulations will get written, implemented, and enforced.  Many years from now.  The problem you solved with these Regulations will have changed by then and the old Regulations will have no effect, so you can fight for new ones!  Along the way, you can receive grants, contributions, and contracts to study new solutions.

All Bad Persuasion Is Sincere.

It’s about the Other Guy, Stupid.

All People Resist Significant Change.

Power Corrupts Persuasion.

Great Persuaders Don’t Need Rich Uncles, Kindness from Strangers, or Third Party Vote Splitters.

And on and on.

If you really want to change people, get outside of yourself.  The way the Big Food and Big Tobacco and Big Oil and the Military-Industrial Complex and the true Change Agents do.  Regulation was invented to keep you looking in the mirror.

Among the many attributes the story of Shirley Sherrod, it stands as a strong example of Biased Processing, that High WATT Central Route approach that uses existing beliefs, expectations, and schema to understand Arguments, rather than following Arguments to conclusions.

On July 20, 2010, a conservative political website posted an edited version of a speech Ms. Sherrod had given to a meeting of the NAACP.  This posting rather quickly came to the attention of the Secretary of the Agriculture, Tom Vilsack.  He only watched the edited version of the speech and did nothing to obtain a copy of the entire speech.  Based in part on that edited version, Vilsack asked for and received Ms. Sherrod’s resignation.  Later, when Vilsack watched the entire speech, he changed his mind about Ms. Sherrod’s remarks, apologized for his hasty decision, and offered her a new job with the government.

Regardless of your political position on this event, I want you to focus on how people like Secretary Vilsack were thinking.  I see it as a clear example of the ELM Bias Process.  There’s no doubt that Vilsack was a High WATT seeker and processor of information about this event.  He moved quickly over the course of a few hours to reach his decision once he saw the edited clip from the political website.  He clearly sought information from other people about this event and had indirect contact with Ms. Sherrod through her supervisory chain.  There’s no evidence at all that Vilsack was a Low WATT Peripheral Route processor ambling along looking for spangly Cues.

Yet, you can also clearly see that Vilsack did not look for all relevant Arguments (for example, he didn’t obtain a copy of the whole speech before he sought Sherrod’s resignation) and he used an existing set of beliefs (the credibility of his Cabinet agencies) to interpret the Arguments contained in the edited speech.

One of the great persuasion problems for any person is trying to understand when you are Objective and when you are Biased.  While Objective Central Route processing does not guarantee you will find the persuasion “truth,” it is usually the best chance you’ve got.  Rarely does Biased Central Route processing lead you to a clear eyed understanding.  But how can you tell the difference between Objective and Biased?

The strongest indication is how self-relevant the issue or event is to you.  If the event cuts to the core of your identity, your strongest beliefs and values, chances are you are Biased and you will make Arguments fit your existing beliefs rather than following the Arguments where they lead.

Another way to see this is with the Rule, All Bad Persuasion Is Sincere.  I suspect that Mr. Vilsack was entirely sincere in this event and did not think strategically about it.  He thought he was on a Truth Mission even though this is clearly a political event which means there’s a ton of ambiguity, disagreement, and conflict in the event – reasonable people will take different positions.  An inSincere Persuasion approach rather than a Sincere Truth approach might have served Mr. Vilsack better.

When an event hits your hot buttons and moves you to Sincerity, be careful.

“This Time Is Different” is one of those marketplace oddities – a best selling book loaded with highly technical and specialized information that is difficult for educated readers who are not trained in economics.  But, nonetheless, the book is a large success.  I guess there are a lot more PhD economists in the world than I realized! Or more people who think they are just as qualified, perhaps.

One trait I admired in reading the book was the authors’ honesty.  They take great pains to constantly state the impoverished state of affairs in economics data.  They frequently lament the difficulty in assembling even weak economic data sets tracking relatively short periods of time.  They carefully assemble what they loudly acknowledge are incomplete, biased, and shaky samples of macro economic figures, then do a yeoman’s job in organizing and explaining them.

Now, what has this got to do with persuasion?

If You Can’t Count It, You Can’t Change It.

The authors of “This Time Is Different” clearly demonstrate that the reason economics is not quite as helpful as folks expect it to be is that we still Can’t Count It.  Despite the reams, piles, stacks, and heaps of economic data, data sets composed of long periods (hundreds of years) of well defined and consistently measured indicators across many nations simply do not exist.  In other words, we lack coherent big picture data sets.  Most often the authors are essentially creating proxy (my word) data sets for analysis – weakness they fully declare.

We face a similar problem with most other observational research areas like climate change, epidemiology, and various streams of evolution-based science as in psychology.  While there are seemingly huge data sets, they are not long term, comprehensive, randomly drawn and certainly not universal.  I’d argue that these cases exemplify my Rule, If You Can’t Count It, You Can’t Change It.  Bad counting doesn’t count and the authors of “This Time Is Different” are extremely careful about the bad counting and constantly warning about it.

You can tell my biases here.  Science is a helluva tool when you’ve got great methods and great data, but when you are reduced to convenience samples of proxy data drawn sporadically over time and place, the science is just not that good.  We need to keep looking and working for better science, for sure.  But, we need to be extremely careful about substituting bad science for good judgment in public policy and private choice.

You’ll know that economics has arrived when the next edition of “This Time Is Different” has a page with a model of variables (something like a structural equation model, if you’re familiar with that lingo), then a simple regression that shows model fit parameters with very large amounts of explained variance.  There won’t be so many tables and figures and charts, because the model will work so well, everything else is obvious.  If you peruse “This Time Is Different,” you will note a lot of numbers and charts, but no statistical analysis that shows models, estimates for parameters, and explained variance.

That’s Counting It.

P.S. Nice “Mad Men” touch with the book cover.  Does it help sales?

P.P.S. Why no reference to David Hackett Fischer’s “The Great Wave” historical analysis of inflation?

As July 8, 2010, the Senate race in California between the current Senator, Barbara Boxer, and her main challenger, Carly Fiorina, is, according to the headline . . .

Field Poll:  Calif. Senate race in statistical tie

And, here’s the statistical evidence: “The survey found 47 percent of likely voters support Boxer while 44 percent back Fiorina, a gap that is within the poll’s margin of error.”

Now, wait a minute.  Boxer has 47% and Fiorina has 44% which under the rules of basic math means that Boxer has 3 more points and thus wins the election, right?  Since when does a 3 point advantage mean we’re tied?

Most folks understand this and see the tie because of that phrase, ” . . . the poll’s margin of error.”  Margin of error in this instance means that if we had run another random sample survey, the results would have varied simply because of random variation in who actually picks up the telephone that day.  A different sample might have Fiorina ahead a point or two.  Thus, the race is in a statistical dead heat, a tie, even though the numbers actually show a difference that clearly points to one candidate over the other.

Another way of saying “margin of error” is to say that the results are not “statistically significant.”  Those two phrases mean the same thing.  And because the 3 point difference between 47% and 44% is within the margin of error, is not statistically significant, everyone understands that even though there is a numerical difference between 47 and 44, it should be understood as a tie, as no difference.

Okay?

Now, here’s where it gets tricky.

The evidence about climate change shows the same characteristics as this opinion poll.  Let me requote Dr. Phil Jones, lead scientist at East Anglia:

And he said that for the past 15 years there has been no ‘statistically significant’ warming.

Now, of course, the past 15 years is the McGuffin in the Global Climate Change argument and shows up in the famous hockey stick graph, reproduced here.

When you look only at the graph, everyone sees that dramatic upturn in temperature on the right hand side.  Looks serious, but as Dr. Jones asserts, that hockey stick increase is “within the margin of error” or “is not statistically significant.”  And just as we know that as of July 8, 2010, the Senate race between Boxer and Fiorina shows no real difference, we know that there’s no real difference in global temperature over the time period of this graph.

If you take the time to read the research studies that form the basis for much of the furor, one statement you almost never see in them, is “statistically significant.”  Or, if you do see that phrase, the criterion for testing significance is set at an easier standard (p < .10) rather than the textbook standard (p < .05).  While the graphs and figures look compelling, the numbers are not.

And, as I’ve documented in this blog, many scientists have an awful skill at mathematics and will make claims about their research that are not supported by their own data.  For example, almost all of the research on warning labels for calorie counts shows no statistically significant effects, yet warning labels for calorie counts are now apart of Health Care Reform We Can All Believe In.  What this means is that in the next couple of years you will see no change in the waistline of America even though scientists asserted warning labels make a difference.

The fact that scientists are making these advocacy assertions does not change reality.  I’m sure you can find petitions with scientist signatures in favor of warning labels, just as you can find petitions with scientist signatures in favor of carbon emission restrictions to reduce global warming.  The fact is, most of them can’t count past ten without taking off their shoes as those petitions prove.  The research they cite contradicts them and they can’t see that because they cannot count.