Focusing Research To Support an “Appropriate Unrigging” Agenda By Getting Beyond Symptoms

If I am right that our change strategy has to be based on understanding how Trump voters and potential Trump voters think about the term “rigging,” then we need to be doing research that shows how and why the system is rigged, and for whom.

My own personal feeling that much of the problem is that research, after currently being mediated through the media, ends up reporting on symptoms, but not on causes and dynamics.  For example, the recent numbers on suicide, health and life expectancy in declining counties did get widely reported, but I bet they made it through as just that, leaving the impacted population to fill in their own “low information” explanations, that probably focused on external threats, (drugs and foreign competition), rather than lack of opportunity caused by American corporate decisions, lack of health care caused by Republican de-funding, etc. (That hypothesis in itself would make a fascinating research project)

While we can not reshape the media, at least in the shot term, I fear, we can start to do research that focuses not so much on the symptoms, but on government and corporate behavior, with symptoms as only the afterthought, and with analysis of the mechanisms of the impact that causes those symptoms.

We should be conducting focus groups and testing messages that are specifically not about getting short term support for specific changes, but getting insight into people’s understanding of underlying dynamics and finding what would disrupt or replace those understandings.

For example, this paper from the FTC on big data raises many questions about the possible discriminatory and exclusionary impacts of big data.  I would suggest that these impacts might include pricing policies that have discriminatory impact on the declining county areas, others that make it harder for people from those areas to apply for jobs, or even get health care assistance online.

So the research needs to be about the direct line from the corporate behavior, in this case the use of big data, to the impacts that the population of those areas feel.

An economist would say these big data techniques help make markets even more perfect.  Others might experience them differently.  The point is for research to provide the information and does not allow victims to be set against each other.

 

If We Knew What People Meant by “Rigged,” Perhaps We Could Then Show Who Was Doing the “Rigging”

When I blogged about the need to do focus groups to understand what people really meant when they said the system was “rigged,” and what were the examples that proved to them that this was so, I fogot to make the most important point.

If we know what they mean, then we can show that maybe they are misled as to who is doing the rigging, or at least taking advantage of it.

An example from the Washington Post raising the very real possibility that Trump son-law Kushner got into Harvard because shortly before admission his dad gave a $2.5 million donation.  Not the only example, I would venture to guess.

 

The Key Question for Pollsters and Focus Groups –What Do You Mean by “Rigged”

Obviously, the belief that “the system is rigged” not only resonated strongly in this election cycle, but was extremely powerful.

It was brilliantly powerful in getting people to vote against their interests.

But the thing we have to do to lay the ground work for a better political alignment is to understand what people actually think they mean by the phrase.  More importantly, we have to find the way to communicate the truth about how it is “rigged” in a way that is true, that appeals to a wide a variety of current perceptions, and that will build support for true “un-rigging.”

Here is a list of some of the things that people think when they respond to the phrase.

“I no longer get the help I used to.”

“Government is helping people who are not like me, and not helping me and people like me.” (Five Star Euphemism Alert)

“Government is helping banks and companies to take away from me.”

“I pay more than my share of tax and get nothing for it.”

“Nobody listens to me and my friends.”

“Government helps bad people.” (Four Star Euphemism Alert, but could refer to corporate malefactors.)

“People in government are just out for themselves.”

“Nobody helps the people who need help.”

“The system is run by people very different from me who want to impose their values on me and make me do things I do not believe in.” (Three Star Euphemism Alert.)

“Money gets you everything.”

I am sure I am missing lots of important ones — please add in the comments.

After identifying the generalizations that appeal, then we need to look for the indicia that people use — what do they see that convinces them of these generalizations.

Once we understand what is going on, then the “Trump Monitoring” can be focused on what will disabuse people of their allusions and help them develop better understanding.  In other words, first we find the facts that counter not so much the generalizations(those get explained away), but the facts that counter the believed facts that support the generalizations.  That is harder to ignore.

Of course, some of the generalizations are true.  The lessons from those are far harder, because we have to develop policies and examples that make them untrue.  That’s going to be the real challenge for the coalition.