Your mission - an informed vote

Governing the body civitas is the most important thing that we, in our role as citizens, do. And it is important that each of our individual decisions be well informed. Soon, Massachusetts citizens will decide on a slate of representatives and settle several ballot questions, the latter an exercise in direct democracy.

When selecting a governmental representative, you must decide which candidate best represents your interests. This is, unfortunately, often involves holding one’s nose and voting for the least bad choice (a topic for another day). But ballot questions constitute pure democracy. Here, instead of selecting a representative and trusting her or his judgment, you make the call. The only way to responsibly do so is to be well informed.

Your choices are simple. The first one is whether to vote at all.

In the recent primary election, only 16% of registered voters turned out to vote (this may account for the nose-holding factor). In the upcoming general midterm, perhaps 40% will cast a ballot. Think of what this means if you choose not to vote.

Imagine a random group of ten citizens, strangers, having coffee at Morin’s. Four of them have decided to vote in the upcoming election and six won’t bother. If you are one of the six, you are in effect telling the four “Whatever you decide, I’m fine with it. I’m putting my family’s well-being in your hands.”

That’s your right as a citizen, but it may not be optimal. Why would you give four strangers unchallenged sway over your family’s welfare? A better alternative would be to inform yourself and cast your ballot.

Ah, but there is the rub, the “inform yourself” part. For if you don’t fully understand the issues and likely outcomes, how can you vote intelligently? Voting for a poor outcome out of ignorance is, perhaps, worse than not voting at all.

The Commonwealth has recognized the importance of voter information and, in the case of ballot questions, has provided a voter guide. This guide  provides a summary of each question, the effect of a yes or no vote, and arguments written by proponents and opponents. The Commonwealth hastens to establish that these arguments are only opinions. You, dear voter, must still assess what you think to be the truth. The Commonwealth may inform, but you must decide.

Let’s take Question 1 as a case in point and attempt to wend an objective path through the countervailing opinions.

First, the facts. Facts should be identified as incontrovertible and not subject to interpretation.

• The current fuel (gasoline and diesel) tax in Massachusetts is 26.5 cents per gallon.
• Section 1 of chapter 64A of the General Laws requires that the tax per gallon be adjusted annually by the percentage change of the Consumer Price Index (from the preceding year) with a lower limit of 21.5 cents per gallon (should the CPI decline)
• Question 1 would strike the requirement that the gas tax be automatically adjusted

Let’s take a look at key points in the arguments. First, in favor:

“Voting yes simply stops the linkage of the gas tax to inflation.” Given the facts, this statement is true.

“This initiative cuts no money for bridge or road repair.” This one is a bit slippery. No, the initiative does not decrease the current 26.5 cent levy. But assuming that the CPI increases, it would reduce the funds automatically available in future years.

 Now the opposition:

“Question One threatens the safety of you and your family when traveling on Massachusetts’ roads and bridges.” This is loaded with assumptions, the foremost being that the legislature will not meet its obligation to maintain public infrastructure, whether by raising taxes, raising fees, or shifting resources to do so.

“A Yes vote would make things even worse, by taking away existing gas tax revenues that we need to solve this public safety crisis…” No, the initiative would not reduce existing tax revenues. It removes the automatic increases. The legislature is free to vote for future increases or reallocation of funds as noted.

Reading between the lines, we can summarize the two positions thusly:

The pro-Question 1 camp feels that the legislature should take affirmative action to provide funding for roads and bridges, and that each such decision should be subject to a vote. Taxation with representation is a sound policy, but there are many precedents for automatic increases. (When has your property tax remained flat year to year?)

The anti-Question 1 group thinks that the legislature will not provide adequate funding by vote and that automatic increases are the way around this problem. But if the legislature is failing, did the voters choose their representatives well?

What’s the right choice? It’s completely up to you. But this is the approach you must take to each of the questions. Inform yourself, think about it, read between the lines, then make your decision. And the miracle of democracy is that, whatever the outcome, the people generally tend to be right.

Spurious Correlations and Dr. Alice Stewart's Triumph

Shoe fitting by x-ray (fluoroscope)

Who says statistics are dry and boring? Tyler Vigen, a Harvard Law student, recently created a fun website called Spurious Correlations. Tyler pokes fun by finding sets of numbers which, by random coincidence, are related. He notes, for instance, that the total number of US Political Action Committees is strongly related to the number of people who die by falling out of a wheelchair. Or that the number of people who have died from being tangled in their bedsheets tracks the total revenue generated by US ski facilities.

Amusing nonsense. And proof positive that correlation does not prove causation. In other words, that two sets of data are correlated does not mean that one causes the other.

The word comes to us from Middle French and means "related together." Two sets of measurements or data that track each other are correlated. Statistically, a relatively simple procedure can be applied to theses sets resulting in a relationship measurement (correlation coefficient) that ranges from -1 to +1. A coefficient of 0 means that the two sets of data are completely unrelated, i.e., none of the changes in one set can be explained by changes in the other. Coefficients of 1 show perfect correlation, the sets of data change in lockstep with each other. (-1 is a perfect inverse relationship, +1 a perfect direct relationship).

Ice cream cones purchased when compared to outdoor temperature forms a strong direct relationship: as temperatures increase, purchases of ice cream likewise increase. As men increase in age, the number of hairs on their head decreases; this is an inverse relationship and, unfortunately, is strongly correlated.

People are quick to tell you that correlation does not prove causation, usually when they disagree with the findings of some study. And they are correct; as Vigen demonstrates, coincidental correlations are not rare.

But as an informed citizen, you must be aware that correlation is a powerful data analysis tool used in fields ranging from health studies to astrophysics to economics. When two sets of numbers are correlated, statisticians do not jump to the conclusion that one causes the other, but rather are put on alert that deeper analysis is called for. Correlation is not proof, but it directs the investigation.

Such as the investigation performed by Dr. Alice Mary Stewart which ultimately saved millions of children the scourge of childhood cancer.

To set the stage, you must realize that radiation and x-rays, discovered in the 1890s by Marie Curie and Wilhelm Roentgen, were considered miracles of the modern age. The danger of exposure was not fully appreciated, and radiation was used in the twentieth century for such applications as illuminating watch dials, fitting shoes, and viewing a fetus in the womb. All were considered safe.

But Dr. Stewart was on a quest to explain a rash of lymphatic leukemia and other childhood cancers in England. Her own godchild died of the disease which drove her interest.

Dr. Stewart and her team conducted a study of 203 English public health hospitals during 1953-1955, looking for details of all children who had contracted cancer. The study included a questionnaire filled out by each mother.

From this mass of data, Dr. Stewart and her statistician, George Kneale, searched for patterns, looked for correlations. And they found one. It turns out that the children of mothers who had had a fetal x-ray were twice as likely to contract leukemia as those who had not had an x-ray. The finding was stunning, and rejected. After all, that radiation was safe was settled science. And Dr. Stewart was, after all (sniff), only a woman.

But she, and Kneale, persevered. Their working relationship was interesting. Whenever Stewart proposed a conclusion, Kneale would apply all of his substantial statistical skill to prove her wrong. This was their method and it made her results stronger as she defended them against stout attacks.

It took nearly twenty years, but Stewart and Kneale amassed a growing dataset of 22,000 childhood cancer victims in which the use of pre-natal x-rays was increasingly complicit. Finally, in the late 1970s, the American and British medical societies accepted Dr. Stewart's findings and recommended that pre-natal x-rays not be routinely performed.

Two lessons here. First, correlation does not prove causation, but it is often a smoking gun begging for deeper analysis.  And the other - share your conclusions and data, welcome challenges, and defend them with logic and reason. Do not dismiss another's theory just because she doesn't share your prejudices.

And now, dear citizen, you know more of correlation than most do.