Sunshine List 2021

The Ontario government has released The Sunshine List. It is a publically-avaialable list which lists the names, positions, and locations of any government employee earning over $100K per year, and was started in 1995 by the Mike Harris government as a way of naming and shaming those who commit the sin of earning above six figures. The article that appeared in today’s Toronto Star had a picture of an elementary school teacher and a classroom of young children, just below the headline, to suggest the targets of this list.

However, the list targets all 240,000 or so full-time government employees who get a paycheck from Queens Park, regardless of the sector of government invloved, such as Public Works, Healthcare, the ministries, OPG and the LCBO. And that just scratches the surface.

The 26 top wage earners working for school boards are those earning more than $250K. All of these people are school board directors, and the occasional associate director. When compared against the other sectors of government, the education sector is still the lowest-paid as they always have been. So it is no surprise that the sector called “School Boards”, according to the Sunshine List, are have the lowest average salary, for those earning above 100K.

The reality of such perceived largesse is twfold: the list which started in 1996 has become less impressive in its impact than it had been back then. $100K today has the same buying power as a salary of $69,769.70 back in 1996.

There is also taxation, which eats up $35,000 of your $100K gross earnings. The money you earn is not what you take home. And in 1996 dollars, the take-home pay of $65K can buy you what $45K used to back then. You can still live more or less comfortably and relatively debt-free on that salary, but it is far from lavish, especially if you live in the Greater Toronto Area because you won’t be able to afford a house or even a condo. An earner taking in $70,000 back in 1996 could buy a home in the GTA. Nowadays, an employee in the GTA earning $100,000 is lucky if they can find a two bedroom apartment that doesn’t break their bank account, especially if they are raising families.

Because of this, the magic number of $100,000 is outdated and much less meaningful than it used to be. It was a lot of money in 1996, but nowadays is barely above a living salary for a family of 4. It only looks big because of all the zeroes after the 1. To match the buying power of $100,000 in 1995, you would need to earn about $160,000 today.

The other aspect of this, is that the 85% of earners on the Sunshine List are earning between $100,000 and $110,000. 70% of earners on the Sunshine List are earning less than $105,000. That means that the per centage of earners just between $105K and $110K is barely 15% of the distribution. And as you go up in salary, the number of earners in each successive bracket falls like a rock. Also, keep in mind that the list isn’t giving you who is earning what, below $100,000. But because it takes a school teacher 10 years to get to that level, it is a safe bet that most Ontario government employees earn well below $100K, even in today’s dollars.

If we use $160,000 as the new cutoff (based on the same 1996 standard, adjusted for inflation), there are exactly 765 earners in Ontario working for school boards earning that either 160K or more, none of whom are teachers. That level of salary is generally earned by school board superintendents and the occasional principal. The 765 education sector earners is far fewer than the 80,434 sunshine earners working for school boards. There are many calls to update this list to take into account the change in standard of living of Sunshine earners, but as you can see number less than 1%, the list would not have nearly the same impact, nor cause anywhere near the same outcry.

And I have to say, why the outcry? We live in a world where Amazon workers are fired for being in the bathroom too long, thereby being a drain on Bezos’s ambition to buy himself another rocket. We live in a world where the average CEO earns more than 300 times more than the average worker under him. Government workers got where they were because of union activity, and out of the recognition that the boss wasn’t going to be nice one day and give us a living wage. The ones who don’t form unions get the shit jobs and shitty lives they duly fought for.

I realize I am being sardonic, but I am also suggesting that fighting for a living wage and adequate benefits is not easy, and is always a struggle, and bosses are hired to care more about profits than whether your skill set matches what earnings you deserve, whether you are taking home a living wage, or even your mental or physical health. Where is the outrage at the CEOs of private companies who earn so much off the backs of their employees? Or even at private companies who form government “partnerships” which benefit off the largesse of the taxpayers? These latter people are invisible on the Sunshine List.

People lose their minds when a government employee earns a living wage, but don’t seem to have a problem when a CEO reports a salary at a shareholders’ meeting in the billions of dollars, don’t know what to do with all that money, and buy themselves a rocket. Meanwhile their employees are so stressed they are unable to hold down a warehouse job for longer than a year or so, lest they be sacked for the crime of taking a bathroom break in an actual bathroom rather than peeing in a bottle like a good employee. This is what happens when you don’t fight for better working conditions.

To the left is a summary of salaries above 100K paid to all employees in the School Board sector of government. This encompasses all managers, custodial staff, secretaries, teachers, psychologists, other specialists, and board office employees right up to the director. Nearly everyone earns below 110K, with the number of earners in each successive bracket falling precipitously as you go up in salary level. With the full list sorted in order of salary, it is possible to determine the median salary for a School Board Sunshine List employee (remember, not all government employees) as being $103,129.16 or, in 1996 dollars, $65,411.73, using data provided by the Toronto Star to do the conversion.

Below is a breakdown by government sector.

A Career Postmortem: Dr. Brian Wansink

Dr. Brian Wansink. Photo courtesy of Wikimedia Commons.

Being formally trained as a Food Scientist in my undergrad years, I had heard about Wansink’s 2006 book Mindless Eating, and became an admirer after reading the book. Because I was a casual reader, I made no effort to “look under the hood” at any papers and studies he might have referred to, and took him at his word as a then-executive director of the Center for Nutrition Policy and Promotion for the US Department of Agriculture (USDA). He was responsible for overseeing the design of the 2010 Dietary Guidelines for Americans, as well as the government-run nutrition site “My Pyramid.gov”. He was also a long-time director of the Food and Brand Lab at Cornell University. With all that under his belt, why would I question what he writes?

The book Mindless Eating has inspired many to be more active and deliberate in managing their nutritional cues, and to take a deeper look into how humans are hard-wired in their perceptions of food. The real strategy would be to find ways to work around these hard-wired perceptions, rather than against them.

The ways he would run his experiments — mostly on college-aged subjects attending Cornell — was that he would offer free food (what college student wouldn’t be attracted by that?). Once you are hooked by the free food (and sometimes a movie), the science kicked in. Plates and food packaging would be weighed by difference in a way that the subject never knew it was being done. They would get a fairly accurate calorie count that way. Then they would ask you about your own perceptions: How much did you think you ate? How many calories did you think you consumed? Depending on what was being investigated, the results when fed back to the participants were often remarkable and surprising. Some of the perceptual tricks in the design of the experiments even fooled graduate students in Dietetics. He showed that these perceptual tricks can be as simple as changing the size of the plate.

Dr. Wansink seemed sly, and clever. But he had to be, because humans can sometimes be even more sly and clever in fooling themselves into thinking that they ate less than they did. The world clearly needed someone like Wansink to expose our human frailties to ourselves, and to show us how we fool ourselves into eating more than we planned to, or than we thought we did.

Two-Buck Chuck comes in many varieties, including red and white.

In Mindless Eating, among his many tales, he discusses people’s perceptions of their meal based on the perceived vintage of the wine they were served. The investigators purchased several cases of the cheapest wine possible, Charles Shaw Wine, nicknamed “2-Buck Chuck”, a wine sold at a chain store called Trader Joe’s in United States. At the time, Charles Shaw Wine could really be purchased for two dollars (USD). All bottles had their labels removed and replaced with a fictitious label suggesting it was from California, and another label suggesting the wine was from North Dakota, a state not known for making wine. The patrons given the various wines with their meals were asked to rate the food (not the wine) they were served and asked whether they would come back. The reaction was far more favourable if the label on the bottle suggested California wine. It was a bit of a sly trick, but at least the 117 diners in the study had a prix fixe all-you-can-eat gourmet meal set at $21.00 (USD), with free wine.

There was another story Wansink likes to talk about, about the bowl of tomato soup that was filled from the bottom using a food-grade feeding tube that was invisible to the participant. The tubing led to a 2-gallon pot containing the soup. The participant seemed oblivious to the bowl of soup that would never empty. The finding here is that people will eat on average 73% more soup than a normal serving if there is no visual cue to tell them to stop eating.  Our stomachs are indeed a very crude instrument for measuring how much we have eaten. We need visual cues, which can be interfered with by the bottomless bowl, but also by regular distractions. This experiment aimed to prove that. For this experimental design, Wansink received the IgNobel prize in Nutrition in 2007.

IgNobel prizes are awarded to scientists whose research makes people laugh, then makes people think. These prizes are awarded by the publication Annals of Improbable Research (AIR), and handed out at an annual ceremony held at Harvard University in Cambridge, Massachusetts, with lectures from the prizewinners being given across town at MIT.

Wansink showed how our perceptions of food quantity is vulnerable to lighting; the presence of company or entertainment or other distractions; the size of our plates; the shape of our drinking glasses; the proximity of junk food from where we happen to be sitting; and so on. All of it was compelling and often headline-grabbing. He has been on interviews about his findings from all 3 major American television networks over the years.

He was apparently able to prove his findings quantitatively, but any graduate students using his findings are now better apt to check his numbers. No one has accused him of fraudulent research, just sloppy research with statistical calculations that didn’t match up with other reported numbers. It began with a now-deleted blog post where, according to The Cut,

Wansink told the story of a Turkish Ph.D. student who came to work in his lab for free. “When she arrived,” he wrote, “I gave her a data set of a self-funded, failed study which had null results (it was a one month study in an all-you-can-eat Italian restaurant buffet where we had charged some people ½ as much as others). I said, ‘This cost us a lot of time and our own money to collect. There’s got to be something here we can salvage because it’s a cool (rich & unique) data set.’ I had three ideas for potential Plan B, C, & D directions (since Plan A had failed).”

Wansink wrote glowingly about the Ph.D. student, Ozge Sigirsci, and in her ability to see the offer of data as an opportunity and get herself published. And that she did. Five papers bylined both by Wansink and Sigirsci, came out of this “failed study”. To grad students reading the blog and wanting their own work published, this raised eyebrows. He was suggesting that it was just fine for a scientist to take a failed study, then massage the data for different null hypotheses until they come up with a correlation that falls outside of a 95% confidence interval, which rejects the null hypothesis (Ho). This is science done backwards. You usually pose the hypotheses before the experiment is run, not after. In other words, a scientist doesn’t run an experiment without knowing what they are researching beforehand.

The kind of statistical error being committed in these papers is known as a “Type M Error” (“M” stands for “Magnitude”). This is where just because you found a correlation with a 5% margin of error, the effect of this statistic might be exaggerated. Remember, this result was stumbled upon as a side effect of slicing and dicing the data until a correlation of “anything” emerged. In that context, how much information is your data giving you that rejects the Ho, which came as more of an afterthought?  It would be better to run a modified experiment to see if the same thing happens when you run the experiment deliberately.

In the blog, Wansink then listed the papers that were published and where they were published. This gave readers 5 key papers to be sceptical about. And there was a research team who did the checking. Tim van der Zee​, Jordan Anaya​, and Nicholas Brown looked into 4 of these 5 papers, and found 150 statistical errors. The error findings were based on inconsistencies in the published tables without looking at the raw data. To look at the raw data, a scientist normally needs to ask the scientist who ran that experiment. It didn’t help that after repeated requests, Wansink refused to share his data with van der Zee, et. al., to settle the matter.

Now, there is no rule saying that he has to share his data. But to paraphrase Andrew Gelman in the blog Statistical Modeling, Causal Inference, and Social Science, there is also no rule saying that anyone in the scientific community needs to take him seriously, either. The various journals have, since 2017 retracted at least 18 of his papers, according to Wikipedia. Another 15 have been formally corrected.

Stanford determined in September, 2018 that he had, according to Science Magazine from 21 September, 2018:

“In a statement issued [on the 20th of September], Cornell’s provost, Michael Kotlikoff, said the investigation had revealed “misreporting of research data, problematic statistical techniques, failure to properly document and preserve research results, and inappropriate authorship.”

Wansink was removed from researching and teaching activities at Cornell, according to Science. Wansink also resigned after this statement was issued.