Category Archives: Research Blogging

Do New Stadiums Lead to an Increase in Business?

Unless you’re familiar with the literature in this arena (no pun intended) or you know about Betteridge’s law of headlines, the title of this post is actually still an unresolved question for you. Well, I won’t delay the inevitable: according to research published earlier this year, the answer is no — new stadiums do no lead to an increase in business.

There are two things I want to talk about as it relates to this research. The first is Richard Florida. If this area is an interest of yours, there’s a good chance that you’ve come across him. Florida has been a professor for the last 20+ years and has written extensively on cities. Here’s a post I found from him within the last year that talks about the very thing that the journal article discussed:

The overwhelming conclusion of decades of economic research on the subject is that using public funds to subsidize wealthy sports franchises makes zero economic sense and is a giant waste of taxpayer money. A wide array of studies have shown that professional teams add virtually no income to local economies. In fact, some of them find that large subsidies actually have a negative effect, taking money out of the local economy. Aside from the jobs generated by actually building the stadium, most jobs inside the stadium—selling food and beer or working at team concessions—are low-paying temp jobs. It’s even worse for football stadiums, which are used for games at most a dozen times a year, and maybe a few more times for concerts or large events. Public economic development dollars can be put to much better use on things besides subsidizing sports teams and their wealthy owners.

Ultimately, the burden of public subsides falls disproportionately on small cities that are the least able to bear the cost. For example, a $200 million public subsidy for a new stadium ends up costing a small city like Santa Clara roughly $1,650 per resident, compared to just $50 a person for L.A. And, of course, teams in bigger cities, with their bigger markets and more revenue, often do not need subsidies at all.

The reason I raise Florida’s name is because I was surprised that I didn’t see his name mentioned in the journal article. To be fair, I don’t think that Florida has done any primary research in this domain, but I would have thought that even in the opening introduction or literature review that there may have been some reference to Florida’s constant discussion of literature like this.

Anyhow, the second thing I wanted to talk about is something that might not be measurable. Well, it might not be measurable in a simple way. As a former amateur athlete, I have a special place in my heart for sports. Certainly, there are plenty of things that one could classify as “wrong” about sports, but part of me still wants to defend it/them and I’ll be upfront: that might be part of what’s going on with this section of this post.

Something I didn’t see in the article (and probably something I wouldn’t expect to find in any well-written article) is a measure of (or discussion of?) the positive externalities that result from a city’s team winning the championship or even the spillover effects from the possible positive externalities. Now that’s a tortured sentence. I’m talking about how the residents of a city feel after their team wins the championship (in a given sport). Naturally, not everyone would be watching (or care), but for those that are fans of the team that wins, there would certainly be elevated levels of joy and happiness immediately following the victory. If there were studies done on this, I suspect that there might be comparisons to those who have won the lottery in that a couple of months after, lottery winners return to a similar level of satisfaction/happiness that they had prior to the lottery win.

I wonder, though, could we measure the economic gains for a city from this positive externality and the resulting spillover effect (in this case, let’s say the spillover effect would be the “pay it forward”-ness of joy from the fans of the team to the non-fans that the fans will be interacting with in the weeks following the city’s team’s victory). Even if there is a tangible effect that can be measured, I’m sure that any reasonable cost-benefit analysis would still conclude that a new stadium isn’t worth it for a city.

ResearchBlogging.orgHarger, K., Humphreys, B., & Ross, A. (2016). Do New Sports Facilities Attract New Businesses? Journal of Sports Economics, 17 (5), 483-500 DOI: 10.1177/1527002516641168

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Positive Stereotypes Are Pervasive and Powerful

Pop quiz: hands up — how many of you think positive stereotypes are OK?

I suspect that for many of you, your first reaction may have been, “well, yeah, they’re positive, right?” I can totally empathize with that shortcut, but consider this excellent quote from Gordon Allport, one of the “founders” of personality psychology: “People may be prejudiced in favor of others; they may think well of them without sufficient warrant,” [quote excerpted from journal article cited below].

Last year, researchers sought to summarize some of the research about positive stereotypes. There were a number of interesting findings. For instance:

Among [a] sample of Asian American students, the majority (52%) had negative reactions (e.g., feeling marginalized) to their group being considered the “model minority” compared with 26% who had positive reactions. […] Although the subjective favorability of positive stereotypes may facilitate their expression among perceivers who intend them as “compliments,” the targets of such stereotypes can feel depersonalized as if they are being acknowledged exclusively through their category membership. [Emphasis mine]

So, while it might be a ‘positive’ stereotype that Asian Americans are considered the “model minority,” it’s possible that an Asian American may feel as if they are being depersonalized when having the stereotype directed at them. That is, they may no longer feel like they’re a person, but rather that they simply belong to this category called “Asian American.”

Let’s back up for a moment.

When I talk about stereotypes in my lectures to students, one of the first things I do is explain the mechanics of a stereotype. Our brain is processing way more stimuli than we could possibly fathom. For instance, in your office right now, do you hear the hum of the lights or the sound of the fan? If you’re on the bus or in a car, do you notice the sound of the brakes? How about at home… do you still hear the creaky sounds of the floorboards or the plethora of sounds that come out of the basement/vents? I suspect the answer to many of these questions for most of you will be no and that’s because you have habituated to them. Your brain has recognized them as non-threatening and moved on to focus on other stimuli — people.

There are so many people on the planet. Really, we could say that there are over 7 billion different kinds of people, but that’s impossible for a brain that’s trying to process as much as it can. So, when you meet people, your brain is busy trying to recognize patterns that it can map onto previous people you’ve met. When everyone’s brain does this, it follows that a thing called “stereotype” emerges. That is, a stereotype is our brain’s way of trying to find a shortcut for understanding the different kinds of people we interact with during our lives.

So, in the example above about Asian Americans, somewhere along the way, someone’s brain decided Asian Americans represented what they believed was a ‘model citizen.’ Forgetting for a second whether this is valid, it’s likely that there were other people’s brains came to this conclusion and so the stereotype is perpetuated.

Just because our brain is doing this in the “background” doesn’t make it ok. As humans, there are so many biases that we have to be aware of when making decisions — our brain taking shortcuts with stereotypes is just one of them. So, what can you do?

Well, as I often say when it comes to biases — the first step is awareness. You’ve gotta recognize that you’re falling prey to stereotyping and once you recognize that you’re doing it, I urge you not to be so hard on yourself. Let’s be clear — I’m not giving you a “pass” for stereotyping, no. But the culture from which you derive can have a lasting effect on your beliefs about people (which inform whether you employ stereotypes).

One quick and easy way to awareness — if you’re ready for it — is Harvard’s Project Implicit Test. I did a quick search and I was surprised that I’ve only mentioned this one other time in the last few years on this site and it was only in passing. From their site:

Psychologists understand that people may not say what’s on their minds either because they are unwilling or because they are unable to do so. For example, if asked “How much do you smoke?” a smoker who smokes 4 packs a day may purposely report smoking only 2 packs a day because they are embarrassed to admit the correct number. Or, the smoker may simply not answer the question, regarding it as a private matter. These are examples of being unwilling to report a known answer. But it is also possible that a smoker who smokes 4 packs a day may report smoking only 2 packs because they honestly believe they only smoke about 2 packs a day. Unknowingly giving an incorrect answer is sometimes called self-deception; this illustrates being unable to give the desired answer.

The unwilling-unable distinction is like the difference between purposely hiding something from others and unconsciously hiding something from yourself. The Implicit Association Test makes it possible to penetrate both of these types of hiding. The IAT measures implicit attitudes and beliefs that people are either unwilling or unable to report.

If you’re ready for the results, I strongly suggest you take the test.

ResearchBlogging.orgCzopp, A., Kay, A., & Cheryan, S. (2015). Positive Stereotypes Are Pervasive and Powerful Perspectives on Psychological Science, 10 (4), 451-463 DOI: 10.1177/1745691615588091

Black Players Were Held to a Higher Standard After Jackie Robinson Broke the Colour Barrier

In (unintentionally) keeping with one of the themes from the last post — let’s talk about baseball after Jackie Robinson broke the colour barrier. Most people will tell you that even after Jackie Robinson broke the colour barrier in 1947, black players had to be that much better than white players before they were given a chance to play. Having not been alive in 1947, many might take the word of those that were. However, we don’t have to! Let’s take a quick detour.

In the mid-90s and especially the 2000s, sabermetrics began making its way into the fold. In short, sabermetrics is a more sophisticated way to analyze baseball statistics. From Fangraphs:

Sabermetrics is about trying to evaluate the sport more accurately. For decades, statistics like home runs, runs batted in, batting average, wins, and earned run average were all we had to determine which players were good, which were bad, and which were in between. But as gathering, collecting, and sharing information became easier, a group of baseball teams and analysts started to develop statistics that were slightly harder to track and disseminate, but ones that were a much better reflection of talent or performance.

The most obvious example of this is the difference between batting average and on-base percentage. A walk is a positive outcome for the batter, and while it isn’t as valuable as a single or a double, it is much better than making an out. Batting average completely ignores walks, meaning that it is failing to capture important information about the hitter. Beyond that, batting average and on-base percentage assume that each hit or time on base is equally valuable, when we know that extra base hits lead to more runs than singles and walks. So there needs to be a way to credit hitters for getting on base, but also for how much their particular way of reaching base is worth. Sabermetrics, at its heart, is about making sure we capture as much of that as possible.

One of the statistics to come out of sabermetrics is called “Wins Above Replacement.” Once again, from Fangraphs:

Wins Above Replacement (WAR) is an attempt by the sabermetric baseball community to summarize a player’s total contributions to their team in one statistic. WAR basically looks at a player and asks the question, “If this player got injured and their team had to replace them with a minor leaguer or someone from their bench, how much value would the team be losing?” This value is expressed in a wins format, so we could say that Player X is worth +6.3 wins to their team while Player Y is only worth +3.5 wins.

Now that we know a bit more about sabermetrics and WAR, let’s get back to the 1950s and the colour barrier. As I said earlier, many might rely on the perceptions of those who were alive to witness baseball in the 1950s. However, we have a statistic like WAR that can help us better understand — empirically — whether black players really did have to play that much better to earn their spot on a team. From research published recently:

The data presented here provide support for anecdotal observations about racial bias in the major leagues. For decades, Black players who were promoted to the major leagues turned out to be more valuable players than White ones promoted at the same time.

Now that we know that there’s data to support the idea of this injustice, when do you think it ended? That is, when do you think that black players had to stop being that much better than white players? Before I read the research, I’m not sure what I would have guessed. Why don’t you take a second and think about what’s happened since 1950 and when you think this injustice has fallen away (or whether you think it’s still going on?) Again, from the research:

[Research] indicates that at least through 1975 (28 years after major league baseball was first integrated), Black players were still held to higher standards: simply put, they had to be better to reach the majors. After that point in time, the difference in eventual performance between White and Black players promoted to the major leagues was no longer significant.

So, it seems that in 1975, twenty-eight years after Jackie Robinson broke the colour barrier, the goal was finally realized. Of course, as the last sentence in the above-quoted research says, ‘no longer significant.’ That doesn’t mean that there still wasn’t an prejudicial effect, but just that in measuring that effect via WAR, it was no longer significant after 1975.

The Society for American Baseball Research (the same group behind sabermetrics) put together some helpful visualizations of the baseball demographics from 1947 to 2012. In reviewing some of them, there isn’t any ‘obvious’ reason for why the prejudicial effect is no longer significant post-1975. I’ve included one of the graphs and encourage you to read the whole article as it talks about the decline in black players in MLB.

ResearchBlogging.orgNewman, L., Zhang, L., & Huang, R. (2015). Prejudice in Major League Baseball: Have Black Players Been Held to a Higher Standard Than White Players? Journal of Sport & Social Issues DOI: 10.1177/0193723515594211

Wanna Lose Weight? Get Some Sleep!

There was some research published within the last year that you might be particularly interested in, should you be in the middle of or about to go on a diet (or you’re interested in your health in general):

This article provides an integrative review of the mechanisms by which sleep problems contribute to unhealthy food intake. Biological, cognitive, emotional, and behavioral mechanisms all underlie this relationship.

When I first came across this headline — the less you sleep, the more you eat — immediately, I was interested. After reading the source article (which I quoted from above), I’m heartened by the possibilities for progress in this area.

Naturally, the food we eat has an effect on how we sleep, but the insight that the fewer hours of sleep we get having an effect on how much we eat, is really important. While anecdotal, I’ve experienced this phenomenon firsthand. If I find myself up past my “bedtime,” I almost always am hungry. And because it’s late at night, my executive function is impaired. Put differently, my ability to make good choices might be compromised. In this case, a good choice would be to not eat a bag of chips or a tub of ice cream (or anything sugary, for that matter). A good choice might even be to reach for a handful of nuts or maybe an apple.

The thing that I wanted to mention in conjunction with this research is my suspicion that there’s a cumulative effect. If you stay up late and then pig out on snacks too close to bedtime, invariably, you’ll probably be waking up with less sleep than you need. As a result, your executive functioning (willpower, decision-making, etc.), will be impaired for the duration of the day. By the time you get to the end of the day, you may find yourself more tired than usual such that when it gets to the time when you’d rather go to bed, you might prefer to “reward” yourself or (decompress) by eating some sweets and staying up late… and then it all starts over again the next day. Once you’re out of balance, Newton’s laws have a way of keeping you there.

This reminds me of something I shared a few years ago about Aikido:

One of the exercises we would often do to practice this sense of blending involved our partner (or partners as it was usually in groups of three or more!) to approach us as if they were attacking us. It was our job to then move out of the way, whilst staying centered. The tempo of this exercise usually started out really slow (intentionally). Though, as time passed, our partners would then speed up. You can imagine how it might be challenging to stay centered in this kind of an activity.

During these times of practice, I remember having a bit of an epiphany.

As my partner would approach me and I would step out of the way, I noticed that the quicker (and the more out of balance!) I was, the more out of balance I would be when stepping out of the way for the next partner who was approaching. Think about that for a second: as I stepped out of the way of one partner and I was off-balance, I was that much more off-balance when stepping out of the way for the next partner. It’s almost akin to the Bullwhip Effect.

This idea of eating “after hours” seems to be a mirror image of the off-balance I experienced during the Aikido exercise. So, if you find yourself on the cusp of a diet, I suggest you consider setting (and keeping!) a strict bedtime for yourself. If you’re curious about how to start this new habit, I strongly suggest Duhigg’s book: The Power of Habit.

ResearchBlogging.orgLundahl A, & Nelson TD (2015). Sleep and food intake: A multisystem review of mechanisms in children and adults Journal of Health Psychology : 10.1177/1359105315573427

Looking for a Husband or a Wife? It’s Time to Learn About Altruism

Human companionship. It’s something that we all crave. In fact, a quick look at Google’s autocomplete shows that two of the top three results for “how to get a” return “girlfriend” and “guy to like you.” It’s pretty clear that sharing our life with someone is something we’d like to do (generally, speaking). So, when I came across some research in this area, I thought I’d contribute to those Google searches with some seemingly helpful data. From the journal article:

Our results show that—among single individuals—engaging in prosocial behavior in any given year was associated with increased odds of finding a partner and entering into a romantic relationship in the following year.

I’ve written about the benefits of prosocial behaviour in a work environment (spend your bonus on your coworkers!), so it’s not entirely surprising to me to see that this same behaviour is also beneficial when it comes to increasing one’s odds of finding a romantic partner. Another way of looking at prosocial behaviour is altruism. Essentially, we’re talking about behaviour where one is attempting to help someone else without expecting something in return. Volunteering is an easy example of this.

You may be wondering about the study’s method. That is, did the researchers guard against the possibility that  the reverse is true (entering into romantic relatonships begets more prosocial behaviour). In fact, they did consider this:

We specifically examined whether those individuals who were single at the beginning of a time period and managed to find a partner at the end of the time period were more likely to experience an increase in helping behavior in the meantime than those who remained single. Our results showed that individuals who started a romantic relationship did not experience an increase in helping behavior compared with those who remained single.

So, it looks like the researchers feel pretty confident in their conclusions about volunteering helping to lead one to a romantic relationship. Before you run out to your local Red Cross or Salvation Army, I wanted to offer a different perspective on this research. In particular, I thought I’d look at some of the historical statistics around volunteerism and marriage. That is, if we accept the premise of the research, we might expect to see there to be some covariance between volunteerism and marriage. That is, as marriage goes up, we might expect that volunteerism would also go up. Similarly, as marriage goes down, we might expect that volunteerism would go down.

I had a harder time than I thought I might in trying to find data on these two subjects. However, I did come across a couple of things that gave me pause about this research. The first, volunteerism. According to some research by the US government, it looks like volunteerism is up, recently. That is, it looks like the propensity for volunteering is higher than it used to be (see graph). The second, marriage rates. If the initial research I shared about prosocial behaviour is true, we’d expect to see higher marriage rates (than there used to be). Here’s the headline from the Pew Research Center a few years ago: Record Share of Americans Have Never Married. So, it’s probably fair to say that marriage rates are down. This doesn’t bode well for our initial research on prosocial behaviour.

One last thing I wanted to share on this: millennials. There’s been plenty written about millennials, but I want to focus on the two things we’re talking about today: volunteering and marriage. Compared to previous generations at the same age, millennials are far less likely to get married. Millennials also differ from Gen X’ers when it comes to volunteering:

… higher rates of community service and volunteering. I mean, let’s face it, for Gen X, volunteering was a punishment. You know, you did something wrong at college, you do community service. (Laughter) But the Millennials — it’s more of a norm.

~

It’s quite possible that the effect realized by the initial research on prosocial behaviour is true, but that it’s not big enough to make a dent in some of these bigger statistics. It’s also possible that some of the counterpoints I’ve raised aren’t as analogous as I think they are. Either way, I think the research in prosocial behaviour is important and I certainly hope you take the chance to spend some time “giving without expecting anything in return.”

ResearchBlogging.orgStavrova, O., & Ehlebracht, D. (2015). A Longitudinal Analysis of Romantic Relationship Formation: The Effect of Prosocial Behavior Social Psychological and Personality Science, 6 (5), 521-527 DOI: 10.1177/1948550614568867

Why It’s Important to Have Diversity (in age!) in Your Work Teams

If you had to guess, would you say that younger people or older people are better at learning abstract causal principles?

When first thinking about this question, I would have thought that older people would be better at this given that they have more experience and that they might have been in analogous situations. However, the research seems to indicate that younger folks are better at things like this. Here’s a passage from the researchers that specifically address my thought that experience would be helpful:

The very fact that older learners know more may make it more difficult for them to learn something new. Once a learner has inferred a general principle (e.g., that people act because of their traits, or that individual objects, rather than combinations of objects or relations between them, have causal powers), that principle may constrain his or her interpretation of new data. Causal relationships that conflict with that principle may then be more difficult to learn.

Certainly this research is important, but the thing I want to highlight here is work teams. Specifically, this study points to the importance of having diverse w0rk teams. It’s important to remember that diversity doesn’t just mean people of different genders and different races, but people of different ages, too. If we mix in folks with different “levels of experience,” we might have a better chance of coming up with a solution to the issue than if we just used folks who were all of the same level experience.

Further to that, I was thinking about how this research comes into play when we think of top management teams or corporate boards. Recall the post I wrote recently that discussed the importance of diversity at the board-level. I don’t remember there being anything related to age in that article, but I also suspect that conducting research on age as it relates to boards or top management teams might be difficult. Usually, we find folks who’ve reached a certain level of experience before they’re considered for work on a corporate board or considered for a promotion to the top management team. Maybe we need to start thinking about considering some younger folks for positions in these roles.

ResearchBlogging.orgGopnik, A., Griffiths, T., & Lucas, C. (2015). When Younger Learners Can Be Better (or at Least More Open-Minded) Than Older Ones Current Directions in Psychological Science, 24 (2), 87-92 DOI: 10.1177/0963721414556653

Psychologists Want an Alternative to the DSM

In another life (or a different timeline, if you prefer) I didn’t change paths and continued on to become a clinical psychologist. In that life (or timeline), I, and many other psychologists are using something totally different than the DSM and the psychologists in this timeline are jealous. Confused?

Recent research published sought to see if the attitudes of psychologists, with regard to the DSM, have changed at all. It turns out, they haven’t:

The results are no different from what was found three decades ago, namely, that a significant number of psychologists are unhappy with the DSM, but almost all of them use it.

So, why do we continue to update the DSM instead of scrapping it and making something better? Well, that’s probably a can of worms for a different post, but it seems telling that in 30 years that psychologists still aren’t happy with what is supposed to be a very important source book for the profession. More than that, as 30 years have spanned, it’s fair to say that even the next generation of psychologists aren’t warming to the DSM.

In reading this study, the most troubling sentence comes from near the end of the article [Emphasis Added]:

They appreciate its help in making diagnoses and supplying reimbursable diagnostic codes, but continue to have scientific, professional, economic, and ethical concerns about it.

That’s troubling, indeed. Scientific, professional, and ethical!

It seems to me that a profession whose bedrock is based in morality and ethics should be motivated to rectify this concern. If they were to change things, what would they change it to? [Emphasis Added]

Even though they may not see the categories in the DSM as merely problems in living, psychologists are interested in alternatives not rooted in the medical model common to the DSM and ICD. Psychologists might be prepared to further develop and use psychologically focused diagnostic alternatives if conditions encouraging them to do so were in place.

That sounds congruent. I remember my time in as a doctoral candidate and many of my colleagues at the time were far more interested in modes of analysis that didn’t subscribe to medical models. There are a number of reasons for this, but for this kind of a wholesale change to occur, I think there needs to be a push from the APA. I suspect that other psychologists would agree with that, but there’s also the possibility that there’s some sort of grassroots “uprising” that starts with individual psychologists. The one hitch with that possibility that I see is that many psychologists work on their own. That is, instead of working alongside their colleagues, they have their own office space and work by themselves. I think if psychologists had something resembling a “union” like there are in some other professions, it would be far easier for them to organize and create the kind of change they’re looking for.

To be clear, I’m not advocating for or suggesting that psychologists should form something like a union, I’m merely saying that if there were this kind of infrastructure in place, I believe it might be easier for there to be a change to the way psychologists diagnose.

ResearchBlogging.orgRaskin, J., & Gayle, M. (2015). DSM-5: Do Psychologists Really Want an Alternative? Journal of Humanistic Psychology DOI: 10.1177/0022167815577897