Moving notice

Hello loyal reader(s) of Cedar’s Digest.

I have decided to pack up my things and move, from to my own self-hosted site:

Please redirect or resubscribe your feedly or RSS readers, or email settings if you wish to continue to receive my posts.

Part of the move is the integration of my professional page, with my cv, scholarship, etc with my blog. Another part is the desire to take control of my own online identity.

Read more about it on my first post at my new place:

Please Allow me to (Re) Introduce Myself


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Social Media as a Catalyst for Psychological Science

Can social media serve as a catalyst for psychological science?

I think many scientists are rightly skeptical of social media as a replacement for other normal scientific processes. Peer review will not be replaced by Tweep Review. Methods sections will not be replaced by “Storifies.”

However, it is equally clear that social media engagement can boost the spread of scientific information, and enhance scientific communication, both within a scientific community as well as between scientists and the public. Social media can be a catalyst for psychological science.

Last week Melanie Tannenbaum, Jorden Cummings, Stuart Ritchie and I presented a symposium at the Association for Psychological Science 2014 annual convention on Social Media as a Catalyst for Psychological Science, laying out both the why and how we have used social media to enhance our science.

Here is a pdf of my presentation, with slides and what I said, hosted by the Open Science Framework. I also expanded that into a blog post.

Here is Melanie Tannenbaum’s presentation (“Social Media can be for Science!“) on slide share. I thought Melanie did a great job of showing how facebook can be used to spread scientific knowledge to friends and family, but also to humanize science to people who might not otherwise encounter someone they consider a scientist in everyday life. When Melanie was curating and trimming her facebook friends, hoping to tailor what friends in different areas of her life saw (would runner friends want so much social psychology? Would psychologists want to see so many cat pictures?), she asked her friends if they wanted to be removed from any lists. One of her old high school friends wrote a poignant comment: “I dropped out of college so your posts are the closest thing I’ll get to an education, please keep me on all your lists.” It also struck me that while facebook links to scientific articles are no substitute for higher education, on Melanie’s facebook page they are more than just a clipped article, because they include the original article as well as discussion among Melanie’s social psychologist community. Eavesdropping on professional or expert dialogue is one of the unheralded benefits of social media to me, and Melanie had a number of great examples of good dialogue as well as the benefits to the rest of her extended social network.

Jorden Cummings talked about how a conversation on twitter led to a research project. Cummings Day APS 2014 – Jorden nicely laid out the process of recruiting participants through twitter, negotiating IRB protocols (she had an approved tweet to use for recruitment) and disseminating the results. I thought her experience also showed very nicely how twitter can link people from relatively disparate backgrounds. Jorden is an academic clinical psychologist who studies interpersonal relationships and psychopathology at the University of Saskatchewan, and her colleague on this project is T. Eugene Day, a systems engineer who studies quality improvement and patient flow, as well as care delivery as a Senior Improvement Advisor and Principal Investigator at the Children’s Hospital of Philadelphia.

Stuart Ritchie closed our session with “4 tips for making psychology on twitter less annoying.” Ritchie – APS 2014 Twitter Talk – 1) Beware the echo chamber. Stuart pointed out that psychologists can lean heavily liberal, and we risk enclosing ourselves in echo chambers. Luckily for us, while moving to towns or neighborhoods that are more ideologically diverse might be difficult, following people who we don’t agree with on twitter is not that hard. 2) Think before you tweet… but also resist the urge to pile on. Highlighting the idiotic and prejudiced tweet by Geoffrey Miller, Stuart agreed that this was a bad idea, and we should avoid such a fate, but also cautioned against the momentum of outrage that can build on twitter. 3) Don’t be a replication bully. This episode has received even more attention since then, but Stuart reminded us what might seem to be a small bit of snark can be spread far and wide on twitter. 4) Finally, Stuart showed us how a bit of complaining on twitter about the poor methodology of a paper between himself, Keith Laws, Tim Smits and Daniel Lakens led to a published critique of the article. I thought this was a great example for two reasons. First, it shows how conversations on twitter can be “kindling” for longer, deeper, more substantial conversations on other channels. People on twitter often recognize the limits of 140 characters, and know you aren’t going to get a roaring fire from a few sticks, but sometimes that’s what you need to get it started. Second, I thought it showed how twitter can level status cues. Stuart is a graduate student and each of the other authors are professors. All too often the water cooler talk is segregated along status lines, and twitter can be an entry for junior colleagues to contribute. Perhaps this isn’t always the case, but I find that on twitter people might not take the time to glance at your conference name tag, or guess your age, and are more likely to react to the content of what you are saying.

Ok, that’s all. I hope that these presentations can help convince some of you psychologists not on twitter to get on, and maybe give a few tips to those of you who are already on or convinced that it is worthwhile.

Posted in psychology, science, web | Tagged , , , | 1 Comment

Social Media as a Catalyst for Psychological Science – My presentation

At the recent Association for Psychological Science annual convention, I co-chaired a symposium on “Social Media as a Catalyst for Psychologist Science.” In my next post I will give some context to the entire session, but first, here is my presentation, in blog form. This presentation is also available as a pdf: Riener – Social Media as a Catalyst for Psychological Science

NT homepage decline

I begin the motivation for using social media to spread psychological science with this chart, from the New York Times Innovation Report, a leaked internal document explaining the external challenges, internal struggles, and plans for the future for the New York Times to continue to be a successful media outlet. This chart illustrates how social media is coming to dominate the web, even “official” or “old media” sites like the New York Times, and how this is a very recent change (notice the years are from 2011 to 2013). This chart shows how visits to the NYT homepage have gone from 160 million a month to less than 80. People are finding the articles they want to read through social media.

These charts to the right (also from the same report) reinforce that point, but looking at the whole web. Visits to home pages are declining while social media referrals are climbing, all over the internet. People have NYTimes Innovation Report - Referralschanged the way they access the web, and shifting to getting referred from social sites.

Why communicate science online? I begin with how to be a scientist on social media by referencing an excellent primer by the biologists Holly Bik and Miriam Goldstein. Their Figure 2 shows the different scientific purposes and time commitments of various social media activities. For this presentation, I will focus on twitter.

As Bik and Goldstein note, different social media are well suited for different purposes. However, one thing that they note in the article that is not clear from the figure, is that these interact. Twitter can help spread a blog post, and a conversation on a blog post can spill out into twitter and facebook. But this is a good framework for how to see the social media landscape and science. For this talk I will be focusing on twitter, which is my preferred social media network.

Liz Neely - twitter as cocktail party at conference

For how to think of twitter, I turn to Liz Neeley, who succinctly frames twitter as a cocktail party at a conference. It isn’t only a presentation, or a poster session (where people are only strictly business) but it also isn’t just your friends who are interested in everything personal. The way I approach it, scientists on twitter shouldn’t be afraid of sharing a few personal details here and there, but most of the people who follow you will do so because of what your professional expertise or interests are, not personal reasons. This of course varies, but I recommend starting out thinking of twitter this way, curating your friends this way, and putting that kind of filter on your communication.

Riener - Who Am I slide

This is a brief snapshot of who I am, what I tweet about, and what I am interested in. So on twitter I will follow people in each of these spheres. I follow other teachers of General and Intro Psychology, historians of psychology (and some historians), perception researchers, teachers, and other people involved in higher education policy debates and faculty governance.

With gratitude to Raul Pacheco, who has listed five things he thinks twitter is useful for in academic contexts, I decided on four for the few minutes I have with you today.

Here are 4 things I’ll talk about today that I find twitter useful for: news and discovery, building scholarly networks, quick help, and giving psychological science away.

News and Discovery

First, as a personalized newspaper. Here are some examples of things I found interesting and useful that came across my twitter feed recently, that I would have not seen otherwise. Holcombe - retina evolutionAlex Holcombe, a fellow perception researcher, came across a fact about the evolution of the retina (in a Nature Reviews Genetics article, a journal I do not read or track) that non-visual cells evolved into visual cells, and visual cells evolved into non-visual. Cool!

Chris Crew - Columbia PhDJay Van Bavel, a social psychologist at Columbia, tweeted a picture of Chris Crew giving a presentation (with Kenneth and Mamie Clark pictured on a slide in the background) and noted Crew was the first African American man to earn a Ph.D. in psych from Columbia since Kenneth Clark. Interesting (and sad) fact that I remember and pass on to my history of psychology class.

ENTJ destroyer of worldsFinally, a colorful example from the Onion, to use when I trash the Myers Briggs Trait Inventory.



Building Scholarly Networks

I also use twitter to build scholarly networks. As a cognitive psychologist in a small school, in a small town in Virginia, we don’t have frequent psychology journal clubs or symposia. So I use twitter to connect with psychologists I would not otherwise be able to have a conversation with. riener - pashler - nature picsHere I am having a brief conversation with Hal Pashler. I will also say that I think twitter often acts as a leveler. If you are a junior faculty or graduate student, you can still have a conversation with a senior faculty member, and the mediated nature of the communication can sometimes reduce some of the cues to power and status that are often present in real world contexts.

I also like twitter to broaden and diversify my scholarly network, beyond the academy, and beyond my areas of interest and research. Sanjay Srivastava is a social psychologist, Audrey Watters is a education journalist who is an excellent (and respected) voice on educational technology, Mark Changizi is a perception researcher who has left academia, but remains quite active in applying perception research to real life problems through his company 2AI labs. Bashir9ist is a pseudonym for a graduate student in neuroscience who I have had a number of conversations with about neuroscience, graduate training in psychology, and other shared interests over the course of a year or two. As he went on the job market, I came to do some informal mentoring and advice. He may not have needed it exactly, (he got an excellent job) but he has not been the only person who I have served in this role. For me, building this scholarly network is not just what I can take from my network, but what I can give back.

Quick Help

Another example, though it may seem trivial, is the quick, non-google-able answer to a question. I am thinking about training myself up on R this summer, but I am a bit daunted, and it was helpful to discover that Jonathan Goya, a computational biologist in my network, is willing to help. Another biologist friend, Jeremia Ory (of the perfect twitter name: DrLabRatOry), chimed in to agree that Jonathan was very helpful.

Giving Psychological Science Away

Me and Nyhan and KonnikovaMy final example of using twitter is to spread psychological science and interact with non-scientists about psychological science. This might be in interacting with a science journalist (as I did here with Maria Konnikova, who is actually a scientist herself so perhaps not a perfect example) or a fellow academic in another related field (Brendan Nyhan is a political scientist who studies false beliefs in politics), but it also might be hosting a chat session with teachers. In the case on the left I hosted a #psychat session and asked AP psychology teachers about how much writing their students did. I also shared some of my conceptions of college readiness.

I’ll close with what many people might think is the first reason to use social media as a psychological science: to spread their own work. My article on learning styles, attempting to translate some of the basic findings in cognitive psychology to show that learning styles are not educationally useful, was spread very widely on social media, and I can track when it is spread and encourage people to ask questions, or answer concerns. I will also add that the other ways that I use twitter contribute to this final use. Because I have built my scholarly networks, asked and provided quick help, interacted with science journalists, the people in my network are more likely to read and spread my science.

That observation bears repeating, that each of the many uses of twitter (and you will certainly find some more yourself) interact with each other. Promotion helps you build your network, and robust networks help you more effectively promote. Offering quick help builds up good will, but sometimes, so does asking for it. Sometimes someone else in your network had that same question and didn’t think to ask. Curating interesting news and discovering things you find cool often means you spread that stuff to your network, and you come to be trusted and respected for your unique perspective.

Finally, I’ll close by saying that twitter and social media have a built in “baby pool.” Jump in, follow ten people, spend ten minutes a day checking it, and let your network grow organically. Don’t feel like you have to do it all at once. Thank you for your time, and I hope to see you on the twitters!

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On Controversial College Speakers, Debating and Critical Thinking

Azusa Pacific University recently disinvited Charles Murray from giving a talk there. The talk had been scheduled for months, but apparently no one realized the full extent of his bad reputation. He wrote an open letter in response.

Although regular readers will know that my politics are quite opposite from Murray’s, I agree with Murray here. Here’s where I think they went wrong.

First of all, don’t invite someone unless you know who you are inviting and what they are going to say. Doing some due diligence on speakers seems not only like college PR 101, but college 101. Would we assign a book to our students without reading it ourselves, or at least having a really good sense of what was in it? Of course not.

Second, if you have invited someone who you discover has views you consider abhorrent, recognize that you have already given them publicity with the invitation. By my mind, rescinding the invitation doesn’t necessarily reduce their stature, all it does it prevent your students from engaging with their ideas on your campus.

Third, we should value engaging with ideas we disagree with in general, and in particular people like Charles Murray. Even when we disagree with conclusions, in higher education we should value people who convey their ideas clearly and with evidence, even if we see them as cautionary tales. I would much rather we engage with Charles Murray, because he often clearly lays out the ideas that many conservatives hold without explicitly stating them, than with vacuous celebrities such as Jenny McCarthy.

One of the things that I try to model in my psychology classes is how we disagree and settle arguments as scientists. Many of my students and I disagree on whether spanking works or not. That’s fine, but how should we disagree? As scientists, we should talk about what “works” means. Does it make children behave better? How would we measure that? Does it make them more obedient? How would we measure that? What sorts of studies could we do? Can we compare households who engage in spanking and those that don’t? What measures should we use?

It is very difficult to train critical thinking or even engage in it without any disagreement. Without disagreement, our claims turn into assumptions, and these assumptions melt away into the air we breathe.  This lesson is the one big lesson of perception. Just because we all see something the same way, doesn’t mean that it isn’t an assumption or a guess. Our visual system is full of assumptions that we don’t experience as assumptions.

We don’t realize that we have assumptions until someone asks “why do you think that?” Certainly it is possible to ask why without disagreeing, my kids do it all the time, but as adults we aren’t as easily led to the “why” questions without disagreeing with someone. You don’t think we need affirmative action? Why do you think that? You think over the past 50 years we have achieved meritocratic sorting in higher education? Why do you think that? You think you can write a book about class divergence as if it can be isolated from race? Why do you think that?

In my last post, I cited an essay by Murray on higher education. I find it useful in my own thinking to really grapple with the ideas here. Murray makes the claim that too many people are going to college.  He argues that we should make K-12 the grades where we impart liberal education and the core knowledge of our society, and that higher education should be more focused and targeted on people who want to be professionals and need training in reading and writing. I found myself agreeing that it is a problem that our society gives everyone the expectation that a college education is absolutely necessary to get a decent paying job, and we end up with many many students who are only in college to get a job, and are not motivated by the knowledge itself. Both Murray and I (and Mike Rose, I’d guess) would agree that our society should respect the trades far more than it does. I think where we’d split is that Murray seems to label trades as “good with your hands” and suitable for our low-IQ, unfit for college underclass, whereas Rose and I see trades as often just as cognitively demanding as professions, but simply not recognized as such. Here’s Murray:

But while it is true that the average person with a B.A. makes more than the average person without a B.A., getting a B.A. is still going to be the wrong economic decision for many high-school graduates. Wages within occupations form a distribution. Young people with okay-but-not-great academic ability who are thinking about whether to go after a B.A. need to consider the competition they will face after they graduate. Let me put these calculations in terms of a specific example, a young man who has just graduated from high school and is trying to decide whether to become an electrician or go to college and major in business, hoping to become a white-collar manager. He is at the 70th percentile in linguistic ability and logical mathematical ability—someone who shouldn’t go to college by my standards, but who can, in today’s world, easily find a college that will give him a degree. He is exactly average in interpersonal and intrapersonal ability. He is at the 95th percentile in the small-motor skills and spatial abilities that are helpful in being a good electrician.

I think he is drastically simplifying both managing, which requires a great deal more than linguistic and logical mathematical ability and being an electrician, which isn’t just small motor and spatial skills.

But that’s not the point. The point is that in laying out his argument, in claiming that the relevant distinguishing characteristic of this young man is ability (whether academic or small motor ability), Murray forces me to confront and sharpen my views on why I think people should go to college, why I think some people are unmotivated about college, and whether some people are “unfit” for college.

Rather than disinviting Charles Murray, why doesn’t Asuza Pacific University use this as a teaching moment, and ask someone else whose views are contrary to Murray’s? Why not spend some money and invite Ta-Nehisi Coates or a Isabel Wilkerson to talk about how the legacy of white supremacy still haunts us? I am not saying that everything is a debate, or that we should always give equal footing to each side of the argument, but if you have already invited someone, and that someone is clearly representative of a large body of views on one side of the political spectrum, why not debate instead of canceling entirely?

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Thumb on the PayScale

In my last post, I took issue with the PayScale college rankings, as well as with how economics reporters framed these rankings, citing their low calculated Return on Investment as evidence that these colleges “make” students poor. Jordan Weissmann has graciously responded to my critique. The Senior Vice President from PayScale itself has also responded in a comment on my post, defending the rankings as useful to high school seniors who later tell him, “I wish I had known this before.” I’m glad for the dialogue, and I think this issue connects to a larger debate on the value of higher education in general, as well as the relative value of different colleges, so I am going to keep the conversation going with a more extensive response.

Weissmann is not alone in his framing of PayScale’s rankings. While his headline at Slate reads “Which College Will Make You Poorest?” Derek Thompson at the Atlantic treads similar ground: “Which College—and Which Major—Will Make You Richest?” and later, “These U.S. Colleges and Majors Are the Biggest Waste of Money.” Walt Hickey goes with a more straightforward, but still uncritical view at 538: “Study Names Colleges with Best Return on Investment.”

My argument was first that salaries from art schools and engineering schools are not directly comparable, since students are not often choosing between Harvey Mudd (#1) and Maryland Institute College of Art (#1301). Chris Chabris mentions this point in his post criticizing 538’s coverage of the rankings. Second, I argued that PayScale and many journalists who wrote about the rankings, are overstating the role of the college in shaping its students salaries and understating other factors in what determines a students future salary, such as the role of selective admissions, constraints in the labor market and choices of the students themselves. Weissmann acknowledges various limitations (including selection bias) of PayScale’s methodology, but he doesn’t see these as reason enough to avoid phrasing like: “Which college will make you poorest?” or “Yes, the art school really is making students poorer if it delivers a negative ROI.”

The subhead for Weissmann’s recent defense of ranking colleges based on graduate salaries reads: “Academics might not like it, but schools should be held accountable.” Since I am the only named academic in the article, and my quote is framed as “Like many in higher education…” I can assume that Weissmann sees my criticism as based on my identity as an academic. True, I am an academic. I do feel solidarity with my fellow providers of higher education, whether they be at the University of Virginia (apparently THE best value! Wahoo!) or at arts schools like Maryland College of Art and Design, or Historically Black Colleges and Universities like Shaw and Fayetteville State University. However, my criticism of this particular set of rankings owes more to my training as a social scientist (and as a psychologist in particular) than to my allegiance with all institutions of higher education. Here’s why:

Claim a Cause? You’ve Got to Earn It

All this writing about salaries reminds me of another kind of earnings. When a scientist such as myself reads a headline with a claim that something causes something else, I ask whether the speaker has earned the right to make that claim.  Can the data cash the check that the causal claim makes? A few examples: “Smoking causes cancer,” “miracle diet causes weight loss,” “stress causes ulcers,” and “vaccines cause autism.”  While many educated people may start with a skeptical “correlation does not equal causation,” most scientists (especially social scientists) know that not all correlations are created equal, some studies are better than others. For a long time, the only good data on the harmful nature of smoking was epidemiological: those who smoked tended to have worse health than those who didn’t. Notice the lack of a causal claim, a study might conclude that a heavy smoker is 50 times more likely to develop lung cancer than a non-smoker, but it is still possible that smokers in general lead more stressful lives, exercise less, and have less healthy diets. In this case, rather than causing cancer, smoking is merely another marker of an unhealthy lifestyle. More recently studies have narrowed in on the biological mechanisms of smoking’s harmful effects on the body. What is it precisely that causes the harm? Is it the nicotine? the tar? What are the cellular mechanisms of the carninogens in cigarettes? These questions now have much more specific answers based on carefully controlled experiments, and even though there still seems to be some randomness to the overall pattern of carcinogens causing cancer (yes, some people can smoke for 60 years and not get cancer), we know a lot more about the biochemical effects of smoking.

But even without research into the cellular mechanisms, the epidemiological, correlational research was able to earn its causal claims. One landmark study compared British male doctors who smoked with …. British male doctors who did not smoke, and followed them for over 40 years. Keeping many other variables constant, this study still finds incredibly harmful effects of smoking.

A similar search has been conducted for a connection between vaccines and autism. Many children exhibit the first signs of autism spectrum disorders at around the same time they are vaccinated. Yet this is a misleading correlation. Epidemiological research would seem to be impossible. How can we compare levels of autism in non-vaccinators and vaccinators if everyone vaccinates? Except now that the fear has spread, we can. Populations that don’t vaccinate their children have the same incidence of autism as those populations who do vaccinate. Amazingly enough, however, populations who choose not to vaccinate DO have higher risk of an outbreak of whooping cough. A long search has concluded that vaccines do not cause autism, through both epidemiological work, as well as the search for biological mechanisms of harm.

Which brings us back to PayScale and the economics reporters. Have PayScale and these reporters earned their causal claims? Are these rankings actually useful to high school seniors deciding where to go to college, as Barnaby Dornfman comments on my previous post, or merely perceived to be?

I remain deeply skeptical.

The Median is not the Message*

*with apologies to Stephen Jay Gould

There are (at least) three classes of factors that could predict a high school student’s future salary. First, a student’s individual characteristics such as preferences, abilities, motivation and even demographic variables such as race and gender affect their future salary. Second, that person’s education and training of course influence what they earn. This is where college fits in, but it might also include high school preparation as well as out of school preparation. Third, students future salaries are dependent on the labor market they enter as they leave college. As many unemployed or underemployed PhD’s are now discovering, someone can have great achievements in the other two factors, but if there are few to no jobs, one’s salary is severely constrained. The PayScale rankings understate these factors in comparing salaries of graduates to the median salary for someone who has only a high school diploma.

The reporters who have covered the rankings, and to a lesser degree, PayScale itself, make two critical errors that undermine their causal claims. First, they gloss over the impact of student and labor market factors on salaries. Second, they also understate how inseparable colleges are from the students who attend them. The rhetorical effect of the apparently straightforward reporting on these rankings are a pair of bold pronouncements “Get thee to a college that doth begin with H-A-R-V, and drink thy fill from the trough of increased economic outcomes” and “But lo! if thy find thyself in Pellville Directional State University, fly fly away, and become a manager at Ye Olde Chipotle, for thy riches will grow more from avoiding useless, expensive learning than from seeking it.” The truth is a lot more complicated. Aggregate salaries depend far more on student characteristics present before they enter college and the labor market that they choose to compete in as they exit college, than what differentiates the colleges that choose to admit them.

There are a few ways to see this in the rankings themselves. I’ll admit that I don’t know much about the Colorado School of Mines, but what is making their students rich is not necessarily the school itself, but the students’ decision to become engineers in Colorado (or miners, maybe Clementine’s dad had it right after all!). When PayScale compares their salaries to what a median high school graduate makes, this isn’t the best comparison, given that these students have already decided to become engineers, it seems with a focus on energy and environment. Likewise, for the number 1 ranked school, (Harvey Mudd), before Harvey Mudd does any educating, it has selected certain students to admit, and some subset (approximately 30%) of those students have made a decision to attend a small engineering school in California. Of these students who choose to attend Harvey Mudd, 14% qualify for Federal Pell Grants and 46% qualify for any federal student loan aid. For these students, the average total federal student loan aid is around $6,400.  I am certain that Harvey Mudd is a fantastic student experience, but I think it is fair to say that they enroll a student body that is privileged, motivated, ambitious, and focused on a high salary occupation from the moment they arrive on campus. These students have decided to become scientists or engineers before they entered Harvey Mudd, and it doesn’t make much sense to compare their return on investment to what the median high school graduate makes.

Perhaps to defenders of the value of these rankings, they are fine with the advice boiling down to: Want to make more money? Become an engineer, not an artist. Here is hard data on how poor you will be as an artist. Going to college won’t help you if you choose a low paying career. As I said before, I am dubious of the value of such advice, although PayScale Senior Vice President Barnaby Dorfman has experienced sending the PayScale rankings to many people who say “I wish I had known!” However, for the I-wish-I-had-known camp to improve economic outcomes by going into engineering, we need enough engineering jobs to accommodate increased labor supply. But this is not the case. There is no STEM skills gap. There is no labor shortage for STEM jobs. Perhaps a better way to improve outcomes would be to forgo college altogether, and, as Weissmann suggests, work in a Ford factory or manage a Chipotle. This assumes that the student choosing these jobs instead of college will make greater than the median salary of high school graduates, which Weissmann acknowledges may not be the case, due in part to “weaker skills.” Even though Weissmann and others briefly consider the other flaws in this model of salary prediction, I think it is worth it to drill down deeper.

The Worst Performers

What if we do this kind of analysis for Derek Thompson’s so-called “biggest wastes of money?” The students entering these colleges quite often already have a deck stacked against them, and not just in college choice. A student entering Shaw University, the oldest historically black college in the South, located in Raleigh, North Carolina, is making a hopeful investment in a college education. But comparing their future salary to the median high school graduate does not take into account the racial disparities in our current labor market. Further, as Raj Chetty and colleagues have shown, economic mobility is constrained not just by demography of the individual, but by geography as well. In his testimony submitted yesterday to the Senate Budget Committee, Chetty describes one pattern with this lack of mobility: “The first pattern we document is that upward income mobility is significantly lower in areas with larger African-American populations.” He also notes that if mobility is measured by a child’s chances of moving from having parents with the lowest quintile in income (poorest 1/5th of population) to themselves having upper quintile income, one of the “commuting zones” lowest in intergenerational economic mobility? You guessed it, Raleigh, North Carolina with 5%, considerably lower than San Francisco, San Jose and San Diego, California,, all with odds more than twice that. See the map he created below:

Chetty map

To connect geographical mobility to higher education, we must understand how far students are likely to travel for college.  Most students stay close to home. Look closely at this data from the ACT.  The median distance to college (for those who took the ACT) is 51 miles. But if you separate groups by test scores, those who score lowest, stay closest to home. If you score between 1 and 15 on the ACT, the median distance to college is 18 miles. The same pattern can be seen depending on parental characteristics. For students whose parents have no college education, the median distance they travel to go to college is 24 miles (parents with graduate degrees? median distance of 95 miles). Poor students are less physically mobile, which is influenced by, and contributes to, their lack of economic mobility.

Take My Advice, Don’t Try it Twice, if You’ve Got but 50 Cents

So the PayScale rankings would have you believe that students should choose higher ranked colleges, instead of those that “make them poor,” like art schools and HBCUs. The advice is not “Don’t be black, because structural racism will still hurt your progress” or “Don’t be poor in the south, because intergenerational economic mobility there is very low” or “don’t find value in art, because your society doesn’t support that,” but rather: “Watch out for these schools, they waste your money!”

Here is where I notice a difference between what I will call the neoliberal economic approach from a conservative one like Charles Murray’s.  Neoliberals are often confident in the power of greater information to improve equality and efficiency, whereas conservatives are openly pessimistic that all students are intellectually capable enough to complete college.  Here’s Charles Murray:

So even though college has been dumbed down, it is still too intellectually demanding for a large majority of students, in an age when about 50 percent of all high school graduates are heading to four-year colleges the next fall. The result is lots of failure.

Whereas Weissmann closes his original reporting of the PayScale rankings with this:

But it does reinforce why we so desperately need high-quality consumer information about higher education. In the past, the higher-ed lobby has stood in the way of allowing the Department of Education to track college graduates over the long term to keep tabs on their lifetime earnings—what’s known as a “unit-record system.” And as a result, we have to rely on less complete government surveys, or less-than-ideal crowdsourced databases like Payscale’s. As a result, some students are going into college financially blind, and they could be ending up poorer for it—literally

Notice another causal claim: the lack of data is what is causing students to go into college financially blind. What goes unsaid here is that if better data existed, then students and their parents would view that data and incorporate it into their model of how college works. Then, armed with better financial vision, they would made better financial decisions. This same confidence underlies the concern about undermatching, in which high achieving poor students choose to attend lower status institutions, when they would apparently have better outcomes at a wealthier, more prestigious college. This is a topic I have written about here and here. Sara Mayeux makes some excellent points about Yale’s tone-deaf and misguided efforts to address undermatching.

A common theme across the educational spectrum emerges. Yes, economic inequality has grown and states continue to disinvest in higher education, but a cheap, easy and effective way of improving students’ economic situation is through educating people who experience low workforce success (i.e. poor people) to help them make more informed decisions. The implication is clear: Low performing schools (whether colleges or urban public schools) don’t need resources, they need to be held accountable. Low performing graduates and their parents don’t need better economic opportunities, they need better data. Graduates of HBCUs don’t need laws and policies to counteract the persistent effects of racist housing programs, racist tax policy, racist hiring practices, racist underfunding of public K-12 schools, they need bourgious norms, invigorating moral culture, and better salary data. Apparently these students should be informed that an HBCU, which may once have been a proud part of familial identity, a cause of pride in black scholarship, a shining beacon of advancement through higher education, well, now big data science shows it offers a low ROI. Prospective students should be advised to go to a better school, or an engineering school, or work at a factory instead.

I know that Weissmann, PayScale, and everyone involved in this debate wants a better system of higher education in these United States of America. We all should want, to paraphrase Lincoln, a higher education system of the students, for the students, and chosen by the students. One that is accountable to the students. But in search of this goal, they are willing to forgive imperfections of their scale, convinced of the desperate need for accountability. But as a psychologist well versed in some of the shameful consequences of imperfect scales in psychology’s past, I am skeptical. Instead of progress and accountability, I see such rankings of colleges based on assumptions of privilege and status, devised by privileged tech boom MBA’s, for the software and energy engineers. I see this scale as one that does not encourage accountability, but merely reflects existing social inequities and blames society’s economic losers, just as existing social policies make their fates increasingly unavoidable. Don’t tell me you are holding colleges accountable, while holding your thumb on the scale.

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The Absurdity of Ranking Colleges by Graduate Salaries

Jordan Weissman has moved from the Atlantic, and is now covering economics at Slate. He has a post up provocatively titled (it is Slate, after all) “What College Will Leave you Poorest?” which covers the Payscale college salary rankings, in which ranks colleges based on the cost of the college offset by the reported salaries of their graduates. In other words, a return on investment for each college. What a grand idea.

Ok, I think it is a terrible idea for a lot of reasons, but in efforts to keep this blog post under 1000 words, I am going to focus on one seemingly minor issue, which to me invalidates this entire ranking system. To illustrate this, humor me first on this brief tangent into basic statistics and my own education in cognitive psychology.

I was a history of science major, so I only took a few psychology classes as an undergraduate, and these were all in the clinical or neuroscience area. So when I got to graduate school in cognitive psych, I had to catch up to learn some basic concepts. One of these didn’t occur to me until I took a class on “Advanced Research Methods in Cognitive Psychology.” We were discussing the merits of how to graph and analyze different kinds of data, and we were talking about time. We reviewed the different types of measurement scales. When a measurement is on an nominal scale, there is no order to the results of the measurement at all. These as categories, and it would make no sense to say that they are in order, or that the differences between them can be interpreted in some quantifiable way. Gender, race, religion, types of fruit, etc etc.  The next type of scale is ordinal. In this scale, the results are ordered, but the difference between the orders doesn’t necessarily make sense. This could be rankings, like eldest, middle and youngest child. We can put them in order, but the difference between the eldest and the middle is not necessarily the same as the difference between the middle and the youngest. Many likert-style (“neutral, ok fine I guess, agree, strongly agree, DEAR GOD YES”) survey items are on an ordinal scale. We can say that someone who chooses option 5 agrees more than option 3, but is the difference between 5 and 3 the same as between 3 and 1? Probably not, and we should analyze our data as if that is the case. The next scale is interval scale, in which the scores are ordered, but also the differences between ranks are equal intervals. For interval scales, the difference between scores of 8 and 10 is the same as between 2 and 4. Time is often given as an example of an interval scale. Finally, a ratio scale has a true zero point, where a score of zero is real and meaningful, such as wealth or income.

We were talking about these scales, and the issue of measuring reaction time came up. It seems like it could at least be an interval scale, if not a ratio. But as we were talking, the professor reminded us that even if the physical scale of time was an interval scale (the difference between 1 and 2 seconds is the same as the difference between 20 and 21 seconds) this did not mean that the psychological dimension of reaction time was also an interval scale. This struck me as an interesting way of thinking about a central insight in scientific psychology, since its inception. We have to be careful in how we treat our measurements, taking into account that the psychological scale does not always map cleanly onto the more physical or concrete scale (whether it be light, sound, time, or money).

Here’s my contention: while money might be an interval scale, salary is not.

Sure, a dollar is a dollar is a dollar, but saying that a mineral engineer makes twice what an artist does, and therefore this particular art school isn’t worth it, that just seems absurd, but it is exactly the logic that their ROI tanking system encourages, and that Weissman’s article adopts in using language like “to be blunt, these schools make students poorer.” No they don’t. I imagine that most students entering art school are fully informed (by parents, teachers, classmates, strangers in the grocery store) that their choice is disastrous and they will never find a lucrative job doing art. They choose to pay for training anyways. Is the art school making them poorer?

The salaries of graduates from Harvey Mudd (#1), the Colorado School of Mines (#11), UNC-Asheville (#1306) and Maryland Institute College of Art (#1301) are not comparable and should not be compared as if they have anything to do with the schools. Instead, this scale is not just a proxy for which careers graduates choose upon leaving the college, but even what career they were interested in upon entering that particular college.

A given measurement scale supports a certain kind of statistical analysis. If one has an nominal scale, it makes no sense to make ordinal claims of greater than or less than (are oranges less than apples, maybe Honeycrisps). If a measurement is on a ordinal scale you can report frequencies, but it makes no sense to analyze means or standard deviations (what is the mean and standard deviation of mild, medium, spicy and Native Thai?).

Perhaps the payscale people should consider replacing their college rankings with a big simple headline that says “Engineers make more than artists.” and “People who apply and are accepted by Harvard are going to make more money than people who apply and are accepted by Morehead State.”

I could go on and on. No matter how seemingly sophisticated these rankings seem, they have not found a way to disentangle a school from the students who choose to attend. Just because we have found a number (salary) that allows us to compare Williams (#16) with Virginia Tech (#69) doesn’t mean that those 53 spaces mean anything at all.

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Grit and Galton: Is psychological research into traits inherently problematic?

Is all psychological research on individual differences racist?

Can psychologists ever separate our shameful past of scientific racism from the methods, techniques and questions that have grown from it?

A recent post criticizing the concept of “grit” (and Angela Duckworth, the researcher responsible for its popularization) made me consider these questions. While grit might be a specific research topic in psychology, it offers a useful case study in how findings in psychology get applied to education and policy settings.

The author of the post in question, Lauren Anderson, an education professor at Connecticut College, recounts discovering that Duckworth was awarded a MacArthur genius grant, and was disturbed as she read more about the roots of grit. From reading the research statement on Duckworth’s website, Anderson sees only one scholar mentioned in the first paragraph: Francis Galton, the father of eugenics.

With that, Anderson lays out what is essentially a guilt-by-association set of questions about the connection between Duckworth and Galton:

“What are we to make of a 2013 “genius” award winner quoting unproblematically the ‘founding father’ of eugenics in the opening paragraph of her research statement, even as her research engages young people of color?”

First, I am going to fully defend Duckworth herself, and any researchers of individual differences (who are also painted as “problematic” with this broad brush). But second, I am going to return to Anderson’s perspective, and try to see how it reflects neither ill-intentioned character assassination, nor intellectual laziness, but rather disciplinary differences, and a split between how people define science.

For the defense: here is Duckworth’s opening paragraph of the research statement:

The Duckworth Lab focuses on two traits that predict success in life: grit and self-control. Grit is the tendency to sustain interest in and effort toward very long-term goals. Self-control is the voluntary regulation of behavioral, emotional, and attentional impulses in the presence of momentarily gratifying temptations or diversions. On average, individuals who are gritty are more self-controlled, but the correlation between these two traits is not perfect: some individuals are paragons of grit but not self-control, and some exceptionally well-regulated individuals are not especially gritty. While we haven’t fully worked out how these two traits are related, it seems that an important distinction has to do with timescale: As Galton (1892) suggested, the inclination to pursue especially challenging aims over months, years, and even decades is distinct from the capacity to resist “the hourly temptations,” pursuits which bring momentary pleasure but are immediately regretted.

It is clear that Duckworth’s work focuses on traits. There is a great deal of modern research on personality psychology that focuses on individual differences in traits. Some people are shy, some people are outgoing, some people are messy, others are fastidious. The research questions are often framed as Duckworth does above. Are there fundamental and relatively stable personality traits? How are they related? How is shyness related to introversion? What kinds of future behavior can personality models predict? Here, in Duckworth’s opening paragraph, Galton is quoted with a very specific claim: there are two kinds of self-control, separated by time scale. One is the ability to resist an immediate momentary pleasure, and another that helps one to pursue a goal over years and decades. What makes Jiro dream of sushi, while some college students dream of pizza and video games?

But much of the research on traits began with white male researchers that were avowed racists. Galton is but one, there is Karl Pearson, a mathematician, pioneer of statistics, and one who saw eugenics as a natural outgrowth of his work on measurement and analysis of individual differences:

“History shows me one way, and one way only, in which a high state of civilization has been produced, namely, the struggle of race with race, and the survival of the physically and mentally fitter race. If you want to know whether the lower races of man can evolve a higher type, I fear the only course is to leave them to fight it out among themselves, and even then the struggle for existence between individual and individual, between tribe and tribe, may not be supported by that physical selection due to a particular climate on which probably so much of the Aryan’s success depended.”

And many of the early trait researchers also did research on individual differences in cognitive ability (or intelligence), which was also often bound up in racism. But does this mean that all trait research is stained? Was eugenics itself a bad seed, as it were, leading to an infected tree of modern trait research?

Absolutely not. If Galton said that some people are more shy than others, would shyness researchers be prohibited from “unproblematically” citing him? Of course not. Galton invented the dog whistle, and we don’t see any racist undertones with that. What’s more, we don’t condemn the transistor simply because its co-inventor, William Shockley, used the credibility granted by his Nobel Prize in Physics in 1956 to embark on an effort to apply the science of intelligence to improving human population through eugenics.

In reading Duckworth’s research statement, Anderson bemoans the “familiar-sounding narrative deployed to rationalize a turn toward individualistic, “objective measures.” But instead, she is simply reading about the existence of an area of psychology research into individual differences, whether they be neuroticism, intelligence, shyness or openness. Of course people are affected by the environments they were raised in and the situation they currently find themselves in. But individual differences exist, and studying them and invoking those who have studied them in the past, does not make one a racist. This is not a “turn toward individualistic objective measures” but an effort to study the dimensions of how people are different from each other. A complete disavowal of the role of individual differences plants us in another moment in psychology’s past, with Watson, Skinner and radical behaviorism, which of course has its own successes, failures, and interesting utopian theories.

Now I am going to step back a moment and consider why Anderson might have seen grit and Galton as problematic, but also the way in which I can agree that the application of the science of grit can actually be racist, even if the science itself is not. As I see it, Anderson sees Galton’s theories as far more coherent than any modern psychologist, including Duckworth, would. She seems to ascribe special meaning to the fact that the quoted section of Galton comes from a book which also has a section on the comparative worth of different races. If one sees Galton as a theorist, as a scientist devoted to forming a coherent, unifying, comprehensive view of human psychology, then each thread is connected to every other thread. Pull on the self-control thread long enough, you will see that it is connected to racist ideology.

However, this is clearly not how many modern psychologists treat Galton, or many of our other pioneers. They made a set of observations, sometimes connected to a theory, sometimes not. Pull on the dog whistle thread, and what do you get? A better understanding of the limits of the human ear, and how it ages. That’s it. For a unified theory of self-control, we might have to include some of Galton’s observations, but also Julian Rotter, Albert Bandura, Walter Miscel, Carol Dweck or Ellen Langer among many others. Put simply, we don’t have a model of how traits, attitudes, beliefs and situations interact. It is too complicated. Simply because we have a lack of a unified theory of human behavior does not mean that psychology isn’t a science. We do have sets of observations on ways in which each of these matter. The person matters, but so does the situation.

So where do I agree with Anderson? Duckworth has collected data showing that

For example, in prospective longitudinal studies, grit predicts final ranking at the Scripps National Spelling Bee, persistence at the U.S. Military Academy at West Point, and graduation from Chicago public high schools over and beyond standardized achievement test scores; likewise, self-control predicts report card grades and improvements in report card grades over time better than measured intelligence

So one’s success in these school situations (and spelling bees) is due more to what we might call “non-cognitive” factors (things that are not measured by traditional intelligence tests) than by cognitive ability. So at least within these contexts, hard work works. Of course, intelligence tests still do explain some variation (it helps to have high cognitive ability) but non-cognitive factors explain more. But we shouldn’t stop there.

I agree with Anderson that we should be careful and skeptical about applying these findings to school policy settings. Because if we take “hard work works” too far, it becomes a just-world fallacy, and blames those who haven’t succeeded for not working hard enough. If Sally wins the Spelling Bee because she was grittier than Tommy, then does one school succeed because it is better at imparting grit? Do schools fail because they don’t successfully transmit grit? Of course it isn’t that simple, nor would Duckworth say it is. She is interested in her little piece of the causes of success. This does not mean that she thinks social structures doesn’t exist, or poverty doesn’t exist, or racism doesn’t exist, just that she is studying something else. The problem becomes when school policy tilts to far in one direction, ignoring others. Students need more practice reading? Skip recess. I’m sorry, but reading researchers are not responsible for short-sighted school administrators who think that 1st graders don’t need recess every day.

Research psychologists such as Duckworth would do well to understand the context (and yes, the narratives) that can drive public acceptance and promotion of their science. But equally, policymakers and interpreters of psychological science should seek to situate the scientific evidence within both its scientific context as well as its social and institutional context. The existence and power of traits does not deny the power of situational and motivational context.

I’ll close with a quote from TaNehisi Coates, which Paul Thomas (see an excellent post here on separating the grit narrative from grit research) saw as relating to grit:

There is no evidence that black people are less responsible, less moral, or less upstanding in their dealings with America nor with themselves. But there is overwhelming evidence that America is irresponsible, immoral, and unconscionable in its dealings with black people and with itself. Urging African-Americans to become superhuman is great advice if you are concerned with creating extraordinary individuals. It is terrible advice if you are concerned with creating an equitable society. The black freedom struggle is not about raising a race of hyper-moral super-humans. It is about all people garnering the right to live like the normal humans they are.

I would rephrase Coates’ distinction between superhuman African-Americans and basic justice. Personality and individual difference researchers might be interested in what makes African-Americans (or any other human beings) different from each other, not necessarily superhuman. I agree that it is terrible advice for creating an equitable society, but I am ok with scientists studying things that don’t necessarily and immediately lead to an equitable society. I find fault with policymakers, who should be in the business of improving social equity (and justice), but instead act as if they can’t because people are different from one another. Policymakers should not seek to improve (or blame) individuals, but rather focus on improving their social circumstances. Duckworth is not in charge of healthy school lunches, or equal resources across schools, or improving teachers working conditions, nor would she deny that these things matter. Duckworth and fellow psychological researchers should be free to investigate the vast diversity of influences on human behavior, including cognitive ability, self control and other traits, but school officials and policy makers shouldn’t act as if grit is a magic bullet.

Posted in education, psychology, research, science | Tagged , , , , | 8 Comments