Field of Science

Doing your homework

I just finished a radio interview about birth order.

Apparently not very much research goes into booking guests for radio & TV shows. Lately, I've been getting at least one interview request a month to talk about birth order. And every time they are disappointed that I can't tell them about how birth order affects personality, that there's little evidence to suggest it does. They *wouldn't* be surprised if they read *anything* that I had written or said on the topic. (Well, except for that FOX interview, which was edited to make it look like I said the exact opposite of what I actually said.)

It's been making me think I should do more birth order research, just so I have something to say at these interviews.

Calling all citizen scientists

SciStarter would like to know more about your experiences with Citizen Science. They are running a survey (here) in preparation for a workshop at the Citizen CyberScience Summit in London next month.

More Citizens, More Science

For the last couple years, most articles about Citizen Science -- in which amateurs contribute to scientific projects -- have been hagiography. These articles were nearly exclusively Ra! Ra!, all about the exciting new development.

It seems that we've matured a bit as a field, because lately I've run across a couple articles that, while still being positive overall, have laid out some real criticism. For instance, in an article in Harvard Magazine, Katherine Xue concludes with the worry that citizen science may be less about involving the public and more about cheap labor (full disclosure: I was interviewed for and appear in this article). Many citizen science projects, she notes, are little more than games or, worse, rote labor, with little true engagement for the volunteer in the scientific mission.

Similarly, in a much-tweeted article at The Guardian, Michelle Kilfoyle and Hayley Birch write, "Who really benefits the most from [citizen science]: the amateurs or the professionals? … Most well-known initiatives are the big crowdsourcing projects: big on the number of participants but not necessarily the level of participation."

Introducing the VerbCorner Forum

These articles resonated with me. Ever since we launched VerbCorner, our citizen science project looking at the structure of language, meaning, and thought, we've wanted to find additional ways to get our volunteers involved in the science and get more out of participation. VerbCorner is very much a crowdsourcing project -- most of what volunteers do on the site is contribute labor. We've always had this blog, where people could learn more about the project, but that's not especially interactive.

To that end, we've added a forum where anyone and everyone involved in the project can discuss the project, offer suggestions, debate the science, and discuss anything related (syntax, semantics, etc.). We have high hopes for this forum. Over the years, I have gotten a lot of emails from participants in the various projects at, emails with questions about the projects, ideas for new experiments, and -- all too often -- reports of bugs or type-os. These emails have been extremely useful, and in a few cases have even led to entirely new research directions. But email is a blunt instrument, and I expect that for everyone who has emailed, at least ten others had similar comments but never got around to tracking down our email address.

I hope to see you on the forum!

A Great Year for

Unique visitors at were up 76% in 2013 over the previous year. That's after several years of fairly steady traffic.

Meanwhile, two journal papers and a conference paper involving data collected at were accepted (and two more are currently under review). Many thanks to everyone who participated and otherwise helped out!

Results (Round 1): Crowdsourcing the Structure of Meaning & Thought

Language is a device for moving a thought from one person's head into another's. This means to have any real understanding of language, we also need to understand thought. This is what makes work on language exciting. It is also what makes it hard.

With the help of over 1,500 Citizen Scientists working through our VerbCorner project, we have been making rapid progress.

Grammar, Meaning, & Thought

You can say Albert hit the vase and Albert hit at the vase. You can say Albert broke the vase but you can't say Albert broke at the vase. You can say Albert sent a book to the boarder [a person staying at a guest house] or Albert sent a book to the border [the line between two countries], but while you can say Albert sent the boarder a book, you can't say Albert sent the border a book. And while you say Albert frightened Beatrice -- where Beatrice, the person experiencing the emotion, is the object of the verb -- you must say Beatrice feared Albert -- where Beatrice, the person experiencing the emotion, is now the subject.

How do you know which verb gets used which way? One possibility is that it is random, and this is just one of those things you must learn about your language, just like you have to learn that the animal in the picture on the left is called a "dog" and not a "perro", "xiaogou," or "sobaka." This might explain why it's hard to learn language -- so hard that non-human animals and machines can't do it. In fact, it results in a learning problem so difficult that many researchers believe it would be impossible, even for humans (see especially work on Baker's Paradox).

Many researchers have suspected that there are patterns in terms of which verbs can get used in which ways, explaining the structure of language and how language learning is possible, as well as shedding light on the structure of thought itself. For instance, the difference (it is argued) between Albert hit the vase and Albert hit at the vase is that the latter sentence means that Albert hit the vase ineffectively. You can't say Albert broke at the vase because you can't ineffectively break something: It is either broken or not. The reason you can't say Albert sent the border a book is that this construction means that the border owns the book, which a border can't do -- borders aren't people and can't own anything -- but a boarder can. The difference between Albert frightened Beatrice and Beatrice feared Albert is that the former describes an event that happened in a particular time and place (compare Albert frightened Beatrice yesterday in the kitchen with Beatrice feared Albert yesterday in the kitchen).

When researchers look at the aspects of meaning that matter for grammar across different languages, many of the same aspects pop up over and over again. Does the verb describe something changing (break vs. hit)? Does it describe something only people can do (own, know, believe vs. exist, break, roll)? Does it describe an event or a state (frighten vs. fear)? This is too suspicious of a pattern to be accidental. Researchers like Steven Pinker have argued that language cares about these aspects of meaning because these are basic distinctions our brain makes when we think and reason about the world (see Stuff of Thought). Thus, the structure of language gives us insight into the structure of thought.

The Question

The theory is very compelling and is exciting if true, but there are good reasons to be skeptical. The biggest one is that there simply isn't that much evidence one way or another. Although a few grammatical constructions have been studied in detail (in recent years, this work has been spearheaded by Ben Ambridge of the University of Liverpool), the vast majority have not been systematically studied, even in English. Although evidence so far suggests that which verbs go in which grammatical constructions is driven primarily or entirely by meaning, skeptics have argued that is because researchers so far have focused on exactly those parts of language that are systematic, and that if we looked at the whole picture, we would see that things are not so neat and tidy.

The problem is that no single researcher -- nor even an entire laboratory -- can possibly investigate the whole picture. Checking every verb in every grammatical construction (e.g., noun verb noun vs. noun verb at noun, etc.) for every aspect of meaning would take one person the rest of her life.

CrowdSourcing the Answer

Last May, VerbCorner was launched to solve this problem. For the first round of the project, we posted questions about 641 verbs and six different aspects of meaning. By October 18th, 1,513 volunteers had provided 117,584 judgments, which works out to 3-4 people per sentence per aspect of meaning. That was enough data to start analyzing.

As predicted, there is a great deal of systematicity in the relationship between meaning and grammar (for details on the analysis, see the next section). These results suggest that the relationship between grammar and meaning may indeed be very systematic, helping to explain how language is learnable at all. It also gives us some confidence in the broad project of using language as a window into how the brain thinks and reasons about the world. This is important, because the mind is not easy to study, and if we can leverage what we know about language, we will have learned a great deal. As we test more verbs and more aspects of meaning -- I recently added an additional aspect of meaning and several hundred new verbs -- that window will be come clearer and clearer.

Unless, of course, it turns out that not all of language is so systematic. While our data so far represent a significant proportion of all research to date, it's only a tiny fraction of English. That is what makes research on language so hard: there is so much of it, and it is incredibly complex. But with the support of our volunteer Citizen Scientists, I am confident that we will be able to finish the project and launch a new phase of the study of language.

That brings up one additional aspect of the results: It shows that this project is possible. Citizen Science is rare in the study of the mind, and many of my colleagues doubted that amateurs could provide reliable results. In fact, by the standard measures of reliability, the information our volunteers contributed is very reliable.

Of course, checking for a systematic relationship between grammar and meaning is only the first step. We'd also liked to understanding which verbs and grammatical constructions have which aspects of meaning and why, and leverage this knowledge into understanding more about the nature of thought. Right now, we still don't have enough data to have exciting new conclusions (for exciting old conclusions, see Pinker's Stuff of Thought). I expect I'll have more to say about that after we complete the next phase of data collection.

Details of the Analysis

Here is how we did the analyses. If meaning determines which grammatical constructions a given verb can appear in, then you would expect that all the verbs that appear in the same set of frames should be the same in terms of the core aspects of meaning discussed above. So if one of those verbs describes, for instance, physical contact, then all of them should.

Helpfully, the VerbNet project -- which was built on earlier work by Beth Levin -- has already classified over 6,000 English verbs according to which grammatical constructions they can appear in. The 641 verbs posted in the first round of the VerbCorner project consisted of all the verbs from 11 of these classes.

So is it the case that in a given class, all the verbs describe physical contact or all of them do not? One additional complication is that, as I described above, the grammatical construction itself can change the meaning. So what I did was count what percentage of verbs from the same class have the same value for a given aspect of meaning for each grammatical construction, and then I averaged over those constructions.

The "Explode on Contact" task in VerbCorner asked people to determine whether a given sentence (e.g., Albert hugged Beatrice) described contact between different people or things. Were the results for a given verb class and a given grammatical construction? Several volunteers checked each sentence. If there was disagreement among the volunteers, I used whatever answer the majority had chosen.

This graph shows the degree of consistency by verb class (the classes are numbered according to their VerbNet number), with 100% being maximum consistency. You can see that all eleven classes are very close to 100%. Obviously, exactly 100% would be more impressive, but that's extremely rare to see when working with human judgments, simply because people make mistakes. We addressed this in part by having several people check each sentence, but there are so many sentences (around 5,000), that simply by bad luck sometimes several people will all make a mistake on the same sentence. So this graph looks as close to 100% as one could reasonably expect. As we get more data, it should get clearer.

Results were similar for other tasks. Another one looked at whether the sentence described someone applying force (pushing, shoving, etc.) to something or someone else:
Maybe everything just looks very consistent? We actually had a check for that. One of the tasks measures whether the sentence describes something that is good, bad, or neither. These is no evidence that this aspect of meaning matters for grammar (again, the hypothesis is not that every aspect of meaning matters -- only certain ones that are particularly important for structuring thought are expected to matter). And, indeed, we see much less consistency:
Notice that there is still some consistency, however. This seems to be mostly because most sentences describe something that is neither good nor bad, so there is a fair amount of essentially accidental consistency within each verb class. Nonetheless, this is far less consistency that what we saw for the other five aspects of meaning studied.

Citizen Science in Harvard Magazine

A nice, extended article on recent projects, covering a wide range -- including Check it out.

Science Mag studies science. Forgets to include control group.

Today's issue of Science carries the most meta sting operation I have ever seen. John Bohannon reports a study of open access journals, showing lax peer review standards. He sent 304 fake articles with obvious flaws to 304 open access journals, more than half of which were accepted.

The article is written as a stinging rebuke of open access journals. Here's the interesting thing: There's no comparison to traditional journals. For all we know, open access journals actually have *stricter* peer review standards than traditional journals. We all suspect not, but suspicion isn't supposed to count as evidence in science. Or in Science.

So this is where it gets meta: Science -- which is not open access -- published an obviously flawed article about open access journals publishing obviously flawed articles.

It would be even better if Bohannon's article had run in the "science" section of Science, rather than in the news section, where it actually ran, but hopefully we can agree that Science can't absolve itself of checking its articles for factualness and logical coherence just by labeling them "news".


I have never been good at coming up with titles for articles. When writing for newspapers or magazines, I usually leave it up to the editor. There is some danger that comes with this, however.

Last week, I wrote a piece for Scientific American about similarities across languages. This piece was then picked up by Salon, which re-ran the article under a new title:
Chomsky's "Universal Language" is incomplete. Chomsky's theory does not adequately explain why different languages are so similar.
I agree that this is snappier than any title I would have come up with. It's also perhaps a bit snappier than the one Scientific American used. It's also dead wrong. For one, there is no such thing as Chomsky's "Universal Language." Or if there is, presumably it is love. Or maybe mathematics. Or maybe music. The term is "Universal Grammar."

If you squint, the subtitle isn't exactly wrong. In the article, I do claim that standard Universal Grammar theory's explanation of similarities across languages isn't quite right. But the title implies that UG suggests that languages are not that similar, whereas the real problem with UG is that -- at least on standard interpretations -- it suggests that languages should be more similar than they actually are.

I sent in a letter to "corrections" at Salon, and the title has now been switched to something more correct. The moral of the story? Apparently writing good titles really is just very hard.

GamesWithWords on Scientific American

Over the last week, has published two articles by me. The most recent, "Citizen Scientists decode meaning, memory and laughter," discusses how citizen science projects -- science projects involving collaborations between professional scientists and amateur volunteers -- are now being used to answer questions about the human mind.

Citizen Science – projects which involve collaboration between professional scientists and teams of enthusiastic amateurs — is big these days. It’s been great for layfolk interested in science, who can now not just read about science but participate in it. It has been great for scientists, with numerous mega-successes like Zooniverse and Foldit. Citizen Science has also been a boon for science writing, since readers can literally engage with the story.
However, the Citizen Science bonanza has not contributed to all scientific disciplines equally, with many projects in zoology and astronomy but less in physics and the science of the mind. It is maybe no surprise that there have been few Citizen Science projects in particle physics (not many people have accelerators in their back yards!), but the fact that there has been very little Citizen Science of the mind is perhaps more remarkable.

The article goes on to discuss three new mind-related citizen science projects, including our own VerbCorner project.

The second, "How to understand the deep structures of language," describes some really exciting work on how to explain linguistic universals -- work that was conducted by colleagues of mine at MIT.
In an exciting recent paper, Ted Gibson and colleagues provide evidence for a design-constraint explanation of a well-known bias involving case endings and word order. Case-markers are special affixes stuck onto nouns that specify whether the noun is the subject or object (etc.) of the verb. In English, you can see this on pronouns (compare "she talked with her"), but otherwise, English, like most SVO languages (languages where the typical word order is Subject, Verb, Object) does not mark case. In contrast, Japanese, like most SOV languages (languages where the typical word order is Subject, Object, Verb) does mark case, with -wa added to subjects and -o added to direct objects. "Yasu saw the bird" is translated as "Yasu-wa tori-o mita" and "The bird saw Yasu" is translated as "Tori-wa Yasu-o mita." The question is why there is this relationship between case-marking and SOV word order.
The article ran in the Mind Matters column, which invites scientists to write about the paper that came out in the last year that they are most excited about. It was very easy for me to choose this one.

Language and Memory Redux

One week only: If you did not do our Language and Memory task when it was running earlier this year, now is your chance. We just re-launched it to collect some additional data.

I expect we'll have enough data without a week to finish this line of studies, rewrite the paper (this is a follow-up experiment that was requested by peer reviewers), and also post the full results here.

Вы понимаете по-русски?

У нас новый русский эксперимент. Большинство психолингвистов занимаются английским. Мы хотим узнать больше об остальних. Не волнуйтесь -- я не сам перевёл эксперимент. Перевела его настоящая рускоязычная!

If you didn't understand that, that's fine. We're recruiting participants for a new experiment in Russian. Apparently you aren't eligible. :)

Much of the research on language is done on a single language: English. In part, that's because many researchers happen to live in English-speaking countries. The great thing about the Internet is we are freed from the tyranny of geography.

One week left to vote

There is less than a week left to vote for our panel at SXSW -- or to leave comments (apparently comments are weighted more heavily than mere votes). 

There is less than a week left to vote for our panel at SXSW -- or to leave comments (apparently comments are weighted more heavily that mere votes). So if you want to support our work in improving psychology and the study of the mind & language, please go vote.

Go to this link to create an SXSW account:
Then go to this link and click on the thumb’s up (on the left under “Cast Your Vote”) to vote for us:
You can read more about our proposal at the SXSW site, as well as here.

Who knows more words? Americans, Canadians, the British, or Australians?

I have been hard at work on preliminary analyses of data from the the Vocab Quiz, which is a difficult 32 word vocabulary test. Over 2,000 people from around the world have participated so far, so I was curious to see which of the English-speaking nationalities was doing best.

Since the test was made by an American (me), you might expect Americans to do best (maybe I chose words or definitions of words that are less familiar to those in other countries). Instead, Americans (78.4% correct) are near the bottom of the heap, behind the British (79.8%), New Zealanders (82.2%), the Irish (80.1%), South Africans (83.9%), and Australians (78.6% -- OK that one is close). At least we're beating the Canadians (77.4%).

A fluke?

Maybe that was just bad luck. Plus, some of those samples are small -- there are fewer than 10 folks from New Zealand so far. So I pulled down data from the Mind Reading Quotient, which also includes a (different) vocabulary test. Since the Mind Reading Quotient has been running longer, there are more participants (around 3,000). The situation was no better: This time, we weren't even beating the Canadians. 

Maybe this poor showing was due to immigrants in America who don't know English well? Sorry -- the above results only include people whose native language is English. 

I also considered the possibility  that maybe Americans are performing poorly because I designed the tests to be hard, inadvertently including worse that are rare in America but common elsewhere. But the consistency of results across other countries makes that seem unlikely: What do the British, New Zealanders, Irish, South Africans and Australians all know that we don't? This hypothesis suggests that the poor showing by Americans is due to one or two items in particular. Right now there isn't enough data to do item-by-item analyses, but once we have more. Which brings me to...

Data collection continues

If you want to check how good your vocabulary is compared to everyone else who has taken the test -- and if you haven't done so already -- you can take the Vocab Quiz here. At the Mind Reading Quotient, you can test your ability to understand other people -- to read between the lines.


Phytophactor asks whether these results are significant. In the MRQ data, all the comparisons are significant, with the exception of US v. Canada (which went the other direction in the Vocab Quiz data anyway). The comparison with Australia is a trend (p=.06). See comments below for additional details. I did not run the stats for Vocab Quiz.

Children don't always learn what you want

Someone has not been watching his/her speech around this little girl.

It's clear she has some sense as to what the phrase means, but clearly she's got the words wrong. But she is treating this phrase as compositional (notice how she switches between "his" and "my").

One of my younger brothers went around for a couple months saying "ship" whenever anything bad happened. But unfortunately we don't have that on video.

Taking research out into the wild

Like others, we believe that science is a little bit WEIRD — much of research is based on a certain type of person, from a very specific social, cultural, and economic background (WEIRD stands for Western Educated Industrialized Rich Democratic; Henrich, Heine, Norenzayan, 2010).  We want to use the web and the help of citizen scientists to start changing that.  In the next few months, we will be launching an initiative called Making Science Less Weird (stay tuned).
As part of Making Science Less Weird, we have proposed a panel presentation at the SXSW conference next year.  Here, "we" includes the team at but also at and
In order to be selected, however, *we need votes*. To support Making Science Less Weird and help us increase diversity in human research, please go to this link to create an SXSW account:
Then go to this link and click on the thumb’s up (on the left under “Cast Your Vote”) to vote for us:
Thanks for your support!