Language fact of the day

The name that appears most often in Genesis is "Jacob", followed by "Joseph".

In other news, the most common word in Moby Dick is "the"; the most common noun (excluding pronouns) is, not surprisingly, "whale".

In Genesis, Moby Dick, and a number of other texts, three-letter words are more common than word of any other length (the one exception I've found so far is Moby Dick)

(Yes, I am learning to use NLTK, which so far I like a lot)

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Boston University Conference on Language Development: Day 3

This post continues my series on this years' BUCLD. While conferences are mostly about networking and seeing your friends, I also managed to attend a number of great talks.

Autism and homophones

Hugh Rabagliati got the morning started with a study (in collaboration with Noemi Hahn and Jesse Snedeker) of ambiguity (homophone) resolution. One of the better-known theories of Autism is that people with Autism have difficulty thinking about context (the "weak central coherence theory"). Rabagliati has spent much of his career so far looking at how people use context to interpret ambiguous words, so he decided to check to see whether people with Autism had any more difficulty than typically-developing folk. (Note that many people with Autism have general language delays. Presumably people with language delays will have trouble on language tasks. This work focused on people with Autism who have roughly normal syntax and semantics.)

Participants listened to sentences with homophones (e.g., "bat") that were either had very constraining contexts (e.g., "John fed the bat that he found in the forest") or not-very-constraining contexts (e.g., "John saw the bat that he found in the forest"). These sentences were part of a longer story. What the participant had to do was pick out a relevant picture (of four on the computer screen) for part of the story. The trick was that one of the pictures was related to the other meaning of the homophone (e.g., a baseball glove, which is related to a baseball bat). Due to priming, if people are thinking about that other meaning of the homophone (baseball bat), they are likely to spend some of their time looking at the picture related to that meaning (the baseball glove). If they have successfully determined that the homophone "bat" refers to the animal bat, they should ignore the glove picture. Which is exactly what happened. For both typically developing 6-9 year-olds and 6-9 year-olds with Autism. This is a problem for the weak central coherence theory.

Autism and prosody

In the same session, the Snedeker Lab presented work on prosody and Autism. This study, described by Becky Nappa, looked at contrast stress. Consider the following:

(1) "Look at the blue house. Now, look at the GREEN..."

What do you expect to come next? If you are like most people, you think that the next word is "house". Emphasizing "green" suggests that the contrast between the two sentences is the color, not the type of object to be looked at. Instead, if the color word was not stressed:

(2) "Look at the blue house. Now, look at the green..."

You don't know what is coming up, but it's probably not a house.

Atypical prosody is a diagnostic of Autism, at least according to some diagnostic criteria. That is, people with Autism often use prosody in unusual ways. But many of these folk have, as I pointed out above, general language difficulties. What about the language-intact Autism population? Here, the data has been less clear. There is still some unusual production of prosody, but that doesn't mean that they don't understand prosody.

Nappa and Snedeker tested children's understanding of contrastive stress. While typically-developing children performed as expected (interpreting contrastive stress as meaning a new example of the same type of object will be described), highly verbal children with Autism performed exactly opposite: they expected a new type of object for (1) and the same type of object for (2).

A second study looking at given/new stress patterns. Compare:

(3) Put the candle on the table. Now put the candle on the counter.
(4) Put the candle on the table. Now put the CANdy on the counter.

In general, if you are going to re-mention the same object ("candle" in (3)), you don't stress it the second time around. When you are mentioning a new object -- especially if its name sounds similar to something you have already described -- you are likely to stress it. Here, interestingly, the ASD children were just as good as typically-developing children.

Nappa puts these two findings together and suggest that children with Autism have overgeneralized the stress pattern in (3-4) to cases like (1-2). In general, they think stressed words refer to something new.

Other Day 3 talks

There were other good talks on Day 3, but by my notes always get more and more sparse as a conference goes on. Researchers from Johns Hopkins University (the speaker was Kristen Johannes) argued that "differences between child and adult spatial language have been previously attributed to underdeveloped conceptual representations" (this is a quote from the abstract). In particular, children use the preposition "on" in strange ways. They argue that this is because children have impoverished spatial vocabulary (there are a number of useful words they don't know) and, given that they don't have those words, they over-apply "on" not so much because they conceptualize of "on"ness differently, but because they are, literally, at a loss for words. When you make adults describe spatial arrangements without using the fancy adult words they normally use, they end up over-applying "on" in much the same way kids do. (Here I am working from memory plus the abstract -- my notes, as I mentioned, are incomplete).

Careful readers will notice that I haven't written about Day 2 yet. Stay tuned.

Boston University Conference on Language Development: Day 1

This year marks my 7th straight BUCLD. BUCLD is the major yearly language acquisition conference. (IASCL is the other sizable language acquisition conference, but meets only every three years; it is also somewhat more international than BUCLD and the Empiricist contingent is a bit larger, whereas BUCLD is *relatively* Nativist).

NOTE I'm typing this up during a break at the conference, so I've spent less time making these notes accessible to the general public than usual. Some parts may be opaque to you if you don't know the general subject matter. Feel free to ask questions in the comments.

Day 1 (Friday, Nov. 2)

What does eyetracking tell us about kid's sentence processing

The conference got off to a great start with Jesse Snedeker's 9am talk, "Negation in children's online language comprehension" (for those who don't know, there are 3 talks at any given time; no doubt the other two 9am talks were good, but I wasn't at them). I was actually more interested in the introduction than the conclusion. Over the last 15 years, the Visual World Paradigm has come to dominate how we study children's language processing. Here is how I usually describe the paradigm to participants in my studies: "People typically look at what is being talked about. So if I talk about the window, you'll probably automatically look at the window. So we can measure what people look at as they listen to sentences to get a sense of what they think the sentence is about at any given time."

Snedeker's thesis was that we actually don't know what part of language comprehension this paradigm measures. Does it measure your interpretation of individual words or of the sentence as a whole? One of the things about language is that words have meanings by themselves, but when combined into sentences, new meanings arise that aren't part of any individual word. So "book" is a physical object, but if I say "The author started the book", you likely interpret "book" as something closer to an activity ("writing the book") than a physical object.

Because the Visual World Paradigm is used extensively by sentence-comprehension people (like me), we hope that it measures sentence comprehension, not just individual words. Snedeker walked through many of the classic results from the Visual World Paradigm and argued that they are consistent with the possibility that the Visual World Paradigm just measures word meaning, not sentence meaning.

She then presented a project showing that, at least in some cases, the Visual World Paradigm is sensitive to sentence meaning, which she did by looking at negation. In "John broke the plate", we are talking about a broken plate, where as in "John didn't break the plate", we are not. So negation completely changes the meaning of the sentence. She told participants stories about different objects while the participants looked at pictures of those objects on a computer screen (the screen of an automatic eyetracker, which can tell where the participant is looking). For example, the story might be about a clumsy child who was carrying dishes around and broke some of them but not others (and so, on the screen, there was a picture of a broken plate and a picture of a not-broken plate). She found that adults and even children as young as three years old look at the broken plate when they heard "John broke the plate" but at the not-broken plate when they heard "John didn't break the plate", and they did so very quickly ... which is what you would expect if eyetracking was measuring your current interpretation of the sentence rather than just your current interpretation of the individual words (in which case, when you hear the word "plate", either plate will do).

(This work was joint work with Miseon Lee -- a collaborator of mine -- Tracy Brookhyser and Matthew Jiang.)

The First Mention Effect

W. Quin Yow of Singapore University of Technology and Design presented a project looking at pronoun interpretation (a topic close to my heart). She looked at sentences in which adults typically interpret the pronoun as referring to the previous subject (these are not the so-called "implicit causality" sentences I discuss most on this blog):

Miss Owl is going out with Miss Ducky. She wants her bag. 

She found, as usual, a strong preference for "she" to refer to Miss Owl in this (and similar) sentences. There is one older study that did not find such a preference in children roughly 4-6 years old, but several other studies have found evidence of (weak) first-mention effects in such sentences, including [shameless self-plug] work I presented at BUCLD two years ago.

Yow compared monolingual English-speaking four year-olds and bilingual English-speaking four year-olds (their "other" language differed from kid to kid). While only the bilinguals showed a statistically significant first-mention effect, the monolingual kids were only just barely not above chance and almost identical to the monolinguals. While the first-mention effects she saw were weaker than what I saw in my own work, her kids were slightly younger (four year-olds instead of five year-olds).

The additional twist she added was that, in some conditions, the experimenter pointed to one of the characters in the story at the moment she uttered the pronoun. This had a strong effect on how adults and bilingual children interpreted the pronoun; the effect was weaker or monolingual children, but I couldn't tell whether it was significantly weaker (with only 16 kids per group, a certain amount of variability between groups is expected).

In general, I interpret this as more evidence that young children do have (weak) first-mention biases. And it is nice to have one's results replicated.

Iconicity in sign language

Rachel Magid, a student of Jennie Pyers at Wellesley College, presented work on children's acquisition of sign language. Some signs are "iconic" in that they resemble the thing being referred to: for instance, miming swinging a hammer as the sign for "hammer" (I remember this example from the talk, but I do not remember whether that's an actual sign in ASL or any other sign language). Spoken languages have iconic words as well, such as "bark", which both means and sort of sounds like the sound a dog makes. This brings up an important point: iconic words/signs resemble the things they refer to, but not perfectly, and in fact it is often difficult to guess what they refer to, though once it has been explained to you, the relationship is obvious.

The big result was that four year-olds hearing children found it easier to learn iconic than non-iconic signs, whereas three year-olds did not. Similar results were found for deaf children (though if memory serves, the three year-old deaf children were trending towards doing better with iconic signs, though the number of subjects -- 9 deaf three year-olds -- was too small to say much about it).

Why care? There are those who think that early sign language acquisition -- and presumably the creation of sign languages themselves -- derives from imitation and mimicry (basically, sign languages and sign language acquisition start as a game of charades). If so, then you would expect those signs that are most related to imitation/mimicry to be the easiest to learn. However, the youngest children -- even deaf children who have learned a fair amount of sign language -- don't find them especially easy to learn. Why older children and adults *do* find them easier to learn still requires an explanation, though .

[Note: This is my interpretation of the work. Whether Magid and Pyers would endorse the last paragraph, I am not sure.]

Briefly-mentioned

Daniele Panizza (another occasional collaborator of mine) presented work done with a number of folks, including Stephen Crain, on 3-5 year-olds' interpretations of numbers. The question is whether young children understand reversals of entailment scales. So, if you say "John has two butterflies", that means that you do not have three, whereas saying "If John has two butterflies, give him a sticker" means that if he has two OR MORE butterflies, give him a sticker [NOTE, even adults find this "at least two" reading to be a bit iffy; the phenomenon is that they find the "at least two" reading much better in a downward-entailing context like a conditional MUCH BETTER than in a normal declarative]. Interestingly, another colleague and I had spent a good part of the last week wondering whether children that age understood this, so we were happy to learn the answer so quickly: they do.

In the next talk, Einat Shetreet presented work with Julia Reading, Nadine Gaab and Gennaro Chierchia also looking at entailment scales, but with scalar quantifiers rather than numerals. Adults generally think "John ate some of the cookies" means that he did not eat all of them (some = some but not all), whereas "John didn't eat all of the cookies" means that he ate some of them (not all = some). They found that six year olds also get both of these inferences, which is consistent with the just-mentioned Panizza study.

These studies may seem esoteric but get at recent theories of scalar implicature. Basically, theories of scalar implicature have been getting much more complex recently, suggesting that this relatively simple phenomenon involves many moving pieces. Interestingly, children are very bad at scalar implicature (even up through the early elementary years, children are much less likely to treat "some" as meaning "some but not all", so they'll accept sentences like "Some elephants have trunks" as reasonable sentences, whereas adults tend to find such sentences quite odd). So the race is on to figure out which of the many component parts of scalar implicature are the limiting step in early language acquisition.

There were many other good talks on the first day; these merely represent those for which I have the most extensive notes. 

Maybe first-borns aren't smarter after all

Although it is conventional wisdom that your birth order affects your personality, it's a hotly-disputed topic among scientists, and in fact my sense is that, if anything, a majority of researchers doubt the existence of birth order effects. Findings have been slippery: one study suggests that, for instance, first-borns are risk-takers, whereas another suggests that they aren't.

Birth Order & Intelligence

One of the most-researched topics has been intelligence: A wide variety of studies have suggested that first-borns have higher IQ scores than later-borns. While not every study has shown this, Bjerkedal and colleagues published in 2007 what seemed to be the definitive proof. They looked at IQ tests for 250,000 Norwegian male conscripts born from 1967 to 1988 -- that's more than 80% of all Norwegian men born in that time period -- and found first-born sons have IQs of about 2.3 points higher than second-born sons.

Because of the size and completeness of this dataset, they were able to rule out various possible confounds in the data that have been sources of controversy in previous studies. For instance, because wealthy, well-educated families rarely have more than two children, simply being a middle child correlates with being less wealthy and having less access to quality education (and health care, etc.). So one might find that middle children have lower IQs, when in fact what you are measuring is not an effect of birth order, but of socio-economic status. Bjerkedal and colleagues were able to control for such factors.

The Flynn Effect

But, as Satoshi Kanazawa of the London School of Economics points out in a recent paper, there was one confound that they didn't consider: the Flynn Effect. Over the last hundred years -- and possibly longer -- the average person has been doing better and better on IQ tests. In fact, this is something that Bjerkedal and colleagues noticed in their own data, with IQ scores rising slightly from 1984 (the first year of their study) to the mid 1990s.

Because of this, IQ test manufacturers have been constantly raising the bar: you have to get more questions right to get an IQ of 100 now than you did fifty years ago. (What has caused the Flynn effect is one of the Big Questions in current research and a topic for a much longer post.) And Bjerkedal and colleagues did the same thing:

To minimize these variations, scores were standardized by calculating deviations from an overall mean score of 5.00 for each calendar year and age.

The idea is that your score is based not on how many questions you got right, but how many questions you got right compared with everyone else who took the IQ test in the same year. Kanazawa points out that this is a confound: The average performance was higher in the 1990s than in the 1980s. So if two people who took the test in 1985 and 1995 answered the exact same questions correct, the one who took it in 1995 would have a lower IQ than the one who took it in 1985. This means that if you compare two siblings, the older sibling will -- all else equal -- have a higher IQ score than the younger sibling.

Caveats

There is one limitation to Kanazawa's story. While Bjerkedal and colleagues report that the average score did increase from 1985 through the early 1990s, they report that the scores then decreased back down to the original level between 1998 and 2002 (the study ended in 2004). Also, the increase was very small (one 1 IQ point) compared to the birth order effect that they reported (a drop of 1-2 IQ points for each older brother). So whether the Flynn effect is sufficient to explain away the Bjerkedal results is hard to say.*

Nonetheless, Kanazawa has one more card up his sleeve: his own study, Kanazawa looked at un-scaled data from IQ tests given to 17,419 children in the UK, finding no effect of birth order on intelligence.

That said, the statistical analyses are complicated, involving several transformations. While the transformations seems reasonable (mostly PCA), the transformations Bjerkedal used also seemed reasonable until we realized that they weren't. I'd like to see that Kanazawa's null effect holds up on the truly raw data as well.

Conclusions

Birth order effects are interesting scientifically because they get at the following question: How does your home environment affect the person you become, if at all? Many of the leading minds today suspect that your home environment has little to no effect on you, at least not in the long term. Birth order effects are a very useful test case. Relatively little theoretical rides on whether oldest siblings are the smartest or youngest siblings are the smartest, but if you could show that birth order affected intelligence, that would be a proof-of-concept that home environment affects the adult you become.

[BTW Nobody doubts that home environment has a strong impact on future income, level of educational achievement, etc. The question is whether it affects your personality, making you introverted or extroverted, etc.]

If the intelligence data do not hold up, that leaves -- to my knowledge -- no direct measures of personality or cognitive function for which we have solid evidence that they are affected by birth order. There is one indirect measure that, to my knowledge, has never been challenged: people tend to be friends with and marry others of the same birth order (some of the evidence came from studies run at gameswithwords.org -- thank you to all who participated). Since we know that people marry others with similar personalities (on average), a plausible explanation is that people with similar birth order have similar personalities, leading them to marry one another. However, the fact that no one has thought of another explanation doesn't mean that there isn't one. Time will tell.

See also: My review of birth order effects for SciAm Mind from 2010.

*Bjerdekal and colleagues renormalized a 9-point scaled score. I cannot tell from the article whether than 9-point scale itself was based on standardized norms -- though most likely it was -- and whether those norms were re-standardized during the 21 years of the study.

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Kanazawa, S. (2012). Intelligence, Birth Order, and Family Size Personality and Social Psychology Bulletin, 38 (9), 1157-1164 DOI: 10.1177/0146167212445911

Poll: What interests you?

Survey results: Where do you get your science news

The last poll asked people where they get their science news. Most folks reported that they get science news from blogs, which isn't surprising, since they were reading this blog. Interestingly, less than 10% reported getting science news from newspapers. This fits my own experience; once I discovered science blogs, I stopped reading science news in newspapers altogether.

I would report the exact numbers for the poll, but Blogger ate them. I can tell that it still has all the data (it remembers that I voted), but is reporting 0s for every category. I'll be switching to Google Forms for the next survey.

What you missed on the Internet last week: 10/29/2012

What is the oldest linguistics department in the USA?
Language Log tries to figure it out. And out. This is more interesting than it sounds.

Oppan Chomsky Style
MIT students remake the world's most famous Korean music video. Chomsky cameos.


Are the McArthur Fellowships the world's most clever marketing scheme?
The Lousy Linguist wants to know.

Mitt Romney's speech patterns
Mark Liberman of Language Log analyzes the presidential hopeful's disfluencies.

If I'm not looking at you, you can't see me
According to children at the University of Cambridge. 

Faster fMRI?

A paper demonstrating a new technique for "ultrafast fMRI" has been getting some buzz on the blogosphere. Although movies often depict fMRI showing real-time activity in the brain, in fact typical methods only collect from one slide of the brain at a time, taking a fair amount of time to cover the entire brain (Neuroskeptic puts this at about 2-3 seconds). This new technique (GIN) can complete the job in 50 ms, and without sacrificing spatial resolution (which is the great advantage of fMRI relative to other neuroimaging techniques like EEG or MEG).

Does this mean fMRI is about to get 50 times faster?

Not exactly. What fMRI is measuring is the change in blood oxygenation in areas of your brain. When a particular area starts working harder, more oxygen-rich blood is sent in its direction, and that can be detected using MRI. The limitation is that it takes a while for this blood to actually get there (around 5-10 seconds). One commenter on the Neuroskeptic post (which is where I heard about this article) wrote "making fMRI 50 times faster is like using an atomic clock to time the cooking of a chicken."

The basic fact is that fMRI is never going to compete with EEG or MEG in terms of temporal resolution, because the latter directly measure the electrical activity in the brain and can do so on very fine time-scales. But that doesn't mean that speeding up fMRI data acquisition isn't a good idea. As the authors of the paper write:

fMRI studies, especially related to causality and connectivity, would benefit from reduced repetition time in terms of better statistics and physiological noise characteristics...

They don't really say *how* these studies would achieve this benefit. The rest of the discussion is mostly about how their technique improves on other attempts at ultra-fast fMRI, which tend to have poor spatial resolution. They do mention that maybe ultra-fast fMRI would help simultaneous EEG-fMRI studies to strengthen the link between the EEG signal and the fMRI signal, but it's obvious to me just how helpful this would be, given the very different timing of EEG and fMRI.

But that's not going to stop me from speculating as to how faster data-acquisition might improve fMRI. (Any readers who know more about fMRI should feel free to step in for corrections/additions).

Speculations

The basic problem is that what you want to do is model the hemodynamic response (the change in blood oxygenation levels) due to a given trial. This response unfolds over a time-course of 5-10 seconds. If you are only measuring what is happening every couple seconds, you have pretty sparse data from which to reconstruct that response. Here's an example of some reconstructed responses (notice they seem to be sampling once every second or so):

Much faster data-collection would help with this reconstruction, leading to more accurate results (and conclusions). The paper also mentions that their technique helps with motion-correction. One of the basic problems in fMRI is that if somebody moves their head/brain even just a few millimeters, everything gets thrown off. It's very hard to sit in a scanner for an hour or two without moving even a smidge (one technique, used by some hard-core researchers, is a bite bar, which is perfectly fitted to your jaw and keeps you completely stabilized). Various statistical techniques can be used to try to mitigate any movement that happens, but they only work so well. The authors of the paper write:

Obviously, all InI-based and comparable imaging methods are sensitive to motion especially at the edges of the brain with possible incorrect estimation of prior information. However, due to the large amount of data, scan times are currently short (4 min in teh current study), which mitigates the motion problem.

I take this to mean that because their ultra-rapid scanning technique collects so much data from each trial, you don't need as many trials, so the entire experiment can be shortened. Note that they are focused on the comparison between their technique and other related techniques, not the comparison between their technique and standard fMRI techniques. But it does seem reasonable that more densely sampling the hemodynamic response for an individual trial should mean you need fewer trials overall, thus shortening experiments.

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Boyacioğlu, R., & Barth, M. (2012). Generalized iNverse imaging (GIN): Ultrafast fMRI with physiological noise correction Magnetic Resonance in Medicine DOI: 10.1002/mrm.24528

Is Dragon Dictate a believer?

I've been using Dictate to take notes on Talmy's Toward a Cognitive Semantics. One of the example sentences is as follows:

I aimed my gun into the living room. (p. 109)

I cannot by any means convince Dictate to print this. It prefers to convert "my gun" to "my God". For example, on my third try, it wrote:

I aim to my God into the living room.

Dictate offers a number of alternatives in case its initial transcription is incorrect. Right now, it is suggesting, as an alternative to "aim to my God":

aimed to my God
aim to my God and
aim to my god
aim to my gun
aimed to my God and
aim to my garden
aimed to my god
aimed to my gun
aim to my guide
aim to my God in
aimed to my God in 

Perhaps Nuance has a religious bent, but I suspect that this is a simple N-gram error. Like many natural language processing systems, Nuance figures out what word you are saying in part by reference to the surrounding words. So in general, it thinks that common bigrams (2-word sequences) are more likely than uncommon bigrams.

According to Google, "my god" appears on the Web 133,000,000 times, whereas "my gun" appears only 8,770,000 times. So "my god" is just much more likely. Similarly, "aim to" is fairly common (215,000,000) hits. So even though "aim to my God" is gibberish, the two components -- "aim to" and "my god" -- are fairly common, whereas the correct phrase -- "aimed my gun" -- is fairly rare (138,000 hits). (The bigram "aimed my" is also infrequent: 474,000 hits).

N-gram systems work better than most everything else, which is why Nuance, Google, and many other companies use them. But examples like this show their deep limitations, in that they make many obvious errors -- obvious to humans, anyway. In this case, because Nuance doesn't know what sentences mean, and doesn't even know basic grammar, it can't tell that "aimed to my god" is both grammatically incorrect and meaningless.

Perspective in language

Language often indicates perspective:

(1) Give me that.
(2) *Give me this.

The reason that (2) is weird -- by convention, an asterisk marks a bad sentence -- is that the word this suggests that whatever is being requested is close to the speaker. Consider also:

(3) Jane came home.
(4) Jane went home.

If we were currently at Jane's home, it would be more natural to say (3) than (4). Of course, we could say (4), but we would be shifting our perspective, treating wherever Jane was as the reference point, rather than where we are now (this is particularly common in story-telling).

A less prosaic example

That is all fairly familiar, so when I turned to section 6.1 of Chapter 1 of Leonard Talmy's Toward a Cognitive Semantics, titled "Perspectival Location", I wasn't expecting anything particularly new. Then I read these examples (p. 69):

(5) The lunchroom door slowly opened and two men walked in.
(6) Two men slowly opened the lunchroom door and walked in.

These sentences describe the same event, but place the reader in a very different position. As Talmy points out, when reading (5), one gets the sense that you are in the lunchroom, whereas in (6), you get the sense that you outside of the lunchroom ... either that, or the door to the lunchroom is transparent glass.

Implied movement

Talmy gives another great pair of examples on page 71:

(7) There are some houses in the valley.
(8) There is a house every now and then through the valley.

The first sentence implies a static point of view, far from the houses, allowing you to see all the houses at once (Talmy calls this "stationary distal perspective point with global scope of attention"), whereas (8) gives the sense of moving through the valley and among the houses, with only a few within view at any given time ("moving proximal perspective point with local scope of attention")


Writing

Talmy's purpose is to put together a taxonomy of linguistic devices, and most of this chapter is trying to lay out all the different factors along which language can vary (for instance, the different types of perspective one can take). And that is of course why I'm reading it.

But it's also interesting to think about as a writer. One flaw in bad writing is using sentences that adopt the wrong perspective (telling a story about Jennifer, who is in the lunchroom, and then using (6)). This example from Talmy shows just how complicated the issues are ... and the tools available to a good writer for subtly guiding the reader through the story.

The toughest cop "alive"

At little while back, while walking down the street and minding my own business, I saw the following advertisement:

This looks like a scare quote; the implication is that Ace Ticket is nowhere near the best, that it is absurd to suggest that it is the best, which, I assume, is not what they were trying to convey.

One of my colleagues -- yes, I did send this around -- suggested that perhaps Ace Ticket hoped we would read this as a direct quote: somebody has called them the best, and they are quoting. The BBC, apparently, does this regularly. For instance, here's a recent article headline: Families tell of their fears for Syria's 'disappeared'.

I'm not a prescriptivist. But this is confusing. I can't tell, from the article, who the BBC is quoting, especially since the term "disappeared", used to mean "abducted or killed", is now standard usage.

It seems I'm not the only one confused. Buzzfeed has a list of "the worst of unnecessary quotation marks", most of which are unintended scare quotes (the tagline: These aren't just "unnecessary," they're "incomprehensible."). For example:

and:

You can find the rest of the Buzzfeed list here.

Someone in the comments brought the World's Most Interesting Man into the mix (I can only hope this starts a meme):

What you missed in the last 2 weeks on the Internet - 10/22

Americans smarter than you thought
Or so says Mark Liberman, who analyzes some prominent examples of the "Fewer than X% of Americans knowY" meme.

Keep analyzing until you have a significant result
Joshua Carp, a Michigan PhD student, tried it out to see what would happen. Neurocritic has the skinny.

Not-final draft
PhD Comics reminds us that as nice as it feels to label a paper "FINAL.doc", you will pay for that good feeling shortly.

Brain mnemonics
Neuroskeptic suggests a few ways of remembering basic neuroanatomy terminology.

Google N-Grams relaunch
Ben Zimmer at LanguageLog explains the new features.

New Experiment: Finding Explanations

Suppose that John is angry. This might be just a feature of his personality. It might be that something aggravating just happened to him. I suppose that is also possible that he took an “unhappy” pill. The point is, that there are many kinds of explanations.

I just posted a new experiment on the website probing people's intuitions about what kinds of explanations they expect for different kinds of events. Many thanks in advance to all who participate.

Participate in Finding Explanations by clicking here.

Poll Results: How much do you revise your papers

In the last poll, I asked folks how much they revise their papers subsequent to first submission. A substantial majority said that they engaged in revisions that were "substantial" or "more than substantial". I was glad to hear that I'm not the only one.

Findings: What do verbs have to do with pronouns?

A new paper, based on data collected through GamesWithWords.org, is now in press (click here for a pre-print). Below is an overview of this paper.

Unlike a proper name (Jane Austen), a pronoun (she) can refer to a different person just about every time it is uttered. While we occasionally get bogged down in conversation trying to interpret a pronoun (Wait! Who are you talking about?), for the most part we sail through sentences with pronouns, not even noticing the ambiguity.

We have been running a number of studies on pronoun understanding (for some previous posts, see here and here). One line of work looks at a peculiar contextual effect, originally discovered by Garvey and Caramazza in the mid-70s:

(1) Sally frightens Mary because she...
(2) Sally loves Mary because she... 

Although the pronoun is ambiguous, most people guess that she refers to Sally in (1) but Mary in (2). That is, the verb used (frightens, loves) seems to affect pronoun resolution.

Causal Verbs

From the beginning, most if not all researchers agreed that this must have something to do with how verbs encode causality: "Sally frightens Mary" suggests that Sally is the cause, which is why you then think that "because she…" refers to Sally, and vice versa for "Sally loves Mary".

The problem was finding a predictive theory: which verbs encode causality which way? A number of theories have been proposed. The first, from Harvard psychologists Roger Brown and Deborah Fish (1983) was that for emotion verbs (frightens, loves), the cause is the person who *isn't* experiencing the emotion -- Sally in (1) and Mary in (2) -- and the subject for all other verbs. This turned out not to be correct. For instance:

(3) Sally blames Mary because she...

Here, most people think "she" is Mary, even though this is not an emotion verb and so the "cause" was supposed to be -- on Brown and Fish's theory -- the subject (Sally).

A number of other proposals have been made, but the data in the literature doesn't clearly support any one (though Rudolph and Forsterling's 1997 theory has been the most popular). In part, the problem was that we had data on a small number of verbs, and as mathematicians like to tell us, you can draw an infinite number of lines a single point (and create many different theories to describe a small amount of data).

Most previous studies had looked at only a few dozen. With the help of visitors to GamesWithWords.org, we collected data on over 1000 verbs. (We weren't the only ones to notice the problem -- after we began our study, Goikoetxea and colleagues published data from 100 verbs in Spanish and Ferstl and colleagues published data from 305 in English). We found that in fact none of the existing theories worked very well.

However, when we took in independently developed theory of verb meaning from linguistics, that actually predicted the results very well. All of the theories tried to divide up verbs into a few classes. Within each class, it was supposed to be all the verbs with either have causes as their subjects (causing people to interpret the pronoun is referring to the subject in sentences like 1-3). Unfortunately, this was rarely the case, as shown in Table 2 of the paper:

A new theory


This was, of course, disappointing. We wanted to understand pronoun interpretation better, but now we understood worse! Luckily, the work did not end there. We turned to a well-developed theory from linguistics about what verbs mean (the work I have described above was developed by psychologists largely independently from linguistics).

The basic idea behind this theory is that the core meaning of verbs is built out of a few basic parts, such as movement, possession, the application of force, and – importantly for us – causality. In practice, nobody goes through the dictionary and determines for every verb, which of these core components it has. This turns out to be prohibitively difficult to do (but stay tuned; a major new project GamesWithWords.org will be focused on just this). But it turns out that when you classify verbs according to the kinds of sentences they can appear in, this seems to give you the same thing: groups of verbs that share these core components meaning (such as causality).

The prediction, then, is that if we look at verbs in the same class according to this theory, all the verbs in that class should encode causality in the same way and thus should affect pronouns in the same way. And that is exactly what we found. This not only furthers our understanding of the phenomenon we were studying, but it is also confirmation of both the idea that verb meaning plays a central role in the phenomenon and is confirmation of the theory from linguistics.


Why so much work on pronouns?


Pronouns are interesting in their own right, but I am primarily interested in them as a case study in ambiguity. Language is incredibly ambiguous, and most of the time we don't even notice it; For instance, it could be that the "she" in (1) refers to Jennifer -- someone not even mentioned in the sentence! -- but you probably did not even consider that possibility. Because we as humans find the problem so easy, it is very hard for us as scientists to have good intuitions about what is going on. This has become particularly salient as we try to explain to computers what language means (that is, program them to process language).

The nice thing about pronouns is that they are a kind of ambiguity is very easy to study, and many good methods have been worked out for assessing their processing. More than many areas of research on ambiguity -- and, I think, more than many areas of psychology that don't involve vision -- I feel that a well worked-out theory of pronoun processing is increasingly within our reach. And that is very exciting.


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Hartshorne, J., and Snedeker, J. (2012). Verb argument structure predicts implicit causality: The advantages of finer-grained semantics Language and Cognitive Processes, 1-35 DOI: 10.1080/01690965.2012.689305

Brown, R., and Fish, D. (1983). The psychological causality implicit in language Cognition, 14 (3), 237-273 DOI: 10.1016/0010-0277(83)90006-9

Goikoetxea, E., Pascual, G., and Acha, J. (2008). Normative study of the implicit causality of 100 interpersonal verbs in Spanish Behavior Research Methods, 40 (3), 760-772 DOI: 10.3758/BRM.40.3.760

Ferstl, E., Garnham, A., and Manouilidou, C. (2010). Implicit causality bias in English: a corpus of 300 verbs Behavior Research Methods, 43 (1), 124-135 DOI: 10.3758/s13428-010-0023-2

Rudolph, U., and Forsterling, F. (1997). The psychological causality implicit in verbs: A review. Psychological Bulletin, 121 (2), 192-218 DOI: 10.1037//0033-2909.121.2.192