I thought that I would write my thoughts about SinFonIJA 11 in Krakow, Poland, which just finished this past weekend. It was organized by three professors in the Dept. of English Studies at Jagiellonian University in Krakow: Marta Ruda, a former visiting scholar at UMD Linguistics, Mateusz Urban, and Ewa Willim, who was Howard Lasnik’s student and the recipient of the infamous manuscript ‘On the Nature of Proper Government’. All three of them were gracious hosts and the conference was very well organized, informative, and fun. SinFonIJA is a regionalconference on formal linguistic analysis focusing on syntax and phonology, but as a neuroscientist, I felt quite welcome and many of the attendees expressed interest in my work. Kraków is a beautiful city and definitely worth visiting, to boot; if you ever visit, make sure to see the Wieliczka salt mine.
I suppose my sense of welcome was helped by the fact that the main theme of the conference was “Theoretical Linguistics within Cognitive science” – I was invited to chair a round table discussion on how linguistics is getting on with the other cognitive sciences these days. Linguistics was a founding member of the modern cognitive sciences during the cognitive revolution in the 50s and 60s – perhaps the founding member, with the work by Chomsky in Generative Grammar stimulating interest in deeper, abstract properties of the mind and articulating an alternative vision of language from the dominant behaviorist perspective. Marta was the key instigator of this theme – this was a frequent topic of discussion between us while we were both at the UMD Linguistics dept., which has a unique capacity to bridge the gaps between formal linguistic theory and other fields of cognitive science (e.g., acquisition, psycholinguistics, neuroscience). The invited keynote speakers comprising the round table addressed foundational questions underlying linguistic theory as well as the relation between formal linguistics and the cognitive sciences in their own talks. The main part of this post will reflect on this topic and the roundtable discussion, but before that I’d like to discuss Zheng Shen’s talk, which highlighted important issues regarding the methods in formal linguistics. Much of what I say here reiterates a previous post of mine on FoL.
Methods and data in formal linguistics
Lately there has been noise about the quality of data in formal linguistics, with some non-formal linguists calling for linguists to start acting more like psychologists and report p-values (because if you don’t have p-values, you don’t have good data, naturally). My impressions are that these concerns are greatly exaggerated and a non-sequitur. If anything, my feelings are that formal linguistics, at least of the generative grammar variety, is on a greater empirical footing than psycholinguistics and neurolinguistics. This is because linguistics rightly focuses on theoretical development, with data as a tool to sharpen theory, rather than a fixation on data itself. This is illustrated well by Shen’s talk.
Shen began by discussing his analysis of agreement in right node raising (RNR) and its empirical superiority over other accounts (Shen, 2018). His account rested on a series of traditional informal acceptability judgments, consulting a small number of native speakers of English to derive the patterns motivating his analysis. Interestingly, other authors offered a competing account of agreement in RNR, which was not just an alternative analysis but included conflicting data patterns – the two papers disagreed on whether particular constructions were good and bad (Belk & Neelman, 2018) (see the abstract submitted by Shen for details). Shen then performed a series of carefully designed acceptability judgment experiments to sort out the source of the discrepancy, ultimately obtaining patterns of data from large groups of naïve participants that essentially agreed with his judgments rather than Belk & Neelman’s.
Psychologists (particularly Ted Gibson & Ev Fedorenko) have been heavily critical of methods in formal linguists of late, claiming that informal acceptability judgments are unreliable and misleading (Gibson & Fedorenko, 2010; 2013; their claim of weak quantitative standards in linguistics has been directly contradicted by the exhaustive research of Sprouse & Almeida, 2012; 2013, which illustrates a replication rate of 95-98% of informal judgments presented in a standard syntax textbook as well as a leading linguistics journal with naïve subjects in behavioral experiments,). This disagreement about data with respect to RNR appears to support these attacks on formal linguistics by providing a concrete example.
This critique is invalid. First, the two sets of authors agreed on a large set of data, disagreeing on a small minority of data that happened to be crucial for the analysis. The two competing theoreticalaccounts highlighted the small discrepancy in data, leading to a proper focus on resolving the theoretical dispute via cleaning up the data point.
Second, Shen’s original judgments were vindicated. In other words, the behavioral experiments essentially replicated the original informal judgments. In fact, Shen noted several quite obvious issues with the use of naïve subjects, in that they may not be sensitive to making judgments under particular interpretations – that is, they may judge the string to be acceptable, but not under the crucial interpretation/structural analysis under consideration. It took a large amount of work (and I assume money) to handle these issues with multiple experiments to (in a nutshell) merely replicate informal judgments that were obtained far more rapidly and easily than the experiments. Essentially, no new data points were obtained – only replications. It is not clear why Shen and Belk & Neelman disagreed on the data (potentially because of dialect differences, British vs. American English) – but it certainly the problem was not with Shen’s informal judgments.
These two facts inform us that while large-scale experiments can be useful, they are not the drivers of research. Shen’s hard work provided replications in the context oftwo detailed, competing theoretical analyses. The experimental data were only acquired after the theoretical analyses were proposed, and those analyses were based on informal judgment data. If we take Gibson & Fedorenko’s (2010) demands for eschewing informal judgments entirely, then we would end up with disastrous consequences, namely slavishly collecting mass amounts of behavioral data, and spending inordinate amounts of time analyzing that data, all in the absence of theoretical development (which is one of the drivers of the un-replicability plague of much of social psychology). Theory should drive data collection, not the other way around.
With that said, the next section changes gears and discusses the special topic of the conference.
Theoretical linguistics within cognitive science: a crisis?
First, I will summarize my introduction to the round table and the main feelings driving what I and Cedric Boeckx perceive to be a crisis regarding the place of formal linguistics in the cognitive sciences – from my perspective, cognitive neuroscience specifically. As I pointed out in a previous blog post on Talking Brains, this crisis is well-illustrated by the fact that the Society for the Neurobiology of language has never had a formal linguist, or even a psycholinguist, present as a keynote speaker in its 10 years of existence, despite many presentations by neuroscientists and experts on non-human animal communication systems.
I think there are many reasons for the disconnect – paramount among these a lack of appreciation for the goals and insights of linguistic theory, sociological factors such as a lack of people who are knowledgeable of both domains and the objectives of both sides, and likely many others. My main point was not to review all of the possible reasons. Rather, I thought it appropriate when discussing with linguists to communicate what is possible for linguists to do to rekindle the interaction among these fields (when I talk to cognitive neuroscientists, I do the opposite – discuss what they are missing from linguistics). I used my own history of attempting to bridge the gaps among fields, raising what I perceived to be a frustrating barrier - the competence/performance distinction. Consider this line from Aspects (Chomsky, 1965), the authoritative philosophical foundation of the generative grammar research enterprise:
“… by a generative grammar I mean simply a system of rules that in some explicit and well-defined way assigns structural descriptions to sentences”
The idea that language is a system of rules is powerful. In the context of the mentalistic theory of grammar, it embodies the rejection of behaviorism in favor of a more realistic as well as exciting view of human nature – that our minds are deep and, in many ways, independent of the environment, requiring careful and detailed study of the organism itself in all of its particularities rather than merely a focus on the external world. It calls for a study of the observer, the person, the machine inside of the person’s head that processes sentences rather than the sentences themselves. This idea is what sparked the cognitive revolution and the intensive connection between linguistics and the other cognitive sciences for decades, and led to so many important observations about human psychology.
For a clear example from one of the conference keynote speakers: the work Ianthi Tsimpli did on Christopher, the mentally impaired savant who apparently had intact (and in fact, augmented) ability to acquire the grammar of disparate languages, including British Sign Language, in the face of shocking deficits in other cognitive domains. Or my own field, which finds that the formal descriptions of language derived from formal linguistic theory, and generative grammar in particular – including syntactic structures with abstract layers of analysis and null elements, or sound expressions consisting of sets of phonological features that can be more or less shared among speech sounds – have quite salient impacts on patterns of neuroimaging data,.
However, it is one thing to illustrate that hypothesized representations from linguistic theory impact patterns of brain activity, and another to develop a model for how language is implemented in the brain. To do so requires making claims for how things actually work in real time. But then there is this:
“... agenerative grammar is not a model for a speaker or a hearer ... When we say that a sentence has a certain derivation with respect to a particular generative grammar, we say nothing about how the speaker or hearer might proceed ... to construct such a derivation”.
The lack of investigation into how the competence model is usedposes problems. It is one thing to observe that filler gap dependences – sentences with displaced elements involving the theoretical operation Movement(or internal merge, if you like) – induce increased activation in Broca’s area relative to control sentences (Ben-Shachar et al., 2003), but quite another to develop a map of cognitive processes on the brain. Most definitely it is not the case that Broca’s area “does” movement.
It is clearly the case that linguists would like to converge with neuroscience and use neuroscience data as much as possible. Chomsky often cites the work of Friederici (as well as Moro, Grodzinsky, and others). For instance, in Berwick & Chomsky’s recent book Why Only Us they have a central part of the book devoted to the brain bases of syntax, adopting Friederici’s theoretical framework for a neurobiological map of syntax and semantics in the brain. Much of my work has pointed out that Friederici’s work, while empirically quite exceptional and of high quality, makes quite errant claims about how linguistic operations are implemented in the brain.
Now, I think this issue can be worked on and improved upon. But how? The only path forward that I can see is by developing a model of linguistic performance – one that indicates how linguistic operations or other components of the theory are implemented during real-time sentence processing and language acquisition. In other words, adding temporal components to the theory, at least at an abstract level. This was my main point in introducing the round table – why not work on how exactly grammar relates to parsing and production, i.e. developing a performance model?
At the end of Ian Roberts’s talk, which quite nicely laid out the argument for strict bottom-up cyclicity at all levels of syntactic derivation, where there was some discussion about whether the derivational exposition could be converted to a representational view that does not appeal to order (of course it can). Linguists are compelled by the competence/performance distinction to kill any potential thinking of linguistic operations occurring in time. This makes sense if one’s goal is to focus purely on competence. With respect to making connections to the other cognitive sciences, though, the instinct needs to be the reverse – to actually make claims about how the competence theory relates to performance.
Near the end of my talk I outlined three stances on how the competence grammar (e.g., various syntactic theories of a broadly generative type) relates to real-time processing (in this context, i.e. parsing):
1. The grammar is a body of static knowledge accessed during acquisition, production, and comprehension (Lidz & Gagliardi, 2015).This represents what I take to be the standard generative grammar view – that there is a competence “thing” out there that somehow (in my view, quite mysteriously) mechanistically relates to performance. It’s one thing to adopt this perspective, but quite another to flesh out exactly how it works. I personally find this view to be problematic because I don’t think there are any other analogs or understandings for how such a system could be implemented in the brain and how it constrains acquisition and use of language (but I am open to ideas, and even better – detailed theories).
2. The grammar is a “specification” of a parser (Berwick & Weinberg, 1984; Steedman, 2000).The idea is that there really is no grammar, but rather that the competence theory is a compact way of describing the structural outputs of the “real” theory of language, the performance models (parser/producer). If this is so, that’s quite interesting, because in my view it completely deprives the competence model of any causal reality, which completely removes its insight into any of the fundamental questions of linguistic theory, such as Plato’s problem – how language is acquired. I do not like this view.
3. The grammar is a real-time processing device, either directly (Miller, 1962; Phillips, 1996) or indirectly (Fodor et al., 1974; Townsend & Bever, 2001) used during real-time processing and acquisition.I very much like this view. It says that the competence model is a thing that does stuff in real time. It has causal powers and one can straightforwardly understand how it works. While I don’t think that the models advocated for in these citations ultimately succeeded, I think they were spot on in their general approach and can be improved upon.
While I personally heavily favor option (3), I would love to see work that fleshes out any of the above while addressing (or leading the way to address) the core philosophical questions of linguistic theory, as discussed by Cedric Boeckx’s.
Part 2 of this post raises and addresses some of the comments by the keynote speakers on this topic.
If you don’t know this story you would best hear about it from the original participants.
The regional domain consists of the former Austro-Hungarian Empire. This divides the borders of current countries, so Krakow is in but Warsaw is out.
Wielizca is no average mine – it was in parts beautiful and educational. It is way more fun than it sounds.
Gibson, E., & Fedorenko, E. (2010). Weak quantitative standards in linguistics research. Trends in cognitive sciences, 14(6), 233-234; Gibson, E., & Fedorenko, E. (2013). The need for quantitative methods in syntax and semantics research. Language and Cognitive Processes, 28(1-2), 88-124.; Sprouse, J., & Almeida, D. (2012). Assessing the reliability of textbook data in syntax: Adger's Core Syntax. Journal of Linguistics, 48(3), 609-652; Sprouse, J., Schütze, C. T., & Almeida, D. (2013). A comparison of informal and formal acceptability judgments using a random sample from Linguistic Inquiry 2001–2010. Lingua, 134, 219-248.
95-98% is probably an underestimate, because there are likely cases where subjects incorrectly report their judgments without properly making the judgment under particular interpretations, etc. However, even taking the 95-98% number at face value, what do we think the replication rate is in certain fields of social psychology? Are formal linguists really supposed to change their way of doing things to match a field that is notoriousthese days for lack of rigor?
Smith, N. V., & Tsimpli, I. M. (1995). The mind of a savant: Language learning and modularity. Blackwell Publishing.
Smith, N., Tsimpli, I., Morgan, G., & Woll, B. (2010). The signs of a savant: Language against the odds. Cambridge University Press.
Brennan, J. R., Stabler, E. P., Van Wagenen, S. E., Luh, W. M., & Hale, J. T. (2016). Abstract linguistic structure correlates with temporal activity during naturalistic comprehension. Brain and language, 157, 81-94.
Okada, K., Matchin, W., & Hickok, G. (2018). Phonological Feature Repetition Suppression in the Left Inferior Frontal Gyrus. Journal of cognitive neuroscience, 1-9.
For evidence on this point see the following papers. Wilson, S. M., & Saygın, A. P. (2004). Grammaticality judgment in aphasia: Deficits are not specific to syntactic structures, aphasic syndromes, or lesion sites. Journal of Cognitive Neuroscience, 16(2), 238-252. Matchin, W., Sprouse, J., & Hickok, G. (2014). A structural distance effect for backward anaphora in Broca’s area: An fMRI study. Brain and language, 138, 1-11. Rogalsky, C., Almeida, D., Sprouse, J., & Hickok, G. (2015). Sentence processing selectivity in Broca's area: evident for structure but not syntactic movement. Language, cognition and neuroscience, 30(10), 1326-1338.