I: Experimental Syntax and the Question of Explanation
Linguistic theory has long sought to explain what speakers know when they know a language. For much of the twentieth century, this question was approached primarily through abstract formalization and introspective judgment. Dr. Jennifer Culbertson’s work represents a decisive shift in emphasis: language is approached not only as a formal system, but as a cognitive system shaped by learning, use, and communication. Experimental syntax, in this view, is not auxiliary to theory; it is central to explanation.
Experimental methods allow linguists to isolate specific factors involved in acquisition and processing, factors that remain obscured in naturalistic data. Child-directed speech corpora and observational studies reveal what learners are exposed to and what they eventually produce, but experiments reveal why certain patterns are easier or harder to acquire. This methodological pivot reframes syntax as a domain where hypotheses about structure, bias, and representation can be tested directly.
II: Learning Grammatical Systems Under Constraint
One of the clearest demonstrations of experimental syntax comes from work on grammatical gender. Languages such as French and Spanish encode gender as a pervasive but semantically opaque feature, posing a puzzle: children acquire these systems rapidly and robustly, while adult learners struggle.
Experimental studies show that children preferentially rely on phonological cues, such as noun endings, over semantic cues like natural gender. Crucially, experiments can equate the reliability of these cues, revealing an underlying bias toward formally consistent, distributional information. Gender systems thus illustrate a general principle: learners are not passive recipients of input but active system-builders, guided by biases that privilege certain kinds of structure.
III: Syntax Learning Beyond Surface Fluency
Naturalistic child speech often appears deceptively adult-like. Experimental work reveals that beneath this surface fluency lie significant learning challenges. Children show persistent difficulty with noun phrase word order patterns that mix head directionality, even when these patterns are common in the ambient language.
Such findings demonstrate that acquisition is gradual and structurally sensitive. Mastery is not simply a matter of frequency or exposure but reflects deeper preferences for consistency and simplicity. Experimental syntax thus uncovers stages of grammatical development that are invisible in corpus data alone.
IV: Constructed Languages and the Limits of Learnability
Artificial language learning paradigms play a crucial role in Culbertson’s research program. By stripping away the idiosyncrasies of natural languages, constructed systems allow precise manipulation of grammatical features. Researchers can test patterns that are rare or unattested cross-linguistically, probing the boundaries of what humans can learn.
These experiments are complemented by computational models that formalize hypotheses about learning mechanisms. Importantly, the models are grounded in experimental results rather than inherited syntactic assumptions. This reverses the traditional flow of explanation: theory is constrained by learnability, not the other way around.
V: Learning Bias and Formal Grammar
A central challenge is integrating experimental findings into formal linguistic theory. Many syntactic frameworks describe what grammars can generate but say little about how those grammars are learned. Culbertson’s work highlights this limitation.
Optimality Theory provides one avenue forward. Because OT encodes preferences and constraints, it naturally accommodates learning biases. Patterns that are easier to acquire correspond to grammars with simpler or more harmonious constraint rankings. By contrast, Minimalist approaches lack an explicit representational space for bias, making it difficult to connect formal derivations with experimental results.
VI: Syntax as a Cognitive System
Culbertson argues that syntactic theory must be psychologically realistic. Syntax is computed in real time, under memory and attentional constraints, and interacts with perception and action. Treating syntax as an isolated formal module obscures its role within the broader cognitive architecture.
This perspective aligns experimental syntax with cognitive science and psycholinguistics. Hierarchical structure, linear order, and meaning are not competing explanations but interacting dimensions of a single system.
VII: Typological Universals and Simplicity
One of the most striking cross-linguistic patterns is syntactic harmony: languages tend to align head-dependent orderings across constructions. While traditionally explained via parameters, experimental work suggests a complementary explanation rooted in cognition.
Simpler grammars, those requiring fewer rules, are easier to learn and process. Learners exhibit a bias toward uniformity, which over time shapes typological distributions. This does not eliminate linguistic structure; rather, it grounds typology in general cognitive pressures.
VIII: Naturalness, Salience, and Word Order
Not all biases reduce to simplicity. Perceptual and semantic factors also shape grammar. Experiments demonstrate a preference for placing animate entities earlier in sentences, reflecting their salience in human cognition.
Such findings suggest that syntactic roles like “subject” may emerge from more fundamental perceptual biases. Structural prominence can thus be understood as a consequence, not a primitive.
IX: Communication as a Shaping Force
Language is not only learned; it is used. Communicative pressures interact with learning biases to shape grammatical systems. Experimental studies show that when communication is required, languages develop regularity, compositionality, and structure.
Without communication, systems collapse into holistic, unstructured codes. Without learning constraints, they become unwieldy and complex. Language emerges from the balance between these pressures.
X: Iterated Learning and Language Evolution
Iterated learning paradigms model language transmission across generations. These experiments reveal how structure accumulates over time as languages are repeatedly learned and used.
Sign language emergence provides a real-world analogue. Newly formed sign languages show rapid development of grammatical structure, offering a window into the origins of linguistic design features.
XI: Gradualism and the Language Faculty
Culbertson endorses a gradualist view of language evolution. Rather than a sudden, fully formed language faculty, linguistic capacities emerge from general cognition shaped by social interaction.
This view accommodates both domain-specific and domain-general processes. Language is special, but not isolated.
XII: Modularity Revisited
The integration of language and cognition does not require rejecting modularity outright. The mind may contain specialized systems that nonetheless rely on general learning and perceptual mechanisms.
The key insight is that linguistic explanation must account for interaction, not isolation.
XIII: Bridging Syntax and Neuroscience
While primarily cognitive in focus, experimental syntax stands to benefit from neuroscience. Understanding how grammatical representations are instantiated in the brain remains an open challenge.
Collaborations linking behavioral experiments with neural measures promise progress without premature reductionism.
XIV: Theory Choice and Experimental Evidence
Experimental syntax rarely adjudicates between entire grammatical frameworks. Many formalisms are equivalent in expressive power. However, frameworks that incorporate probabilistic bias and learning mechanisms align more naturally with experimental findings.
This offers a pragmatic criterion for theory development.
XV: Future Directions
The future of experimental syntax lies in addressing core grammatical phenomena, including negation and scope. Artificial language learning, computational modeling, and interdisciplinary collaboration will be central.
As linguistics increasingly intersects with artificial intelligence, experimental syntax provides tools to evaluate whether machines learn language-like representations or merely exploit surface patterns.
XVI: Conclusion
Dr Jennifer Culbertson on Experimental Syntax - Oxford University Linguistics Society
