This article examines the claim that the recursive operation Merge underlies the generative structure of the natural number system. I argue that this claim rests on a conflation between recursion as a property of syntactic representation and recursion as a property of numerical computation. In syntax, repeated applications of Merge yield hierarchically structured expressions; in arithmetic, the successor function yields successive values. These are not the same kind of operation. Focusing on recent proposals by Mendívil-Giró (2025) and Watanabe (2017), I show that Merge, whether external or internal, does not by itself derive numerical succession, but only structured symbolic objects whose interpretation must be independently determined. I further argue that the principal assumptions needed to sustain a Merge-based theory of natural number (innate numerical generativity, hierarchical structure in the count list, and a primitive lexical item corresponding to 1) lack independent empirical support. I conclude that number generativity is better understood as an emergent property of compositional symbolic structure than as the direct output of a successor-like operation implemented by narrow syntax.

This article proposes a theoretical framework for a Bio-Ethological 4E Linguistics that integrates ethology, biolinguistics, and embodied cognition within a single biological continuum. It argues that the persistent division between linguistic internalism and behavioral biology has produced two incomplete naturalisms—one mental without life, the other biological without mind. By aligning Tinbergen’s four questions of ethology (mechanism, ontogeny, function, evolution) with the four dimensions of 4E cognition (embodiment, enaction, embeddedness, extension), the paper reconstructs language as an evolved form of biological sense-making rather than an abstract code. Classical ethology—represented by Tinbergen, Lorenz, Hinde, and Hess—anticipated many principles later formalized in enactive and embodied theories of mind, while contemporary 4E approaches have yet to ground their concepts in the empirical study of behavior. The proposed synthesis restores that missing continuity by treating linguistic interaction as a living process of regulation within ecological and social systems. Language, on this view, functions as an adaptive interface linking individual cognition to collective life. The article concludes with a programmatic agenda for a unified science of communication that spans neurobiological mechanisms, developmental dynamics, social coordination, and cultural evolution. A Bio-Ethological 4E Linguistics thus redefines language as life expressing itself through meaning—an approach that re-joins the study of mind with the study of behavior and situates linguistics within the broader biology of living systems.

A core component of a successful artificial general intelligence would be the rapid creation and manipulation of grounded compositional abstractions and the demonstration of expertise in the family of recursive hierarchical syntactic objects necessary for the creative use of human language. We evaluated the recently released o3 model (OpenAI; o3-mini-high) from ChatGPT and discovered that while it succeeds on some basic linguistic tests relying on linear, surface statistics (e.g., the Strawberry Test), it fails to generalize basic phrase structure rules; it fails with comparative sentences involving semantically illegal cardinality comparisons (‘Escher sentences’); it fails to correctly rate and explain acceptability dynamics; and it fails to distinguish between instructions to generate unacceptable semantic vs. unacceptable syntactic outputs. When tasked with generating simple violations of grammatical rules, it is seemingly incapable of representing multiple parses to evaluate against various possible semantic interpretations. We ran all of these prompts multiple times again through the API and provide basic accuracy scores. In stark contrast to many recent claims that artificial language models are on the verge of replacing the field of linguistics, our results suggest not only that deep learning is hitting a wall with respect to compositionality ( Marcus, 2022 ), but that it is hitting [ a [ stubbornly [ resilient wall ]]] that cannot readily be surmounted to reach human-like compositional reasoning simply through more compute.

This paper draws a deep connection between smuggling (Collins, 2005) and labeling (Collins, 2002; Chomsky, 2013, 2015), showing that the movement of the smuggler in a smuggling derivation can be triggered by the labeling algorithm.

The idea that mathematical ability and language are related in human cognition is an old one. It is commonly assumed in the philosophical tradition, in psychology and in cognitive science, generally implying that knowledge of numbers is indebted to knowledge of language. In this contribution I suggest a more specific model of the relationship between knowledge of numbers and knowledge of language in the light of developments in the neuroscience of numerical understanding and in linguistic theory. The proposed model places the evolutionary development of the syntactic component of the Faculty of Language at the basis of the transition from the innate sense of number that we share with other animals to the sophisticated mathematical ability of our species.

Some recent influential work in the Minimalist Program takes the position that Merge, the core language ability to recursively combine two elements together, is free. However, if Merge were completely free, there would be an infinite number of possible derivations for every utterance. Thus, Merge must be constrained in some way. In this paper, I describe a computer model of language that implements a limited form of Merge that is free. I attempt to demonstrate that, within the confines of the language module, Labeling is generally sufficient to constrain Free Merge, and I discuss issues that arise regarding overgeneration of syntactic structures given Free Merge.

In this article, we summarise and critically evaluate Ryan Nefdt’s The Philosophy of Theoretical Linguistics: A Contemporary Outlook (2024). In this book, Nefdt brings the tools of philosophy to bear on contemporary linguistics, targeting perennial debates in syntax, semantics, pragmatics, phonology, and the evolution of language. In so doing, Nefdt sketches several tantalising paths for progress on these topics. Although some of Nefdt’s arguments are underdeveloped, this book serves as a worthwhile introduction to the philosophy of linguistics.