Standard proposals of scientific anti-realism assume that the methodology of a scientific researc... more Standard proposals of scientific anti-realism assume that the methodology of a scientific research program can be endorsed without accepting its metaphysical commitments. I argue that the distinction between competence, the rules governing one’s language faculty, and performance, or linguistic behavior, precludes this. Linguistic theories aim to describe competence, not performance, and so must be able to distinguish observations reflective of the former from those reflective of the latter. This classification of data makes sense only against the background of a psychologically realistic view of linguistic theory. So the very methodology of the science commits one to its realistic interpretation.
Richard Feynman famously claimed that philosophy of science is as useful for science as ornitholo... more Richard Feynman famously claimed that philosophy of science is as useful for science as ornithology is for birds. Perhaps linguists are simply more self-reflective than most avians, but this has never seemed true in linguistics. On the contrary, in the modern history of linguistics, linguists have not merely paid attention to philosophical debates concerning the relations between evidence, theory and reality, but have actively contributed to them. Continuing this admirable trend, Linguistic Intuitions brings together fourteen chapters from linguists and philosophers centred on the question: (How) can linguistic intuitions provide evidence for empirical linguistic theory? This disarmingly simple question raises a variety of important questions, ranging from the ‘philosophical’ (What is language? What is evidence?) to the ‘scientific’ (What is the argument structure of ‘get’? Are movement islands grammatical or perceptual?). The first half of the book, mainly by philosophers, is centred on identifying the causal antecedents of linguistic intuitions. The second half, mainly by linguists, focuses on debates concerning the need, if any, for large-scale surveys and statistical analysis in linguistics, beyond the traditional method of consulting one’s own intuitions. This division by topic and field understates the continuity of these debates. While the emphasis, and reference points, vary, the chapters are remarkably coherent with several themes occurring throughout. Given constraints of space, I will focus on just one such theme. One significant determinant of the character of a science is the observability of the domain it aims to investigate. Sometimes we can directly observe the target of inquiry. Sometimes we can only construct measuring devices which, if well designed, enable us to observe states which correlate with the target. Predictably, this difference leads to variations in disciplinary methodology. In linguistics, it is not clear whether we are even in the latter category. However, what linguists can do is utilize human beings as measuring devices. While we cannot observe languages directly, we can ask people about their native tongues. This book is centrally an investigation into the reliability of this methodology: should we take native speakers’ intuitive judgements about language to tell us about language itself? Answering this question depends on distinguishing between several senses of ‘reliability’. First, given that linguistic intuitions are typically reported in the form of declarative sentences, we can ask whether these intuitions are (typically) TRUE?1
Generative grammarians typically advocate for a rationalist understanding of language acquisition... more Generative grammarians typically advocate for a rationalist understanding of language acquisition, according to which the structure of a developed language faculty reflects innate guidance rather than environmental influence. This proposal is developed in developmental linguistics by triggering models of language acquisition. Opposing this tradition, various theorists have advocated for empiricist views of language acquisition, according to which the structure of a developed linguistic competence reflects the linguistic environment in which this competence developed. On this picture, linguistic development is accounted for by general statistical learning mechanisms. In this article I shall precisify the debate, provide a clearer picture of what is at stake, and show why an intermediate picture is needed.
Deep learning (DL) techniques have revolutionised artificial systems’ performance on myriad tasks... more Deep learning (DL) techniques have revolutionised artificial systems’ performance on myriad tasks, from playing Go to medical diagnosis. Recent developments have extended such successes to natural language processing, an area once deemed beyond such systems’ reach. Despite their different goals (technological development vs. theoretical insight), these successes have suggested that such systems may be pertinent to theoretical linguistics. The competence/performance distinction presents a fundamental barrier to such inferences. While DL systems are trained on linguistic performance, linguistic theories are aimed at competence. Such a barrier has traditionally been sidestepped by assuming a fairly close correspondence: performance as competence plus noise. I argue this assumption is unmotivated. Competence and performance can differ arbitrarily. Thus, we should not expect DL models to illuminate linguistic theory.
Traditional arguments against the identification of the language of thought with natural language... more Traditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain philosophers and linguists to suggest that this identification is not as implausible as it once seemed. In this paper, I discuss the prospects for such an identification in light of these developments in linguistic theory. I raise a new challenge against the identification thesis: the existence of ungrammatical but acceptable expressions seems to require a gap between thought and language. I consider what must be the case in order for this objection to be dealt with.
In this paper, I shall provide a novel response to the argument from contextsensitivity against t... more In this paper, I shall provide a novel response to the argument from contextsensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language meaning. From this perspective, disparity between the scientific model and its realworld target is to be expected. I elaborate on what such an approach to semantics would look like.
I present a novel, collaborative, methodology for linguistics: what I call the 'explanatory econo... more I present a novel, collaborative, methodology for linguistics: what I call the 'explanatory economy'. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light.
Language has long been a problem-case for subsymbolic theories of mind. The reason for this is ob... more Language has long been a problem-case for subsymbolic theories of mind. The reason for this is obvious: Language seems essentially symbolic. However, recent work has developed a potential solution to this problem, arguing that linguistic symbols are public objects which augment a fundamentally subsymbolic mind, rather than components of cognitive symbol-processing. I shall argue that this strategy cannot work, on the grounds that human language acquisition consists in projecting linguistic structure onto environmental entities, rather than extracting this structure from them.
Traditional arguments against the identification of the language of thought with natural language... more Traditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain philosophers and linguists to suggest that this identification is not as implausible as it once seemed. In this paper, I discuss the prospects for such an identification in light of these developments in linguistic theory. I raise a new challenge against the identification thesis: the existence of ungrammatical but acceptable expressions seems to require a gap between thought and language. I consider what must be the case in order for this objection to be dealt with.
Inquiry: An Interdisciplinary Journal of Philosophy
In this paper, I shall provide a novel response to the argument from context-sensitivity against ... more In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language meaning. From this perspective, disparity between the scientific model and its real-world target is to be expected. I elaborate on what such an approach to semantics would look like.
I present a novel, collaborative, methodology for linguistics: what I call the 'explana-tory econ... more I present a novel, collaborative, methodology for linguistics: what I call the 'explana-tory economy'. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light.
Standard proposals of scientific anti-realism assume that the methodology of a scientific researc... more Standard proposals of scientific anti-realism assume that the methodology of a scientific research program can be endorsed without accepting its metaphysical commitments. I argue that the distinction between competence, the rules governing one’s language faculty, and performance, or linguistic behavior, precludes this. Linguistic theories aim to describe competence, not performance, and so must be able to distinguish observations reflective of the former from those reflective of the latter. This classification of data makes sense only against the background of a psychologically realistic view of linguistic theory. So the very methodology of the science commits one to its realistic interpretation.
Richard Feynman famously claimed that philosophy of science is as useful for science as ornitholo... more Richard Feynman famously claimed that philosophy of science is as useful for science as ornithology is for birds. Perhaps linguists are simply more self-reflective than most avians, but this has never seemed true in linguistics. On the contrary, in the modern history of linguistics, linguists have not merely paid attention to philosophical debates concerning the relations between evidence, theory and reality, but have actively contributed to them. Continuing this admirable trend, Linguistic Intuitions brings together fourteen chapters from linguists and philosophers centred on the question: (How) can linguistic intuitions provide evidence for empirical linguistic theory? This disarmingly simple question raises a variety of important questions, ranging from the ‘philosophical’ (What is language? What is evidence?) to the ‘scientific’ (What is the argument structure of ‘get’? Are movement islands grammatical or perceptual?). The first half of the book, mainly by philosophers, is centred on identifying the causal antecedents of linguistic intuitions. The second half, mainly by linguists, focuses on debates concerning the need, if any, for large-scale surveys and statistical analysis in linguistics, beyond the traditional method of consulting one’s own intuitions. This division by topic and field understates the continuity of these debates. While the emphasis, and reference points, vary, the chapters are remarkably coherent with several themes occurring throughout. Given constraints of space, I will focus on just one such theme. One significant determinant of the character of a science is the observability of the domain it aims to investigate. Sometimes we can directly observe the target of inquiry. Sometimes we can only construct measuring devices which, if well designed, enable us to observe states which correlate with the target. Predictably, this difference leads to variations in disciplinary methodology. In linguistics, it is not clear whether we are even in the latter category. However, what linguists can do is utilize human beings as measuring devices. While we cannot observe languages directly, we can ask people about their native tongues. This book is centrally an investigation into the reliability of this methodology: should we take native speakers’ intuitive judgements about language to tell us about language itself? Answering this question depends on distinguishing between several senses of ‘reliability’. First, given that linguistic intuitions are typically reported in the form of declarative sentences, we can ask whether these intuitions are (typically) TRUE?1
Generative grammarians typically advocate for a rationalist understanding of language acquisition... more Generative grammarians typically advocate for a rationalist understanding of language acquisition, according to which the structure of a developed language faculty reflects innate guidance rather than environmental influence. This proposal is developed in developmental linguistics by triggering models of language acquisition. Opposing this tradition, various theorists have advocated for empiricist views of language acquisition, according to which the structure of a developed linguistic competence reflects the linguistic environment in which this competence developed. On this picture, linguistic development is accounted for by general statistical learning mechanisms. In this article I shall precisify the debate, provide a clearer picture of what is at stake, and show why an intermediate picture is needed.
Deep learning (DL) techniques have revolutionised artificial systems’ performance on myriad tasks... more Deep learning (DL) techniques have revolutionised artificial systems’ performance on myriad tasks, from playing Go to medical diagnosis. Recent developments have extended such successes to natural language processing, an area once deemed beyond such systems’ reach. Despite their different goals (technological development vs. theoretical insight), these successes have suggested that such systems may be pertinent to theoretical linguistics. The competence/performance distinction presents a fundamental barrier to such inferences. While DL systems are trained on linguistic performance, linguistic theories are aimed at competence. Such a barrier has traditionally been sidestepped by assuming a fairly close correspondence: performance as competence plus noise. I argue this assumption is unmotivated. Competence and performance can differ arbitrarily. Thus, we should not expect DL models to illuminate linguistic theory.
Traditional arguments against the identification of the language of thought with natural language... more Traditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain philosophers and linguists to suggest that this identification is not as implausible as it once seemed. In this paper, I discuss the prospects for such an identification in light of these developments in linguistic theory. I raise a new challenge against the identification thesis: the existence of ungrammatical but acceptable expressions seems to require a gap between thought and language. I consider what must be the case in order for this objection to be dealt with.
In this paper, I shall provide a novel response to the argument from contextsensitivity against t... more In this paper, I shall provide a novel response to the argument from contextsensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language meaning. From this perspective, disparity between the scientific model and its realworld target is to be expected. I elaborate on what such an approach to semantics would look like.
I present a novel, collaborative, methodology for linguistics: what I call the 'explanatory econo... more I present a novel, collaborative, methodology for linguistics: what I call the 'explanatory economy'. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light.
Language has long been a problem-case for subsymbolic theories of mind. The reason for this is ob... more Language has long been a problem-case for subsymbolic theories of mind. The reason for this is obvious: Language seems essentially symbolic. However, recent work has developed a potential solution to this problem, arguing that linguistic symbols are public objects which augment a fundamentally subsymbolic mind, rather than components of cognitive symbol-processing. I shall argue that this strategy cannot work, on the grounds that human language acquisition consists in projecting linguistic structure onto environmental entities, rather than extracting this structure from them.
Traditional arguments against the identification of the language of thought with natural language... more Traditional arguments against the identification of the language of thought with natural language assume a picture of natural language which is largely inconsistent with that suggested by contemporary linguistic theory. This has led certain philosophers and linguists to suggest that this identification is not as implausible as it once seemed. In this paper, I discuss the prospects for such an identification in light of these developments in linguistic theory. I raise a new challenge against the identification thesis: the existence of ungrammatical but acceptable expressions seems to require a gap between thought and language. I consider what must be the case in order for this objection to be dealt with.
Inquiry: An Interdisciplinary Journal of Philosophy
In this paper, I shall provide a novel response to the argument from context-sensitivity against ... more In this paper, I shall provide a novel response to the argument from context-sensitivity against truth-conditional semantics. It is often argued that the contextual influences on truth-conditions outstrip the resources of standard truth-conditional accounts, and so truth-conditional semantics rests on a mistake. The argument assumes that truth-conditional semantics is legitimate if and only if natural language sentences have truth-conditions. I shall argue that this assumption is mistaken. Truth-conditional analyses should be viewed as idealised approximations of the complexities of natural language meaning. From this perspective, disparity between the scientific model and its real-world target is to be expected. I elaborate on what such an approach to semantics would look like.
I present a novel, collaborative, methodology for linguistics: what I call the 'explana-tory econ... more I present a novel, collaborative, methodology for linguistics: what I call the 'explana-tory economy'. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light.
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