(Benjamins Current Topics) Nikolas Gisborne, Willem B. Hollmann-Theory and Data in Cognitive...

Theory and Data in Cognitive Linguistics

Volume 67

Theory and Data in Cognitive LinguisticsEdited by Nikolas B. Gisborne and Willem HollmannThese materials were previously published in Studies in Language 36:3 (2012)

Benjamins Current TopicsSpecial issues of established journals tend to circulate within the orbit of the subscribers of those journals. For the Benjamins Current Topics series a number of special issues of various journals have been selected containing salient topics of research with the aim of finding new audiences for topically interesting material, bringing such material to a wider readership in book format.

For an overview of all books published in this series, please see http://benjamins.com/catalog/bct

http://benjamins.com/catalog/bct

Theory and Data in Cognitive Linguistics

Edited by

Nikolas B. GisborneUniversity of Edinburgh

Willem HollmannLancaster University

John Benjamins Publishing CompanyAmsterdam / Philadelphia

Library of Congress Cataloging-in-Publication Data

Theory and Data in Cognitive Linguistics / Edited by Nikolas B. Gisborne and Willem Hollmann.

p. cm. (Benjamins Current Topics, issn 1874-0081 ; v. 67)The genesis of this volume was a workshop at the Societas Linguistica Europaea

conference in Vilnius in 2010, organised by Hollmann and Gisborne, on the question of what specific contribution cognitive linguistics has made to the gathering and analysis of linguistic data.

Includes bibliographical references and index.1. Cognitive grammar--Data processing--Congress. 2. Semantics--Data processing--

Congress. I. Gisborne, Nikolas B., 1966- editor. II. Hollmann, Willem, editor.P165.T53 2014415--dc23 2014020747isbn 978 90 272 4255 6 (Hb ; alk. paper)isbn 978 90 272 6960 7 (Eb)

2014 John Benjamins B.V.No part of this book may be reproduced in any form, by print, photoprint, microfilm, or any other means, without written permission from the publisher.

John Benjamins Publishing Co. P.O. Box 36224 1020 me Amsterdam The NetherlandsJohn Benjamins North America P.O. Box 27519 Philadelphia pa 19118-0519 usa

8 TM The paper used in this publication meets the minimum requirements of the American National Standard for Information Sciences Permanence of Paper for Printed Library Materials, ansi z39.48-1984.

Table of contents

Introduction

Theory and data in cognitive linguistics 1Nikolas B. Gisborne and Willem B. Hollmann

Frequencies, probabilities, and association measures in usage-/exemplar-based linguistics: Some necessary clarifications 15

Stefan Th. Gries

Reconstructing constructional semantics: The dative subject construction in Old Norse-Icelandic, Latin, Ancient Greek, Old Russian and Old Lithuanian 49

Jhanna Bardal, Thomas Smitherman, Valgerur Bjarnadttir, Serena Danesi, Gard B. Jenset and Barbara McGillivray

The historical development of the it-cleft: A comparison of two different approaches 87

Amanda L. Patten

Theory and data in diachronic Construction Grammar: The case of the what with construction 115

Graeme Trousdale

The semantics of definite expressions and the grammaticalization of the 141Nikolas B. Gisborne

Cognitive explanations, distributional evidence, and diachrony 185Sonia Cristofaro

Word classes: Towards a more comprehensive usage-based account 211Willem B. Hollmann

Smashing new results on aspectual framing: How people talk about car accidents 239

Teenie Matlock, David Sparks, Justin L. Matthews, Jeremy Hunter and Stephanie Huette

Index 261

Introduction

Theory and data in cognitive linguistics

Nikolas B. Gisborne and Willem B. HollmannUniversity of Edinburgh / Lancaster University

The genesis of this volume was a workshop at the Societas Linguistica Europaea conference in Vilnius in 2010, organised by Hollmann and Gisborne, on the ques-tion of what specific contribution cognitive linguistics has made to the gathering and analysis of linguistic data. The workshop, Theory and data in cognitive linguis-tics, included the chapters in this volume by Bardal et al., Cristofaro, Gisborne, Hollmann, and Trousdale; Pattens chapter should have been presented at the conference, but the author was unable to attend; and the chapters by Gries and Matlock et al. were specially commissioned for this volume.

One of the motivations for the workshop was the observation that cognitive linguistics has an honourable tradition of paying respect to naturally occurring language data. In a tradition which typically describes itself as usage based, it makes sense to consider linguistic data in terms of what can actually be found. Therefore, for example, there have been fruitful interactions between corpus data and aspects of linguistic structure and meaning: Gries & Stefanowitsch (2006) have proposed a particular research strategy couched in construction grammar; Cuyckens et al. (2003) explored corpus data in the analysis of lexical semantics; and Bybee (2001) presented a usage-based approach to phonology. The usage-based research strategy has also led to an exploration of dialect data, sociolinguis-tic data collection methods, and sociolinguistic theoretical concepts in the light of the cognitive stance on language (Hollmann & Siewierska 2006, 2007, 2011; Clark and Watson 2011). In addition, there has been an increase in several kinds of experimental work seeking to link cognitive linguistics to current research in psycholinguistics (Bergen et al. 2007, Dbrowska 2008), as well as in attempts to combine evidence from various sources, as in Gries et al. (2005).

However, not all linguistic data is simply naturally occurring or derived from experiments with statistically robust samples of speakers. Other traditions, espe-cially the generative tradition, have fruitfully used introspection and questions about the grammaticality of different strings to uncover patterns which might otherwise have gone unnoticed. The difference between control and raising

2 Nikolas B. Gisborne and Willem B. Hollmann

patterns (Rosenbaum 1967), the distributional constraints on reflexive pro-nouns (Reinhart 1983), the island constraints (Ross 1967), and that-trace effects (Chomsky & Lasnik 1977) are all important linguistic phenomena which were uncovered by the research methodologies of the generative tradition. In relation to that-trace effects it is also worth mentioning the work of Cowart (1997) and Featherston (2005a, 2005b). Both of these generative grammarians have done im-portant pioneering work on turning acceptability judgments into a methodology that is considerably more robust than it had been in what Cowart first referred to as the Hey Sally method (1997: 2), where the researcher collects a few informal judgments at the most in addition to their own.

Some of the data sets considered by generative linguists have been subject to cognitive analyses: Van Hoek (1997) wrote on anaphora, while island constraints were discussed by Deane (1992), who attempted to locate the constraints in a view of language that was consistently embedded within a larger theory of human cog-nition. More recent cognitive work has addressed other topics which have been important in generative and formal theorising. For example, Bardal (2008) of-fered a cognitive perspective on quirky case marking, and Israel (2004) presented a cognitive analysis of polarity, a topic that has received extensive discussion in the generative and formal semantic literature.1 We might call the data sets analysed in these studies theoretically uncovered data, i.e. facts about language that linguists have discovered as a result of their particular theoretical tools.

There is also a diachronic tradition which, by necessity, must pay attention to real language data (because it could not otherwise describe phenomena) but where the degree to which data are (necessarily) idealized is contingent on wheth-er language change is viewed as sudden and abrupt (Lightfoot 1979) or gradual and incremental (Croft 2000, Hopper & Traugott 2003). The assumption that lan-guage change is catastrophic was first developed by Lightfoot in the generative tradition. The gradualist tradition is in line with cognitive assumptions about the organization of lexical and grammatical categories, and although it is usually not explicit, most (functionalist) work in grammaticalization is consistent with many of the research results of the cognitive tradition. Indeed, there is now an emerging body of work in diachronic construction grammar, such as Gisborne and Patten (2011), Israel (1996), Patten (2010), Traugott (2003), Trousdale (2008), and Patten (2010), which brings the functionalist and cognitive traditions together in explor-ing language change.

1. In a slightly different turn, some data which have been discussed within the generative tradi-tion have been subject to challenges by cognitive linguists as to their reliability, as in Dbrowskas (1997) study on WH-clauses.

Theory and data in cognitive linguistics 3

However, there are areas where cognitive linguists have neglected some of the data sets which have been important in generative theorising. For example, if we take language change, although there is work where the grammaticalization tradi-tion has examined the same data sets as generative linguists, such as the emergence of the English modals, there are areas where the two research paradigms have not converged. There are several generative studies of changes in word order, just as there are studies of changes in patterns of negation (van Kemenade 1999, Pintzuk 1999, Koopman 2005) but we are not aware of cognitive research into these topics.

Linguistic typology has not received as much attention from cognitive lin-guists as one would perhaps expect, given that crosslinguistic facts may give clues to cognitive structure (Croft 1998). Nevertheless, there has been enough work to see how a cognitive approach might differ from a generative one. Generative work (e.g. Baker 2009) is generally motivated by a search for Universal Grammar and tends to be based on relatively small language samples. Cognitive work on lin-guistic typology, by contrast, continues the legacy of the Greenbergian approach by using relatively large language samples, and by arguing that what is universal does not lie in language structure as such, but in speakers conceptual spaces and in the constraints on the mappings between functions and structures (Croft 2001, Cristofaro 2003).

Summing up the observations made thus far, we can see that the divide be-tween generative and cognitive approaches to language is intimately connected to the kinds of data drawn upon, the way in which generalisations are derived from these data, and how data is gathered. The divide is wide, but we note that there have been attempts to bridge it, to some extent on the cognitive side (Croft 1999), but more clearly by generative linguists such as Culicover & Jackendoff (2005). Some cognitive work sets out explicitly to address data and research questions that have been discovered and addressed in the generative tradition. Hudson (2003) is an exploration of gerunds within a cognitive theory of linguistic categories, and Gisborne (2010) includes a discussion of the perception verb complements which were a motivation for situation semantics (Barwise & Perry 1983) and event se-mantics (Higginbotham 1985).

In selecting the chapters for this volume, and indeed for the earlier workshop, we thought it was important to address the questions of the extent to which cog-nitive linguistics offered an alternative paradigm to the formalist traditions and, indeed, to what extent cognitive linguists spoke to linguists from formalist tra-ditions. As well as developing the research traditions that have emerged out of cognitive linguistics early focus on lexical semantics, and a respect for naturally occurring data, we thought that it was important to see how cognitive approaches could provide coherent and empirically sound accounts of the kinds of theoreti-cally uncovered data that we referred to above. If cognitive approaches can provide


robust accounts of those data, then they (should) have an advantage with regard to their compatibility with findings in cognitive psychology.

In addition, we took the view that cognitive linguists must critically evalu-ate their growing set of theoretical constructs and assumptions, some of which may not make clear contributions to our understanding of language (Broccias & Hollmann 2007). Essentially, against a background of how we gather and analyse our data, we wanted to offer a forum where cognitive linguists could critically evaluate their research practice and engage with a range of research questions, not only those which naturally arise within the cognitive research tradition.

As a result of the thoughts and ideas we describe above, we asked our con-tributors to address some specific questions and these questions frame the con-tents of the chapters which we have gathered in this volume. Although we describe each chapter in turn below, this is an opportune point to explain how the chapters generally fit the volume. The first question was whether cognitive linguistic ap-proaches could uncover generalisations that are not so easily uncovered in other approaches. Four chapters treat this question in various ways, those by Bardal et al., Gisborne, Patten, and Trousdale, which all have a historical focus as well, as does the chapter by Gries, which does not have a diachronic dimension. Another question was about the reliability status of theoretically uncovered data and gener-alisations: This is addressed in the chapters by Gries and Hollmann. We also won-dered whether there were assumptions in cognitive theories which do not have obvious benefits in the analysis of linguistic data, and the chapters by Cristofaro, Gries, and Hollmann address this. Finally, we were interested in how a theorys stance on the mind (is it embodied or encapsulated?) affects research results, and this question is addressed in the chapter by Matlock et al.

The contributions to this volume overlap in terms of the themes they address but, on top of that, they also fall into three clusters. A number of them seek to address the questions from a (partly) diachronic perspective: Patten, Trousdale, and Bardal et al. But Bardal et al.s main aim is to provide a blueprint for the reconstruction of constructional semantics, and its emphasis is thus really meth-odological. Griess chapter addresses methodology as well. Given the primacy of methodology in any field of research, these two chapters start off the volume, with Bardal et al. forming a natural bridge to the diachronic section. The remaining contributions by Gisborne, Cristofaro, Hollmann, and Matlock et al. primarily ad-dress theoretical issues. Gisbornes and Cristofaros chapters also discuss historical evidence and the nature of theoretical questions and thus figure here as a link to the final, theoretical section of the volume. Matlock et al.s chapter engages with general real world concerns as well, and language and power in particular. For this reason, it seemed fitting for their study to conclude this volume.

We now turn to discussing the chapters in more detail.


Gries

The chapter by Gries addresses a number of methodological questions which have come up in the cognitive literature. In particular, it addresses Bybees (2010) criti-cism of collostructional analysis and discusses the roles that frequencies, condi-tional probabilities, and association measures play in the study of co-occurrence phenomena in usage-based linguistics. Here the basic question is how to induce generalisations from a corpus, and the research strategy is to use modern statisti-cal techniques against a background notion of association measures as a way of exploring language structure from corpus data.

Griess chapter sets out to define and exemplify the method of collostructional analysis and to provide a range of references for its successful application. It also clarifies a number of misunderstandings about the method, particularly concern-ing the choice of association measures, and the robustness of the measures given different corpus sizes and observed frequencies. It then exemplifies the explana-tory and predictive power of collostructions from corpus data and experimental validation and outlines a research programme, or perspective, that views distribu-tional and co-occurrence data as important in cognitive theoretical research, and motivates it both theoretically and empirically.

Given his theorys statistical underpinnings, and strong commitment to nat-urally occurring data, Gries then relates co-occurrence data in constructions to Zipfian distributions and entropy, and proposes a new quantitative definition of construction.

Bardal et al.

Bardal et al.s chapter has a historical focus as well, but focuses on the area of reconstruction. In particular, the authors set out to reconstruct the dative subject construction in a proto-stage of Indo-European using evidence from Old Norse-Icelandic, Ancient Greek, Latin, Old Russian, and Old Lithuanian. The novelty of the chapter lies in the nature of the object of reconstruction. Within the field of reconstruction (see e.g. Fox 1995), the focus has traditionally been on struc-ture, especially phonological structure. Reconstructing the syntax and semantics of lexical items and grammatical morphemes has been more controversial and less common. But Bardal et al. go further than that by studying a complex construc-tion, defined as a form-meaning pairing.

In more traditional models such as Generative Grammar the research ques-tion addressed by the authors would not even arise, as constructions are not recog-nised. As a result, related work tends to propose a very abstract meaning for the


dative case. By contrast, here, as well as in earlier work by Bardal (e.g. 2009), constructions are not only recognised but, following Croft (2001), they are seen as the very building blocks of grammar. Thus, dative case markers are seen as an integral part of the various constructions they occur in, and the task of recon-structing the dative becomes the task of reconstructing constructions featuring this case marker.

Bardal et al. investigate semantic differences and similarities among the data from the five different branches of Indo-European included in their sample, and on this basis, reconstruct a possible proto-stage. Due to the exclusion of a number of other branches, they do not make any general claims about proto-Indo European as a whole, but rather suggest that their reconstruction may be applicable to a West-Indo-European stage.

An important tool in Bardal et al.s reconstruction is the semantic map model (see e.g. Croft 2001, Haspelmath 2003). Unlike the generative quest for Universal Grammar, the semantic map approach begins with the suggestion that what lan-guages share is conceptual, and that language universals are to be discovered in constraints on the mapping between the conceptual plane and linguistic structure.

Patten

Pattens contribution is one of several in this volume that put cognitive linguistics through its paces in the context of diachrony. She focuses on the history of the it-cleft in English.

It-clefts have not received very much attention in the historical literature apart from handbooks such as Visser (1963). Recently, however, they have started to attract more attention, especially perhaps within the generative tradition, see e.g. Ball (1991, 1994) and Perez-Guerra (1999). Pattens study starts by outlining the generative account of Ball, who suggests that it-clefts emerged in Middle English from the NP BEON Rel-Clause pattern. Balls story bears considerable similarity to Lightfoots classical account of the rise of English modal verbs in terms of the proposed abrupt profile of the change. Patten contrasts this with a more gradualist reconstruction, where the it-cleft is seen as a development from the Old English hit-cleft construction. As a result, some properties of the Present-day English cleft, related to their peculiar syntax as well as their specificational function, fall into place.

From the point of view of the volume, a particularly interesting shortcoming Patten reveals in generative work is that the pattern on which Ball suggests the it-cleft is based is actually very rare, occurring only in translations from Latin. In the Generative model frequency is generally not given very much importance,


but most cognitive linguists subscribe to the usage-based model, in which fre-quency plays a crucial role in relation to grammatical representation (see e.g. Bybee 1985, Croft 2000). It is intuitively implausible that such a rare and restricted pattern should have given rise to the relatively frequent it-clefts, and the usage-based model provides a natural and empirically based framework for this position. Another respect in which Pattens contribution engages with the questions posed in this volume is that she argues that Ball disregards the Old English hit-clefts be-cause they do not fit the abrupt, Lightfootian model of change.

Trousdale

The contribution by Trousdale is historical as well. Like Patten, the author com-pares a generative linguistic account (Felser & Britain 2007) to a cognitive, con-struction-based one. Yet where Pattens chapter deals with the fairly common it-clefts, Trousdale studies the rather infrequent what with construction, e.g. What with the high cost of living in this area, double income households are the norm.

Trousdale starts by summarising Felser & Britains (2007) analysis, which re-jects a constructionist view of the pattern, arguing instead that the meaning of what with is fully compositional and can be accounted for within the Minimalist model of phrase structure. As Trousdale notes, semantic unpredictability was in-deed a property of constructions according to Goldberg (1995). This view has been abandoned by Goldberg (2006), however, on the condition that the construction is frequent enough to become entrenched with its fully predictable meaning. The unpredictability stipulation was, moreover, never part of the construction-based cognitive approaches of Langacker (1987) and Croft (2001).

Trousdale moves on to discuss what with from the perspective of construction grammar, drawing attention to the various sub-types of the construction. Their gradual historical development is seen to consist of a number of micro-changes (Brinton & Traugott 2005: 150). Some of these changes involve narrowing and re-duction, while others display broadening and expansion. We observe reduction in terms of the prepositions that co-occur with (the ancestor of) this construc-tion, with e.g. what by and what from falling out of use. On the other hand, while the construction used to be mainly restricted to two coordinated noun phrase complements, other types of complements have become possible over time, with no need for coordination. Overall, the profile of the change fits especially well with the recent literature on grammatical constructionalisation (e.g. Himmelmann 2004, Traugott 2010). However, in relation to the theme of the volume Trousdale also notes that recent generative literature pays more attention to micro-chang-es (see e.g. Roberts 2010). He concludes that there is thus (an opportunity for)


a degree of rapprochement between the generative and cognitive approaches to language change.

Gisborne

Gisbornes chapter is concerned with three related questions: what is the proper analysis of a definite expression as a quantified expression or as an expression of discourse familiarity; how can the alternative approaches be modelled in a cogni-tive theory, especially as the debate has largely been conducted in different models of formal semantics; and which theory best accounts for the historical development of the English definite article? Gisborne argues that the best treatment of definite expressions is that they are in fact quantified, as originally proposed in Russell (1905), and he goes on to elaborate a set-based treatment of definite expressions modelled in one particular cognitive theory, Word Grammar (Hudson 1990, 2007).

The chapter argues that the diachrony of the English definite article is straight-forwardly accounted for in this semantic approach because there is no need to assume that there are major semantic changes in the development from demon-strative to definite article. Instead, what is seen is a loss of the deictic element in the meaning of the demonstrative, with the result that the meaning of the definite article is somewhat more abstract.

This chapter shows that it is possible to model research findings from formal semantics within a cognitive theory, and it sets out to show that a full evaluation of different theoretical positions requires an exploration of both diachronic facts and synchronic distributions, which brings about certain similarities with Cristofaros chapter. It is also argued that the cognitive embedding of the semantics of definite expressions makes a theory of change more straightforward than a model theo-retic semantics would.

Cristofaro

The chapter by Cristofaro is yet another chapter with a diachronic dimension. The general issue that concerns the author is how to weigh synchronic evidence against diachronic evidence in cognitive explanations of linguistic patterns. The data that the chapter is concerned with mostly involves prototype effects in dependent clauses and alignment phenomena, such as ergative-absolutive vs. nominative-accusative case marking, and the question of whether synchronic evidence and theories based on synchronic evidence lead to robust conclusions about underly-ing cognitive mechanisms.


Cristofaro observes that synchronic distributional patterns, such as can be found in alignment systems and the parts of speech are routinely taken as evidence for specific cognitive mechanisms. However, one of the issues that this approach does not address is that these cognitive mechanisms do not appear to play any role in the diachronic development of these constructions. For example, nomina-tive, ergative, and active alignment systems often originate from processes which are independent of the cognitive mechanisms that are postulated to account for these systems on synchronic grounds. Likewise, some types of prototype effects, such as those found in dependent clauses, arise from processes that are arguably independent of the fact that the relevant grammatical categories have a prototype structure.

Cristofaros conclusion is that synchronic distributional evidence cannot be tak-en as evidence for specific cognitive mechanisms, in the sense that it is not clear that these mechanisms actually lead speakers to create or use particular constructions.

Hollmann

The possibility of a rapprochement between (some versions of) generative and cognitive linguistics is also suggested by Hollmann, albeit in a very different con-text. His contribution addresses the representation of word classes. Traditionally, word classes have been one of the main areas of debate between generative and cognitive linguists. Generative grammarians (e.g. Baker 2003, Aarts 2007) tend to emphasise distributional properties, while cognitive linguists argue that categori-sation is determined semantically (Langacker 1987) or semantically-pragmatically (Croft 2001). However, Hollmann suggests that the distinction between the two traditions is perhaps not as sharp as it might appear, as Crofts suggestions con-cerning the discourse propositional act functions of the different word classes may be translated into language-particular distributional properties.

Focusing on English word classes, Hollmann reports on a production experi-ment in which subjects were asked to devise novel nouns and verbs, and use these in a sentence. The phonological and distributional properties of these nonce forms were then analysed. With regard to phonology, the results revealed a high degree of overlap with work on lexical categorisation in psycholinguistics (e.g. Cassidy & Kelly 1991, Kelly 1992, 1996, Monaghan et al. 2005).

In relation to the theme of this volume, the psycholinguistic evidence sug-gests that both generative and cognitive linguists have failed to acknowledge cer-tain highly relevant facts. Incorporating phonology into the models, for example, would lead to more convergence. The analysis of the syntax of the novel forms led to an interesting conclusion as well: at least some distributional facts emphasised


in the generative model in particular, co-occurrence with a determiner may be more important than one might expect on the basis of cognitive linguistic work.

One important caveat Hollmann notes with regard to the potential conver-gence between generative and cognitive linguists is that one extreme incarnation of generative grammar, i.e. Distributed Morphology (Halle & Marantz 1993), would fare very poorly indeed in the face of the evidence presented in this chapter. Theorising in DM thus constitutes a paradigm case of the kinds of formal linguis-tic overabstraction lamented by the psycholinguist Ferreira (2005).

Matlock et al.

The contribution by Matlock et al. invokes the notion of embodiment. Embodiment is the suggestion in cognitive science and philosophy that our bodily experience shapes aspects of the mind. Embodiment thus poses a challenge to traditional Cartesian dualism. In the context of the Modularity Hypothesis made by genera-tive grammar, it is unsurprising that embodiment has not been accorded a place in the theory, while it has been naturally incorporated into cognitive linguistics. One example of this is the cognitive linguistic account of metaphors based on bodily experience, such as Good is Up and Bad is Down (see e.g. Johnson 1987, Lakoff 1987, Lakoff & Johnson 1999). Matlock et al. relate embodiment to the language and gestures produced in a task where subjects watched a video of a car accident and were then asked to describe what happened vs. what was happening. The authors show that the imperfective question yielded more details being provided, i.e. more motion verbs and expressions related to reckless driving being used, and more iconic gestures being produced.

Much of Matlocks previous work (e.g. 2004, Gibbs & Matlock 2008) is centred on the notion of mental simulation, i.e. the mental reactivation of patterns associ-ated with past bodily experiences. Here, Matlock et al. argue that the imperfective aspect invites a different kind of mental simulation of the events witnessed, along the lines suggested by the classic typological literature on aspect (e.g. Comrie 1976, Dahl 1985).

With regard to the questions that this thematic volume is built around, Matlock et al. show how, in relation to the language and gestures evoked by differ-ent aspectual framing, a cognitive linguistic viewpoint may represent an advan-tage over a modular theory such as generative grammar. Yet at the same time it reveals that there is considerable scope left for cognitive linguists to do research on how language structure might guide interpretation in real world situations. The present study very clearly raises the issue of leading questions in for example a courtroom setting an issue that cognitive linguistics may at least begin to


address. The closely related issue of language and power has been addressed in a very different tradition, i.e. that of Critical Discourse Analysis (e.g. Fairclough 2001, van Dijk 2008). Yet the present study (and see also Fausey & Matlock 2011 for a study of aspect in discourse about politics) is considerably more convincing in terms of a detailed study of empirical, psycholinguistic evidence than work in CDA tends to be.

References

Aarts, Bas. 2007. Syntactic gradience: The nature of grammatical indeterminacy. Oxford: Oxford University Press.

Baker, Mark C. 2003. Lexical categories: Verbs, nouns, and adjectives. Cambridge: Cambridge University Press.

Baker, Mark. 2009. Formal Generative Typology. In B. Heine and H. Narrog (eds.), The Oxford handbook of linguistic analysis, 285312. Oxford: Oxford University Press.

Ball, Catherine N. 1991. The historical development of the it-cleft. Philadelphia, PA: University of Pennsylvania dissertation.

Ball, Catherine N. 1994. The origins of the informative-presupposition it-cleft. Journal of Pragmatics 22. 603628.

Bardal, Jhanna. 2008. Productivity: Evidence from case and argument structure in Icelandic. Amsterdam: John Benjamins.

Bardal, Jhanna. 2009. The development of case in Germanic. In Jhanna Bardal & Shobhana L. Chelliah (eds.), The role of semantic, pragmatic and discourse factors in the development of case, 123159. Amsterdam: John Benjamins.

Barwise, Jon & John Perry. 1983. Situations and attitudes. Cambridge, MA: MIT Press.Bergen, Benjamin, Shane Lindsay, Teenie Matlock & Srini Narayanan. 2007. Spatial and linguis-

tic aspects of visual imagery in sentence comprehension. Cognitive Science 31. 733764.Brinton, Laurel, and Elizabeth Closs Traugott. 2005. Lexicalization and language change.

Cambridge: Cambridge University Press.Broccias, Cristiano & Willem B. Hollmann. 2007. Do we need summary and sequential scan-

ning in (Cognitive) grammar? Cognitive Linguistics 18. 487522Bybee, Joan. 1985. Morphology. Amsterdam: John Benjamins.Bybee, Joan L. 2001. Phonology and language use. Cambridge: Cambridge University Press.Bybee, Joan. 2010. Language, usage, and cognition. Cambridge: Cambridge University Press.Cassidy, Kimberley W. & Michael H. Kelly. 1991. Phonological information for grammatical

category assignment. Journal of Memory and Language 30. 348369.Chomsky, Noam & Howard Lasnik. 1977. Filters and Control. Linguistic Inquiry 8. 425504.Clark, Lynn & Kevin Watson. 2011. Testing claims of a usage-based phonology with Liverpool

English t-to-r. English Language and Linguistics 15. 523547.Comrie, Bernard. 1976. Aspect. Cambridge, MA: Cambridge University Press.Cowart, W. 1997. Experimental syntax: Applying objective methods to sentence judgments.

London: Sage Publications.Cristofaro, Sonia. 2003. Subordination. Oxford: Oxford University Press.


Croft, William. 1998. Linguistic evidence and mental representations. Cognitive Linguistics 9. 151173.

Croft, William. 1999. What (some) functionalists can learn from (some) formalists. In M. Darnell, E. Moravcsik, F. Newmeyer, M. Noonan & K. Wheatley (eds.), Functionalism and formalism in linguistics, 85108. Amsterdam: John Benjamins.

Croft, William. 2000. Explaining language change: An evolutionary approach. Harlow: Longman.Croft, William. 2001. Radical Construction Grammar: Syntactic theory in typological perspective.

Oxford: Oxford University Press.Culicover, Peter, and Ray Jackendoff. 2005. Simpler syntax. Oxford: Oxford University Press.Cuyckens, Hubert, Ren Dirven & John R. Taylor (eds.). 2003. Cognitive approaches to lexical

semantics. Berlin: Mouton de Gruyter.Dbrowska, Ewa. 1997. The LAD goes to school: A cautionary tale for nativists. Linguistics 35.

735766.Dbrowska, Ewa. 2008. Questions with long-distance dependencies: A usage-based perspective.

Cognitive Linguistics 19. 391425.Dahl, sten. 1985. Tense and aspect systems. New York: Basil Blackwell.Deane, Paul D. 1992. Grammar in mind and brain. Berlin: Mouton de Gruyter.Dijk, Teun van. 2008. Discourse and power. Houndsmills: Palgrave.Fairclough, Norman. 2001. Language and power, 2nd edn. Harlow: Longman.Fausey, Caitlin M. & Teenie Matlock. 2011. Can grammar win elections? Political Psychology 32.

563473.Featherston, Sam. 2005a. That-trace in German. Lingua 115. 12771302.Featherston, Sam. 2005b. Magnitude estimation and what it can do for your syntax: Some wh-

constraints in German. Lingua 115. 15251550Felser, Claudia & David Britain. 2007. Deconstructing what with absolutes. Essex Research

Reports in Linguistics 53: 97134.Ferreira, Fernanda. 2005. Psycholinguistics, formal grammars, and cognitive science. The

Linguistic Review 22. 365380.Fox, Anthony. 1995. Linguistic reconstruction. Oxford: Oxford University Press.Gibbs, Raymond W. & Teenie Matlock. 2008. Metaphor, imagination, and simulation:

Psycholinguistic evidence. In Raymond W. Gibbs, Jr. (ed.), Cambridge handbook of meta-phor and thought, 161176. New York: Cambridge University Press.

Gisborne, Nikolas B. 2010. The event structure of perception verbs. Oxford: Oxford University Press.

Gisborne, Nikolas B. & Amanda Patten. 2011. Constructions and grammaticalization. In Bernd Heine & Heiko Narrog (eds.), The Oxford handbook of grammaticalization, 92104. Oxford: Oxford University Press.

Goldberg, Adele E. 1995. Constructions: A construction grammar approach to argument struc-ture. Chicago: University of Chicago Press.

Goldberg, Adele E. 2006. Constructions at work: On the nature of generalization in language. Oxford: Oxford University Press.

Gries, Stefan Th. & Anatol Stefanowitsch (eds.). 2006. Corpora in cognitive linguistics: Corpus-based approaches to syntax and lexis. Berlin/New York: Mouton de Gruyter.

Gries, Stefan Th., Beate Hampe & Doris Schnefeld. 2005. Converging evidence: Bringing together experimental and corpus data on the association of verbs and constructions. Cognitive Linguistics 16. 635676.


Halle, Morris & Alec Marantz. 1993. Distributed Morphology and the pieces of inflection. In Kenneth Hale & S. Jay Keyser (eds.), The view from Building 20, 111176. Cambridge, MA: MIT Press.

Haspelmath, Martin. 2003. The geometry of grammatical meaning: Semantic maps and cross-linguistic comparison. In M. Tomasello (ed.), The new psychology of language, vol. 2, 211242. Mahwah, NJ: Lawrence Erlbaum.

Higginbotham, James. 1985. On semantics. Linguistic Inquiry 16. 547593.Himmelmann, Nikolaus. 2004. Lexicalization and grammaticization: Opposite or orthogonal?

In Walter Bisang, Nikolaus Himmelmann & Bjrn Wiemer (eds.), What makes grammati-calization? A look from its components and its fringes, 2142. Berlin: Mouton de Gruyter.

Hollmann, Willem B. & Anna Siewierska. 2006. Corpora and (the need for) other methods in a study of Lancashire dialect. Zeitschrift fr Anglistik und Amerikanistik 54. 203216.

Hollmann, Willem B. & Anna Siewierska. 2007. A construction grammar account of possessive constructions in Lancashire dialect: Some advantages and challenges. English Language and Linguistics 11. 407424.

Hollmann, Willem B. & Anna Siewierska. 2011. The status of frequency, schemas, and iden-tity in Cognitive Sociolinguistics: A case study on definite article reduction. Cognitive Linguistics 22. 2554.

Hopper, Paul & Elizabeth Traugott. 2003. Grammaticalization, 2nd edn. Cambridge: Cambridge University Press.

Hudson, Richard. 1990. English word grammar. Oxford: Basil Blackwell.Hudson, Richard. 2003. Gerunds and multiple default inheritance. Natural Language and

Linguistic Theory 21. 579615Hudson, Richard. 2007. Language Networks. Oxford: Oxford University Press.Israel, Michael. 1996. The way constructions grow. In Adele E. Goldberg (ed.), Conceptual struc-

ture, discourse and language, 217230. Stanford: CSLI.Israel, Michael. 2004. The pragmatics of polarity. In Laurence Horn and Gregory Ward (eds.),

The handbook of pragmatics, 701723. Oxford: Blackwell.Johnson, Mark. 1987. The body in the mind: The bodily basis of meaning, imagination and reason.

Chicago: University of Chicago Press.Kelly, Michael 1996. The role of phonology in grammatical category assignment. In James L.

Morgan and Katherine Demuth (eds.), From signal to syntax, 249262. Hillsdale: Erlbaum.Kelly, Michael H. 1992. Using sound to solve syntactic problems: The role of phonology in gram-

matical category assignments. Psychological Review 99. 349364.Koopman, Willem. 2005. Transitional syntax: Postverbal pronouns and particles in Old English.

English Language and Linguistics 9. 4762.Lakoff, George & Mark Johnson. 1999. Philosophy in the flesh: The embodied mind and its chal-

lenge to Western thought. New York: Basic Books.Lakoff, George. 1987. Women, fire and dangerous things: What categories reveal about the mind.

Chicago: University of Chicago Press.Langacker, Ronald W. 1987. Foundations of cognitive grammar. Volume 1: Theoretical prerequi-

sites. Stanford: Stanford University Press.Lightfoot, David W. 1979. Principles of diachronic syntax. Cambridge: Cambridge University Press.Matlock, T. 2004. Fictive motion as cognitive simulation. Memory & Cognition 32. 13891400.Monaghan, Padraic, Nick Chater & Morten H. Christiansen. 2005. The differential role of pho-

nological and distributional cues in grammatical categorisation. Cognition 96. 143182.


Patten, Amanda. 2010. Cleft sentences and grammaticalization. University of Edinburgh disser-tation.

Prez-Guerra, Javier. 1999. Historical English syntax: A statistical corpus-based study on the organisation of Early Modern English sentences (Studies in Germanic Linguistics 11). Mnchen: Lincom Europa.

Pintzuk, Susan. 1999. Phrase structures in competition: Variation and change in Old English word order. New York: Garland.

Reinhart, Tanya. 1983. Anaphora and semantic interpretation. London: Croom Helm.Roberts, Ian G. 2010. Grammaticalization, the clausal hierarchy, and semantic bleaching. In

Elizabeth Traugott & Graeme Trousdale (eds.), Gradience, gradualness and grammaticaliza-tion, 4573. Amsterdam: Benjamins.

Rosenbaum, Peter S. 1967. The grammar of English predicate complement constructions. Cambridge, MA: MIT Press.

Ross, John Robert. 1967. Constraints on variables in syntax. MIT dissertation.Russell, Bertrand. 1905. On denoting. Mind 14. 479493.Traugott, Elizabeth. 2003. Constructions in grammaticalization. In Brian D. Joseph & Richard

D. Janda (eds.), A handbook of historical linguistics, 624647. Oxford: Blackwell.Traugott, Elizabeth Closs. 2010. Grammaticalization. In Silvia Luraghi & Vit Bubenik (eds.), The

Continuum companion to historical linguistics. London: Continuum, 269283.Trousdale, Graeme. 2008. Constructions in grammaticalization and lexicalization: Evidence

from the history of a composite predicate in English. In Graeme Trousdale & Nikolas B. Gisborne (eds.), Constructional approaches to English grammar, 3367. Berlin/New York: Mouton de Gruyter

Van Hoek, Karen. 1997. Anaphora and conceptual structure. Chicago: University of Chicago Press.Van Kemenade, Ans. 1999. Sentential negation and word order in Old English. In Ingrid Tieken-

Boon van Ostade, Gunnel Tottie & Wim van de Wurff (eds.), Negation in the history of English, 147166. Berlin: Mouton de Gruyter.

Visser, F. Th. 1963. An historical syntax of the English language, Part 1: Syntactical units with one verb. Leiden: Brill.

Frequencies, probabilities, and association measures in usage-/exemplar-based linguisticsSome necessary clarifications*

Stefan Th. GriesUniversity of California, Santa Barbara

In the last few years, a particular quantitative approach to the syntax-lexis interface has been developed: collostructional analysis (CA). This approach is an application of association measures to co-occurrence data from corpora, from a usage-based/cognitive-linguistic perspective. In spite of some popularity, this approach has come under criticism in Bybee (2010), who criticizes the method for several perceived shortcomings and advocates the use of raw frequencies/percentages instead. This chapter has two main objectives. The first is to refute Bybees criticism on theoretical and empirical grounds; the second and further-reaching one is to outline, on the basis of what frequency data really look like, a cline of analytical approaches and, ultimately, a new perspective on the notion of construction based on this cline.

1. Introduction

Linguistics is a fundamentally divided discipline, as far as theoretical foundations and empirical methodology are concerned. On the one hand and with some sim-plification, there is the field of generative grammar with its assumptions of (i) a highly modular linguistic system within a highly modular cognitive system (ii) with considerable innate structure given the poverty of the stimulus, and (iii) a

* This chapter is a revised and extended version of a plenary talk I gave at the 6th International Conference on Construction Grammar in Prague. I thank the audience there, workshop par-ticipants and panel discussants at the Freiburg Institute of Advanced Studies, students of my doctoral seminar on psycholinguistics at UCSB, the audience of a Linguistics Colloquium talk at UC Berkeley, and (in alphabetical order) William Croft, Sandra C. Deshors, Adele E. Goldberg, Anatol Stefanowitsch, and Stefanie Wulff for feedback, input, and/or discussion. I also thank two anonymous reviewers and the editors of this volume for their comments. The usual dis-claimers apply.

16 Stefan Th. Gries

methodology largely based on made-up judgments of made-up (often context-free) sentences. On the other hand and with just as much simplification, there is the field of cognitive/functional linguistics with its emphasis on (i) domain-general mechanisms, (ii) pattern-learning based on statistical properties of the input, and (iii) an (increasing) reliance on various sorts of both experimental and observational data.

Over the last 25+ years, this latter field has amassed evidence calling into the question the assumption of a highly modular linguistic system, a large amount of innate structure, and the reliability of the predominant kind of acceptability judg-ment data. First, there is now a lot of experimental evidence that shows how much aspects of syntax interact with, or are responsive to, e.g., phonology, semantics, or non-linguistic cognition. Second, many studies have now demonstrated that the supposedly poor input is rich in probabilistic structure, which makes many of the supposedly unlearnable things very learnable. Third, Labov and Levelt, among others, already showed in the early 1970s that the judgments that were adduced to support theoretical developments were far from uncontroversial and that better ways of gathering judgment data are desirable. Over the last few years, corpus data have especially become one of the most frequently used alternative types of data.

This movement towards empirically more robust data is desirable. However, while (psycho)linguistic experimentation has a long history of methodological development and refinement, the situation is different for corpus data. While cor-pus linguistic approaches have been around for quite a while, the methodological evolution of corpus linguistics is still a relatively young development and many corpus-based studies are lacking the methodological sophistication of much of the experimental literature. This situation poses a bit of a challenge because, while a usage-based approach to language an approach stipulating that the use of language affects the representation and processing language does not require usage data, the two are of course highly compatible. This makes the development of an appropriate corpus-linguistic toolbox an important goal for usage-based lin-guistics.

This chapter is concerned with a recent corpus-based approach to the syntax-lexis interface called collostructional analysis (CA), which was developed to apply recent developments in corpus linguistics to issues and questions in cognitive/us-age-based linguistics. Most recently, however, this approach was criticized (Bybee 2010: Section 5.12) for several perceived shortcomings. The first part of this chap-ter constitutes a response to Bybees claims, which result from a lack of recognition of the methods assumptions, goals, and published results. However, I will also discuss a variety of cognitive-linguistic and psycholinguistic notions which are of relevance to a much larger audience than just collostructional researchers and which speak to the relation between data and the theory supported or required by

Frequencies, probabilities, and association measures in usage-/exemplar-based linguistics 17

such data. Section 2 provides a brief explanation of the collostructional approach while the approach is now reasonably widespread, this is necessary for the sub-sequent discussion. Section 3 presents the main claims made by Bybee, which I will then address in Section 4. Section 5 will develop a cline of co-occurrence complexity and discuss its theoretical motivations and implications with a variety of connections to psychological and psycholinguistic work.

2. Collostructional analysis: A brief overview

2.1 Perspective 1: CA and its goals

All of corpus linguistics is by definition based on frequencies either on the ques-tion of whether something occurs (i.e., is a frequency n > 0?) or not (i.e., is n = 0?) or on the question of how often something occurs (how large is n?) which makes it a distributional discipline. Since linguists are usually not that much interested in frequencies per se but rather structure, semantics/meaning, pragmatics/func-tion, etc., corpus-linguistic work has to make one very fundamental assumption, namely that distributional characteristics of an element reveal many if not most of its structural, semantic, and pragmatic characteristics; cf. the following quote by Harris (1970: 785f.):

[i]f we consider words or morphemes A and B to be more different in meaning than A and C, then we will often find that the distributions of A and B are more different than the distributions of A and C. In other words, difference of meaning correlates with difference of distribution.

A more widely-used quote to make the same point is Firths (1957: 11) [y]ou shall know a word by the company it keeps. Thus, corpus-linguistic studies of words have explored the elements with which, say, words in question co-occur, i.e., the lexical items and, to a much lesser degree, grammatical patterns with which words co-occur their collocations and their colligations. However, since some words overall frequencies in corpora are so high that they are frequent nearly everywhere (e.g., function words), corpus linguists have developed measures that downgrade/penalize words whose high frequency around a word of interest w may reflect more their overall high frequency than their revealing association with w. Such measures are usually referred to as association measures (AMs) and are usually applied such that one

i. retrieves all instances of a word w;ii. computes an AM score for every collocate of w (cf. Wiechmann 2008 or Pecina

2009 for overviews);

18 Stefan Th. Gries

iii. ranks the collocates of w by that score;iv. explores the top t collocates for functional patterns (where functional encom-

passes semantic, pragmatic, information-structural, ).

Thus, the purpose of ranking words on the basis of such AMs is to produce a ranking that will place words at the top of the list that (i) have a relatively high frequency around w while (ii) not being too frequent/promiscuous around other words.

2.2 Perspective 2: CA and its mathematics/computation

CA is the extension of AMs from lexical co-occurrence a word w and its lexical collocates to lexico-syntactic co-occurrence: a construction c and the x words w1, w2, , wx in a particular slot of c. Thus, like most AMs, CA is based on (usu-ally) 22 tables of observed (co-)occurrence frequencies such as Table 1.

Table 1. Schematic frequency table of two elements A and B and their co-occurrenceB B Totals

A nA & B nA & B nAA nA & B nA & B nATotals nB nB nA & B & A & B

Two main methods are distinguished. In the first, collexeme analysis (cf. Stefanowitsch & Gries 2003), A is a construction (e.g., the ditransitive NP V NP1 NP2), A corresponds to all other constructions in the corpus (ideally on the same level of specificity), B is a word (e.g., give) occurring in a syntactically-defined slot of such constructions, and B< corresponds to all other words in that slot in the corpus. A collexeme analysis requires such a table for all x different types of B in

1. The expected frequencies are computed as in every contingency table or in chi-square tests for independence. The expected frequency in each cell is the result of row total times column to-tal divided by the sum of all frequencies in the table. For instance, 10351160/138,664 8.66 9.

Table 2. Observed frequencies of give and the ditransitive in the ICE-GB (expected fre-quencies in parentheses; from Stefanowitsch & Gries 2003)1

Verb: give Other verbs TotalsConstruction:ditransitive

461 (9) 574 (1,026) 1,035

Other clause-level constructions

699 (1,151) 136,930 (136,478) 137,629

Totals 1,160 137,504 138,664


the relevant slot of A. For example, Table 2 shows the frequency table of give and the ditransitive based on data from the ICE-GB. Each of these x tables is analyzed with an AM; as Stefanowitsch & Gries (2003: 217) point out, [i]n principle, any of the measures proposed could be applied in the context of CA. Most applications of CA use the p-value of the Fisher-Yates exact test (pFYE) or, as a more easily inter-pretable alternative, the (usually) negative log10 of that p-value (cf. Gries, Hampe & Schnefeld 2005: 671f., n. 13).

The authors give several reasons for choosing pFYE, two of which (cf. Pedersen 1996) I mention here, a third important one will be mentioned in Section 2.3.

i. exact tests do not make distributional assumptions that corpus data usu-ally violate, such as normality and/or homogeneity of variances (cf. Gries & Stefanowitsch 2004: 101);

ii. because of the Zipfian distribution of words in a constructions slot, any AM one might want to use must be able to handle the small frequencies that char-acterize Zipfian distributions (Stefanowitsch & Gries 2003: 204) and at the same not be anti-conservative.

For Table 2, the pFYE is a very small p-value (< 4.94e324) or a very large log10 of that p-value (> 323.3062) so the mutual attraction between give and the ditran-sitive is very strong. This measure is then computed for every verb type in the ditransitive so that the verbs can be ranked according to their attraction to the di-transitive. This entails that the p-values are mainly used as an indicator of relative importance (cf. Stefanowitsch & Gries 2003: 239, n. 6), and virtually all collostruc-tional applications have focused only on the 20 to 30 most highly-ranked words and their semantic characteristics (although no particular number is required).

For the second method, distinctive collexeme analysis (cf. Gries & Stefanowitsch 2004a), the 22 table is set up differently: A corresponds to a construction (e.g., the ditransitive), A corresponds to a functionally similar construction (e.g., the prepositional dative NP V NP PPfor/to), B corresponds to a word (e.g., give) occur-ring in syntactically-defined slots of A, and B corresponds to all other words in the slots/the corpus; cf. Table 3.

Table 3. Observed frequencies of give and the ditransitive and the prepositional to-dative in the ICE-GB (expected frequencies in parentheses; from Gries & Stefanowitsch 2004)

Verb: give Other verbs TotalsConstruction:ditransitive

461 (213) 574 (822) 1,035

Construction:prepositional dative

146 (394) 1,773 (1,525) 1,919

Totals 607 2,347 2,954

20 Stefan Th. Gries

Again, this results in a very small pFYE (1.835954e-120) or very large negative logged10 p-value (119.7361), indicating that gives preference for the ditransitive over the prepositional dative is strong. Again, one would compute this measure for all x verbs attested at least once in either the ditransitive or the prepositional to-dative, rank-order the x verbs according to their preference and strength of preference, and then inspect the, say, top t verbs for each construction.

Other extensions of CA are available and have been used. One, multiple dis-tinctive collexeme analysis, extends distinctive collexeme analysis to cases with more than two constructions (e.g., the will-future vs. the going-to future vs. the shall-future vs. present tense with future meaning). Another one, covarying collex-eme analysis, computes measures for co-occurrence preferences within one con-struction (cf. Gries & Stefanowitsch 2004b).2

2.3 Perspective 3: CA and its results, interpretation, and motivation

As outlined above, CA returns ranked lists of (distinctive) collexemes, which are analyzed in terms of functional characteristics. For the ditransitive data discussed above with Table 2, the rank-ordering in (1) emerges:

(1) give, tell, send, offer, show, cost, teach, award, allow, lend, deny, owe, promise, earn, grant, allocate, wish, accord, pay, hand,

Obviously, the verbs are not distributed randomly across constructions, but reveal semantic characteristics of the constructions they occupy. Here, the verbs in (1) clearly reflect the ditransitives meaning of transfer (most strongly-attract-ed verbs involve transfer), but also other (related) senses of this construction (cf. Goldbergs 1995: Ch. 5): (non-)enablement of transfer, communication as transfer, perceiving as receiving, etc.

Similarly clear results are obtained from comparing the ditransitive and the prepositional dative discussed above with Table 3. The following rank-orderings emerge for the ditransitive (cf. (2)) and the prepositional dative (cf. (3)):

(2) give, tell, show, offer, cost, teach, wish, ask, promise, deny,

(3) bring, play, take, pass, make, sell, do, supply, read, hand,

Again, the verbs preferring the ditransitive strongly evoke the notion of trans-fer, but we also see a nice contrast with the verbs preferring the prepositional da-tive, which match the proposed constructional meaning of continuously caused (accompanied) motion. Several verbs even provide nice empirical evidence for

2. All of these CA methods (with different AMs) can be computed easily with an interactive R script available at .

http://tinyurl.com/collostructions


an iconicity account of the dative alternation as proposed by Thompson & Koide (1987): Verbs such as bring, play, take, and pass involve some greater distance be-tween the agent and the recipient (pass here mostly refers to passing a ball in soc-cer), certainly greater than the one prototypically implied by give and tell.

By now, this method has been used successfully on data from different lan-guages (e.g., English, German, Dutch, Swedish, ) and in different contexts (e.g., constructional description in synchronic data, syntactic alternations (Gilquin 2006), priming phenomena (Szmrecsanyi 2006), second language acquisition (Gries & Wulff 2005, 2009, Deshors 2010), and diachronic language change (Hilpert 2006, 2008). However, while these above examples and many applica-tions show that the CA rankings reveal functional patterns, one may still wonder why this works. This question might especially arise given that the most widely-used though not prescribed statistical collostructional measure is in fact a sig-nificance test, a p-value. Apart from the two mathematical motivations for this p-value approach mentioned in the previous section, there is also a more concep-tual reason, too.

As all p-values, such (logged) p-values are determined by both effect and sample size or, in other words, the p-value weighs the effect on the basis of the observed frequencies such that a particular attraction (or repulsion, for that mat-ter) is considered more noteworthy if it is observed for a greater number of occur-rences of the [word] in the [constructional] slot (Stefanowitsch & Gries 2003: 239, n. 6). For instance, all other things being equal, a percentage of occurrence o of a word w in c (e.g., 40%) is upgraded in importance if it is based on more tokens (e.g., 14/35) than on less (e.g.,

8/20). This cannot be emphasized enough, given that proponents of CA have been (wrongly) accused of downplaying the role of ob-served frequencies. CA has in fact been used most often with FYE, which actually tries to afford an important role to observed frequencies: it integrates two pieces of important information: (i) how often does something happen ws frequency of occurrence in c, which proponents of observed frequencies rely on but also (ii) how exclusive is ws occurrence to c and cs to w. Now why would it be useful to combine these two pieces of information? For instance,

(i) because frequency plays an important role for the degree to which con-structions are entrenched and the likelihood of the production of lexemes in individual constructions (cf. Goldberg 1999)

(Stefanowitsch & Gries 2003: 239, n. 6, my emphasis); (ii) because we know how important frequency is for learning in general (cf., e.g., Ellis 2007); (iii) because collostructional analysis goes beyond raw frequencies of occur-

rence, [] determining what in psychological research has become known as

22 Stefan Th. Gries

one of the strongest determinants of prototype formation, namely cue validity, in this case, of a particular collexeme for a particular construction

(cf. Stefanowitsch & Gries 2003: 237, my emphasis).

In spite of these promising characteristics, Bybee (2010) criticizes CA with respect to each of the three different perspectives outlined above: the goals, the mathematical side, and the results/interpretation of CA. In her claims, Bybee also touches upon the more general point of frequencies vs. AMs as used in many cor-pus- and psycholinguistic studies. In this chapter, I will refute the points of critique by Bybee and discuss a variety of related points of more general importance to cognitive/usage-based linguists.

3. Bybees points of critique


The most frequent, but by no means only, implementation of CA uses pFYE as an AM, which (i) downgrades the influence of words that are frequent everywhere and (ii) weighs more highly observed relative frequencies of co-occurrence that are based on high absolute frequencies of co-occurrence. Bybee (2010: 97) criti-cizes this by stating that the problem with this line of reasoning is that lexemes do not occur in corpora by pure chance and that it is entirely possible that the factors that make a lexeme high frequency in a corpus are precisely the factors that make it a central and defining member of the category of lexemes that occurs in a slot in a construction. Using the Spanish adjective solo alone as an example, she goes on to say that, for solo, Collostructional Analysis may give the wrong results [my emphasis, STG], because a high overall frequency will give the word solo a lower degree of attraction to the construction according to this formula (2010: 98).


Bybee (2010: 98) also takes issue with the of the bottom right cell in the 22 ta-bles: Unfortunately, there is some uncertainty about the fourth factor mentioned above the number of constructions in the corpus. There is no known way to count the number of constructions in a corpus because a given clause may instan-tiate multiple constructions. Later in the text, however, she mentions that Bybee & Eddington tried different corpus sizes and obtained similar results (Bybee 2010: 98).



3.3.1 The perceived lack of semanticsBybee criticizes CA for its lack of consideration of semantics. Specifically, she summarizes Bybee & Eddington (2006), who took the most frequent adjectives occurring with each of four become verbs as the centres of categories, with se-mantically related adjectives surrounding these central adjectives depending on their semantic similarity, as discussed above (Bybee 2010: 98); this refers to Bybee & Eddingtons (2006) classification of adjectives occurring with, say, quedarse, as semantically related. She then summarizes [t]hus, our analysis uses both frequen-cy and semantics whereas [p]roponents of Collostructional Analysis hope to ar-rive at a semantic analysis but do not include any semantic factors in their method. Since no semantic considerations go into the analysis, it seems plausible that no semantic analysis can emerge from it (Bybee 2010: 98).

3.3.2 The perceived lacks of semantics and discriminatory powerThe above claim is also related to the issue of discriminatory/predictive power. In an attempt to compare Bybees raw frequency approach to CA, Bybee com-pares both approaches discriminability with acceptability judgment data. For two Spanish verbs meaning become (ponerse and quedarse) and twelve adjectives from three semantic groups (high freq. in c with these two verbs, low freq. in c but semantically related to the high freq. ones, and low freq. in c and semantically unrelated to the high freq. ones), the co-occurrence frequencies of the verbs and the adjectives, the frequency of the adjectives in the corpus, and the collostruction strengths were determined.

As Bybee mentions, frequency and collostruction strength make the same (correct) predictions regarding acceptability judgments for the high-frequency co-occurrences. However, semantically related low-frequency adjectives garner high acceptability judgments whereas semantically unrelated low-frequency ad-jectives do not. Bybee does not report any statistical analysis, but eyeballing the data seems to confirm this; she states [o]f course, the Collostructional Analysis cannot make the distinction between semantically related and semantically un-related since it works only with numbers and not with meaning (2010: 100). She goes on to say [t]hus for determining what lexemes are the best fit or the most central to a construction, a simple frequency analysis with semantic similarity produces the best results.

Finally, Bybee criticizes CA in terms of how many such analyses handle low-frequency collexemes, which are ignored (2010: 101). This is considered a prob-lem because low-frequency lexemes often show the productive expansion of the category and [w]ithout knowing what the range of low frequency, semantically

24 Stefan Th. Gries

related lexemes is, one cannot define the semantic category of lexemes that can be used in a construction (p. 101).

3.3.3 The absence of cognitive mechanisms underlying CAFrom the above claims regarding the relation between frequency, collostruction strength, (semantic similarity), and acceptability judgments, Bybee infers, in agreement with Goldbergs earlier research, that high-frequency lexical items in constructional slots are central to the meaning of a construction. However, she also goes on to claim that

Gries and colleagues argue for their statistical method but do not propose a cog-nitive mechanism that corresponds to their analysis. By what cognitive mech-anism does a language user devalue a lexeme in a construction if it is of high frequency generally? This is the question Collostructional Analysis must address. (2010: 100f.)

4. Clarifications, repudiations, and responses

This section addresses Bybees points of critique and other issues. I will show that Bybees understanding, representation, and discussion of CA does not do the method justice, but the discussion will also bring together a few crucial notions, perspectives, and findings that are relevant to cognitive/usage-based linguists, ir-respective of whether they work with CA or not.


There are three main arguments against this part of Bybees critique. The first is very plain: As cited above, Stefanowitsch & Gries (2003: 217) explicitly state that any AM can be used, one based on a significance test (pFYE, chi-square, t, ), one based on some other comparison of observed and expected frequencies (MI, MI2, ), an effect size (Cramers V/, log odds, ), or some other measure (MinSem, P, ). For example, Gries (2011, available online since 2006) uses the odds ratio to compare data from differently large corpus parts. Any criticism of CA on these grounds misses its target.

A second, more general counterargument is that the whole point of AMs is to separate the wheat (frequent co-occurrence probably reflecting linguistically relevant functional patterns) from the chaff (co-occurrence at chance level reveal-ing little to nothing functionally interesting). Consider an example on the level of lexical co-occurrence: Whoever insisted on using raw frequencies in contexts alone would have to emphasize that most nouns co-occur with the very frequently


and that whatever makes the occur in corpora is precisely the factor that makes it frequent around nouns. I do not find this particularly illuminating. As a more pertinent example, Bybees logic would force us to say that the as-predicative, exemplified in (4) and discussed by Gries, Hampe & Schnefeld (2005), is most importantly characterized not by regard (the verb with the highest collostruction strength), but by see and describe, which occur more often in the as-predicative than regard (and maybe by know, which occurs nearly as often in the as-predica-tive as regard). Given the semantics of the as-predicative and the constructional promiscuity and semantic flexibility of especially see and know, this is an unintui-tive result; cf. also below.

(4) a. V NPDirect Object as complement constituent b. I never saw myself as a costume designer c. Politicians regard themselves as being closer to actors

It is worth pointing out that the argument against testing against the null hypothesis of chance co-occurrence is somewhat moot anyway. No researcher I know believes words occur in corpora randomly just as no researcher analyzing experimental data believes subjects responses are random of course they dont and arent: if they did, what would be the point of any statistical analysis, with AMs or frequencies? With all due recognition of the criticisms of the null hypoth-esis significance testing paradigm, this framework has been, and will be for the foreseeable future, the predominant way of studying quantitative data this does not mean the null hypothesis of chance distribution is always a serious contender. Plus, even if null hypothesis testing were abandoned, this would still not constitute an argument against AMs because there are AMs not based on null hypothesis frequencies and the most promising of these, P, is in fact extremely strongly cor-related with pFYE. Lastly, regardless of which AM is used to downgrade words that are frequent everywhere, all of them recognize it is useful to consider not just the raw observed frequency of word w in context c but also the wider range of ws uses. That is, users of AMs do not argue that the observed frequency of w in c is unimportant they argue that it is important, as is ws behavior elsewhere. It is surprising that this position could even be criticized from a(n) usage-/exemplar-based perspective, something to which I will return below.

The final counterargument is even more straightforward: Recall that CA in-volves a normalization of frequencies against corpus size (for CA) or constructional frequencies (for DCA). But sometimes one has to compare 2+ constructions, as in Gries & Wulff (2009), who study to/ing-complementation (e.g., he began to smoke vs. he began smoking). They find that consider occurs 15 times in both construc-tions. Does that mean that consider is equally important to both? Of course not: the to-construction is six times as frequent as the ing-construction, which makes

26 Stefan Th. Gries

it important that consider managed to squeeze itself into the far less frequent ing-construction as often as into the far more frequent to-construction. An account based on frequencies alone could miss that obvious fact CA or other approaches perspectivizing the observed frequencies of w in c against those of w and/or c do not.


Let us now turn to some of the more technical arguments regarding CAs input data and choice of measure.

4.2.1 The issue of the corpus sizeLet us begin with the issue of Bybees fourth factor, the corpus size in construc-tions. Yes, an exact number of constructions for a corpus cannot easily be gener-ated because

i. a given clause may instantiate multiple constructions (Bybee 2010: 98);ii. researchers will disagree on the number of constructions a given clause in-

stantiates;iii. in a framework that does away with a separation of syntax and lexis, research-

ers will even disagree on the number of constructions a given word instantiates.

However, this is much less of a problem than it seems. First, this is a problem nearly all AMs have faced and addressed successfully. The obvious remedy is to choose a level of granularity close to the one of the studied phenomenon. For the last 30 years collocational statistics used the number of lexical items in the corpus as n, and collostructional studies on argument structure constructions used the number of verbs. Many CA studies, none of which are cited by Bybee or other crit-ics, have shown that this yields meaningful results with much predictive power (cf. also Section 4.2.2 below).

Second, CA rankings are remarkably robust. Bybee herself pointed out that different corpus sizes yield similar results, and a more systematic test supports that. I took Stefanowitsch & Griess (2003) original results for the ditransitive con-struction and increased the corpus size from the number used in the paper by a factor of ten (138,664 to 1,386,640), and I decreased the observed frequencies used in the paper by a factor of 0.5 (with ns = 1 being set to 0 / omitted). Then I computed four CAs:

one with the original data; one with the original verb frequencies but the larger corpus size; one with the halved verb frequencies and the original corpus size; one in which both frequencies were changed.


In Figure 1, the pairwise correlations of the collostruction strengths of the verbs are computed (Spearmans rho) and plotted. The question of which verb frequencies and corpus size to use turns out to be fairly immaterial: Even when the corpus size is de-/increased by one order of magnitude and/or the observed frequencies of the words in the constructional slots are halved/doubled, the overall rankings of the words are robustly intercorrelated (all rho > 0.87). Thus, this issue is unproblematic when the corpus size is approximated at some appropriate level of granularity and, trivially, consistently, in one analysis.

rho = 0.87

corpus=138664obs. n=100%

corpus=1386640obs. n=100%

corpus=138664obs. n=

50%

corpus=1386640obs. n=

50%

Logg

ed c

oll.

str.

Logg

ed c

oll.

str.

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5

1.5

0.5

1.5

0.5 1.0 2.5

rho = 0.87

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.89

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.99

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.91

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.89

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.99

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.99

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.91

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

rho = 0.91

Logg

ed c

oll.

str.

Logged coll. str.

0.5

1.5

0.5 1.0 2.5

Logged coll. str.0.5 1.0 2.5

Logged coll. str.0.5 1.0 2.5

rho = 0.99 rho = 0.91

Figure 1. Pairwise comparisons between (logged) collostruction values, juxtaposing cor-pus sizes (138,664 and 1,386,640) and observed frequencies (actually observed ones and values half that size, with ns = 1 being omitted)

28 Stefan Th. Gries

4.2.2 The distribution of pFYEAnother aspect of how CA is computed concerns its response to observed fre-quencies of word w in construction c and ws overall frequency. Relying on fre-quencies embodies the assumption that effects are linear: If something is observed twice as often as something else (in raw numbers or percent), it is, unless another transformation is applied, two times as important/entrenched/ However, many effects in learning, memory, and cognition are not linear:

the power law of learning (cf. Anderson 1982, cited by Bybee herself); word frequency effects are logarithmic (cf. Tryk 1986); forgetting curves are logarithmic (as in priming effects; cf. Gries 2005,

Szmrecsanyi 2006),

Given such and other cases and Bybees emphasis on domain-general pro-cesses (which I agree with), it seems odd to rely on frequencies, which have math-ematical characteristics that differ from those of many general cognitive processes. It is therefore useful to briefly discuss how frequencies, collostruction strengths, and other measures are related to each other, by exploring systematically-varied artificial data and authentic data from different previous studies.

As for the former, it is easy to show that the AM used in most CAs, pFYE, is not a straightforward linear function of the observed frequencies of words in con-structions but rather varies as a function of ws frequency in c as well as ws and cs overall frequencies, as Figure 2 partially shows for systematically varied data. The

200

300

400

500600700800900

100

attraction

repulsion

0 50 100 150 200 250Frequency of verb in construction

log

10 o

f pFY

E

250

200

150

100

50

0

Figure 2. The interaction between the frequency of w, the overall frequencies of w and c, and their collostruction strengths


frequency of w in c is on the x-axis, different overall frequencies of w are shown in differently grey-shaded points/lines and with numbers, and -log10 pFYE is shown on the y-axis.

I am not claiming that logged pFYE-values are the best way to model cogni-tive processes for example, a square root transformation makes the values level off more like a learning curve but clearly a type of visual curvature we know from many other cognitive processes is obtained. Also, pFYE values are highly cor-related with statistics we know are relevant in cognitive contexts and that may, therefore, serve as a standard of comparison. Ellis (2007) and Ellis & Ferreira-Junior (2009: 198 and passim) discuss a uni-directional AM called P, which has been used successfully in the associative-learning literature. Interestingly for the data represented in Figure 2, the correlation of pFYE with Pword-to-construction is ex-tremely significant (p < 1015) and very high (rho = 0.92) whereas the correlations of the observed frequencies or their logs with Pword-to-construction are significant (p < 108) but much smaller (rho = 0.65). Again, pFYE is not necessarily the optimal solution, but it exhibits appealing theoretical characteristics ([transformable] cur-vature, high correlations with measures from learning literature, responsiveness to frequency) that makes one wonder how Bybee can just dismiss them.

Let us now also at least briefly look at authentic data, some here and some fur-ther below (in Section 4.3.2). The first result is based on an admittedly small com-parison of three different measures of collostruction strengths: For the ditransitive construction, I computed three different CAs, one based on -log10 pFYE, one on an effect size (logged odds ratio), and one on Mutual Information (MI). Consider the three panels in Figure 3 for the results, where the logged frequencies of the verbs in the ditransitive are on the x-axes, the three AMs are on the y-axes, and the verbs are plotted at the x/y-values reflecting their frequencies and AM values. The corre-lation between the frequencies and AMs is represented by a polynomial smoother and on the right, I separately list the top 11 collexemes of each measure.

Comparing these results to each other and to Goldbergs (1995) analysis of the ditransitive suggests that, of these measures, pFYE performs best: Starting on the right, MIs results are suboptimal because the prototypical ditransitive verb, give, is not ranked highest (let alone by a distinct margin) but only third, and other verbs in the top five are, while compatible with the ditransitives semantics, rather infrequent and certainly not ones that come to mind first when thinking of the ditransitive. The log odds ratio fares a bit better because give is the strongest col-lexeme, but otherwise the problems are similar to MIs ones.

The pFYE-values arguably fare best: give is ranked highest, and by a fittingly huge margin. The next few verbs are intuitively excellent fits for the polysemous ditran-sitive and match all the senses Goldberg posited: the metaphor of communication as transfer (tell), caused reception (send), satisfaction conditions implying transfer

30 Stefan Th. Gries

(offer), the metaphor of perceiving as receiving (show), etc.; cf. Stefanowitsch & Gries (2003: 228f.) for more discussion. Note also that pFYE also exhibits a behavior that should please those arguing in favor of raw observed frequencies: As the poly-nomial smoother shows, it is pFYE that is most directly correlated with frequency. At the same time, and this is only a prima facie piece of evidence, it is also the pFYE-values whose values result in a curve that has the Zipfian shape that one would expect for such data (given Ellis & Ferreira-Juniors (2009) work (cf. also below).

Finally, there is Wiechmanns (2008) comprehensive study of how well more than 20 AMs predict experimental results regarding lexico-constructional co-oc-currence. Raw co-occurrence frequency scores rather well but this was in part be-cause several outliers were removed. Crucially, pFYE ended up in second place and the first-ranked measure, Minimum Sensitivity (MS), is theoretically problematic. Using the notation of Table 1, it is computed as shown in (5), i.e. as the minimum of two conditional probabilities:

(5) MS =min( nA&B , nA&B) = min(p(word |construction), p(construction|word))nA nB One problem here is that some collexemes positions in the ranking order will be due to p(word|construction) while others will be due to p(construction|word). Also, the value for give in Table 2 is 0.397, but that does not reveal which condi-tional probability that value is p(word|construction) or p(construction|word). In fact, this can lead to cases where two words get the same MS-value, but in one

1.5

1.0

0.5

0.0

log10 of pFYE against logverb freq in cx+1

logverb freq in cx+1 logverb freq in cx+1 logverb freq in cx+1

log

10 o

f pFY

E

log odds against logverb freq in cx+1 MI against logverb freq in cx+1

3002.0

6

4

2

0

20.5

250

200

150

100

50

0

1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6

log

odds

MI

Figure 3. Output scores for the ditransitive of three different AMs (left: pFYE, middle: log odds ratio, right: MI)


case it is p(word|construction) and in the other it is p(construction|word). This is clearly undesirable, which is why pFYE, while only second, is more appealing. As an alternative, a uni-directional measure such as P is more useful (cf. Gries to appear).


4.3.1 The perceived lacks of semanticsI find it hard to make sense of Bybees first objection to CA, the alleged lack of consideration of semantics discussed in Section 3.3: (i) her claim appears to con-tradict the exemplar-model perspective that permeates both her whole book and much of my own work; (ii) it does not engage fully with the literature; (iii) it is based on a partial representation of CA, and so it is really arguing against a straw man.

As for (i), Bybees statement that [s]ince no semantic considerations go into the analysis, it seems plausible that no semantic analysis can emerge from it is false. There is a whole body of work in, e.g., computational (psycho)linguistics where purely frequency-based distributional analyses reveal functionally inter-pretable clusters. Two classics are Redington, Chater & Finch (1998) and Mintz, Newport & Bever (2002). Both discuss how multidimensional distributional anal-yses of co-occurrence frequencies reveal clusters that resemble something that, in cognitive linguistics, is considered to have semantic import, namely parts of speech. And even if one did not postulate a relation between parts of speech and semantics, both reveal that something can emerge from a statistical analysis (parts of speech) that did not enter into the analysis. Even more paradoxically, it is a strength of exactly the type of usage-/exemplar-based models that Bybee and I both favor that they can explain such processes as the emergence of categories of any kind from processing and representing vast numbers of usage events in mul-tidimensional memory space.

As for (ii), it is even less clear how anyone can imply having read CA studies but claim that collostructional results do not reveal semantic patterns. For exam-ple, there are the (discussions of the) lists of collexemes presented in Stefanowitsch & Gries (2003) recall the ditransitive and the dative alternation from Section 2.3 above plus there are many other studies aside from Stefanowitsch & Gries (2003) and Gries & Stefanowitsch (2004) cf. Sections 4.2.2 and 4.3.2 for many examples nearly all of which have discussed at length functional patterns in the top-ranked collexemes. This lack of engagement with the literature extends even to the CA work speaking most directly to this question: Gries & Stefanowitsch (2010), first presented in 2004 and available online since 2006, clustered the first

32 Stefan Th. Gries

verbs in the into-causative (cf. (6)) based on the ing-verbs,3 and the verbs in the way-construction (cf. (7)) based on the prepositions.

(6) a. V

(Benjamins Current Topics) Nikolas Gisborne, Willem B. Hollmann-Theory and Data in Cognitive...

Documents

Transcript of (Benjamins Current Topics) Nikolas Gisborne, Willem B. Hollmann-Theory and Data in Cognitive...