Gustafson Capková, and my statistics guru Thomas Hörberg. ... social media has turned out to be an excellent research tool, since posting a question about ...
Triangulating Perspectives on Lexical Replacement
From Predictive Statistical Models to Descriptive Color Linguistics Susanne Vejdemo Academic dissertation for the Degree of Doctor of Philosophy in Linguistics at Stockholm University to be publicly defended on Friday 3 March 2017 at 13.00 in hörsal 4, hus B, Universitetsvägen 10 B. Abstract
The aim of this thesis is to investigate lexical replacement processes from several complementary perspectives. It does so through three studies, each with a different scope and time depth. The first study (chapter 3) takes a high time depth perspective and investigates factors that affect the rate (likelihood) of lexical replacement in the core vocabulary of 98 Indo-European language varieties through a multiple linear regression model. The chapter shows that the following factors predict part of the rate of lexical replacement for non-grammatical concepts: frequency, the number of synonyms and senses, and how imageable the concept is in the mind. What looks like a straightforward lexical replacement at a high time depth perspective is better understood as several intertwined gradual processes of lexical change at lower time depths. The second study (chapter 5) narrows the focus to seven closely-related Germanic language varieties (English, German, Bernese, Danish, Swedish, Norwegian, and Icelandic) and a single semantic domain, namely color. The chapter charts several lexical replacement and change processes in the pink and purple area of color space through experiments with 146 speakers. The third study (chapter 6) narrows the focus even more, to two generations of speakers of a single language, Swedish. It combines experimental data on how the two age groups partition and label the color space in general, and pink and purple in particular, with more detailed data on lexical replacement and change from interviews, color descriptions in historical and contemporary dictionaries, as well as botanical lexicons, and historical fiction corpora. This thesis makes a descriptive, methodological and theoretical contribution to the study of lexical replacement. Taken together, the different perspectives highlight the usefulness of method triangulation in approaching the complex phenomenon of lexical replacement.
Keywords: semantics, lexical typology, semantic typology, historical linguistics, historical semantics, lexical replacement, lexical change, rate of lexical replacement, color, regression models, Swedish, English, German, Danish, Norwegian, Icelandic, method triangulation. Stockholm 2017 http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-137874 ISBN 978-91-7649-644-2 ISBN 978-91-7649-645-9
Department of Linguistics Stockholm University, 106 91 Stockholm
Triangulating Perspectives on Lexical Replacement From Predictive Statistical Models to Descriptive Color Linguistics
Susanne Vejdemo
Table of Contents Acknowledgements
ix
1
1
Introduction
1.1
Research questions and perspectives
2
1.2
Studies and thesis structure
4
1.3
Style conventions
5
Background
2
7
2.1
Words and concepts
8
2.2
Lexical replacement and lexical change
11
2.3
Lexical replacement and primary words
12
2.4
Where do new primary words come from?
13
2.5
Is there regularity in lexical change?
15
2.6
Lexical change is not uniform
17
2.7
Some semantic and pragmatic factors in lexical change
19
2.7.1
Emotional charge
19
2.7.2
Imageability
21
2.7.3
Frequency and entrenchment
21
2.7.4
Subjectification, inferences, polysemy, synonymy
23
2.7.5
Speaker age effects
28
Macro-perspective: A model of some semantic and pragmatic causes of lexical replacement
3
3.1
Background and method
30 32
3.1.1
Measuring lexical replacement: basic assumptions
32
3.1.2
Lexical replacement and Swadesh lists
34
3.1.3
Earlier models of lexical replacement
36
3.1.4
Evaluation of earlier models
39
3.2
A new model
3.2.1
Variables in the model
43 43
3.2.2
Word class (Semantic Categories)
45
3.2.3
Imageability
45
3.2.4
Entrenchment (as frequency and co-occurrence)
46
3.2.5
Age of acquisition
47
3.2.6
Emotional charge / Arousal
47
3.2.7
Senses
48
3.2.8
Synonyms
48
3.3
Results and discussion
49
3.4
Summary
55
3.5
Rate for particular semantic domains
57
3.6
Chapter end notes and bridge to the next chapter
61
4
Introduction to color studies
63
4.1
Terms amd definitions
65
4.2
Background on color linguistics
66
4.2.1
The Berlin and Kay paradigm
66
4.2.2
New color concepts appear in border regions
71
4.2.3
Color concepts and perspective shifts
74
4.2.4
Labels for color concepts gradually become simpler
75
4.2.5
Intra-language variation in color labeling
77
4.2.6
Intermittent summary
79
The EoSS Experiment Protocol
81
4.3
5
Meso-perspective: Cross-linguistic lexical change in pink and purple
84
5.1
Languages and speakers
86
5.2
General results
88
5.3
The PINK1 and PINK2 concepts
90
5.4
System A: a single PINK1 concept
91
5.5
System B: the PINK1 concept
93
5.6
System B: the PINK2 concept
98
5.7
The PURPLE1 concept
102
5.8
Rare responses
108
5.9
Discussion
109
6 6.1
Micro-perspective: diachronic lexical change in pink and purple
112
Words for pink and purple in historical texts
115
6.1.1
Textual Material
115
6.1.2
Results
117
6.2
Meta-awareness of change: interviews with older speakers
131
6.2.1
Method and material
131
6.2.2
Results
132
6.3
Summary of textual and interview results
140
6.4
Capturing intergenerational differences through color elicitation
143
6.4.1
Supplementary notes on methodology
143
6.4.2
Results
145
6.4.3
Differences over the entire spectrum
146
6.4.4
Differences within the PINK1, PINK2, and PURPLE1 areas
158
6.5
Discussion
6.5.1
7
169
Are derived colors in general, and purple and pink in particular, special?
169
6.5.2
Lexical change processes in pink and purple
171
6.5.3
Reconnecting with some previous theories
173
General conclusions
175
Appendix A: Factors influencing the rate of replacement.
189
Appendix B: Naming task results
196
Appendix C: Best example task results
201
Appendix D: EoSS codes, Munsell codes, Hex codes
205
Appendix E: The effect of color blindness
206
Appendix F: Swedish summary / Svensk sammanfattning
207
References
216
ACKNOWLEDGEMENTS Just as it takes a village to raise a child, it takes a community to create a dissertation. This thesis would not have been possible without the generous support of my supervisors and academic role models, Maria Koptjevskaja Tamm and Bernhard Wälchli. You have taught me so much, and I will be forever grateful for all the help, insights, arguments, and laughter. You have been the anchoring string to my plunging / flying / soaring kite, and I have always felt secure in your support in matters both professional and personal. The heart of my community is the Department of Linguistics at Stockholm University. It’s where I grew up academically, and where I have always returned after academic adventures around the world. I am very grateful to my academic family there and the great learning and research environment that they have created. It is a privilege to know that you can knock on any door and always be greeted with an enthusiastic “Sure, I’d love to read three pages on color theory by tomorrow, that sounds just fascinating!” I wish to thank Professor Östen Dahl, my “mock-defense opponent,” who has been my employer in several research projects over the years, and who is also the person who introduced me to linguistics in the first place, back when I was still a high school student. There are so many colleagues at the Department who have helped me in learning the trade of linguistic research – in seminars, in lunch room discussions, in detailed and insightful comments on drafts – but I would especially like to mention Ljuba Veselinova, Emil Perder, Eva Lindström, Kristina Nilsson Björkenstam, Sofia Gustafson Capková, and my statistics guru Thomas Hörberg. In the wider community of Stockholm University, I am very grateful for the support of the steering committee of FoSprak, the Special Doctoral Programme in Language and Linguistics. I’ve been fortunate enough to work and learn alongside other PhD students both in and outside the programme. In particular I would like to mention Sigi Vandewinkel (a treasured coauthor), Guillermo Montero Melis, and of, course, my wonderful roommates Ghazaleh Vafaeian and Pernilla Hallonsten Halling: thanks for all your comments, in tutorials, over tea, and in late night discussions in the saunas of Bommersvik. Widening the circle yet again, I wish to thank the PIs and other members of the Evolution of Semantic Systems consortium (Max Planck Institute for Psycholinguistics, Nijmegen). In particular, I am thankful to Michael Dunn for lots of interesting insights, for playing host for my visit to the institute, and for giving me comments on early drafts of the paper (coix
written with Thomas Hörberg) that forms the basis of chapter three in this thesis. Through the consortium I met my co-authors for the paper that forms the basis of the fifth chapter of this thesis: Þórhalla Guðmundsdóttir Beck, Cornelia von Scherpenberg, Åshilde Næss, Martina Zimmerman, Linnea Stockall and Matthew Whelpton. I am especially happy that the project brought me into contact with Carsten Levisen. I would also like to thank the organizers and participants at the The Colour Language and Colour Categorisation Conference in Tallinn, 2013. There, and at various other conferences, I have met people who have since been kind enough to correspond with me about lexical semantics, such as Mari Uusküla, Magalie Desgrippes, Elena Parina, and Misuzu Shimotori. I have also received grants to support my travels from Gålöstiftelsen, FoSpråk, and Stockholm University. I am also fortunate to be surrounded by a wealth of non-linguists who have aided the growth of this thesis through their various skills and talents – social media has turned out to be an excellent research tool, since posting a question about statistics, programming, or evaluation of semantic content has often led to dozens of valuable replies. This great set of people includes, among many others, the ever-helpful Gustaf Rydevik, Jon Karlfeldt, Stefan Björk, and Annika Waern. I also wish to thank all the participants in my experiments, the reviewers and editors who helped with the journal papers, and Lamont Antieau, my proof-reader. I would never have made it this far without my family, who has always supported me wholeheartedly – in particular, of course, my wonderful parents, Kerstin and Stefan, the bedrock of my existence. Finally, there is my best friend, statistician, programmer, cook, driver, proof-reader, chocolate procurer, cheerleader, designer of the front-page image of this thesis, co-worker, and sometime co-author: my husband Mikael Vejdemo-Johansson. Wherever I may wander, you will always be my home. Thank you.
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1 INTRODUCTION Since ‘tis natures law to Change, Constancy alone is strange. -John Wilmot Languages change. It is an essential part of their very nature. The systematic scientific inquiry into how and why these changes occur is a common research topic in linguistics, and great advances have been made in uncovering the rules and tendencies of phonological and grammatical changes. It has proven more difficult to find systematic rules for changes in the lexicon, and this thesis contributes to that ongoing discussion. The aim of this thesis is to investigate lexical replacement processes from several complementary perspectives. A typical example of lexical replacement is the change of the most common word for ‘girl’ in English from maiden (Old and Middle English) to girl (Modern English). In modern speech, maiden can no longer be used as a neutral expression to refer to any young female – the word has become replaced for this particular meaning. Assuming that the meaning ‘girl’ does not vary, prototypical lexical replacement is the fact and the process of this meaning being denoted first by one word (i.e. maiden) and then by another (i.e. girl). The process maiden Æ girl seems, on the surface, to be a straightforward kind of lexical replacement. However, to a large extent this seeming simplicity is an illusion born from the lengthy (broad) time perspective: from a time scale of several centuries, we can conclude that the replacement has taken place, without knowing how or why, or what effects the replacement has had on other parts of the vocabulary. The color domain yields good examples of complex kinds of lexical replacement. Field bindweed (Convolvulus Arvensis L.) is a flower that is sometimes white and sometimes pink, and this fact has consistently been reported in floras (botanical encyclopedias) during the last few centuries – but over time, the color terms have changed. In 19th century Swedish floras, the term ljust röd ‘light red’ was typically used. In the beginning of the 20th century, however, floras referred to the same flower as skär ‘pink’. And by the beginning of the 21st century, the flower was being described as rosa ‘pink’. The ljust röd Æ skär Æ rosa example is a slightly more complicated example of lexical replacement than maiden Æ girl, at least on the surface. From a broader time perspective, it is clear that the same referent – the color 1
of a particular flower – is connected to a lexical replacement ljust röd Æ skär Æ rosa. Several concrete questions immediately arise from this example, however: Rosa and skär co-existed historically in Swedish, and still do. At what point in time could a lexical replacement be said to have occurred? How does a lexical replacement process interact with other kinds of change? For instance, the term röd ‘red’ and its modified form ljust röd ‘light red’ still exist in modern Swedish. That means that the lexical replacement described above is connected with a semantic change: the area of the perceptual color space that röd denotes has changed, since it is now not the most natural way for speakers to describe the color of the field bindweed. Similarly, skär is still used (though rarely) in modern Swedish, but usually only for the lightest shades of pink. How quickly do lexical replacement processes occur? During the same time period in which the word describing the color of field bindweed has been replaced two times in Swedish, the word for the typical color of grass has stayed the same. How uniform is lexical replacement? Is the process of change from ljust röd till skär the same as that from skär to rosa? All these questions belong to the lexical typological research tradition in linguistics – defined as “the “characteristic ways in which language […] packages semantic material into words” by Lehrer (1992, p. 249) and “the cross-linguistic and typological dimension of lexicology” by KoptjevskajaTamm (2008, p. 5), or more concretely the “systematic study of crosslinguistic variation in words and vocabularies” (Koptjevskaja-Tamm, 2016, p. 4). Lexical typological research can have both more local approaches (restricted to a particular lexical field, to a particular process, or to a particular polysemy pattern) and more general approaches (with the aim of uncovering patterns that are relevant for the structuring of the entire lexicon) (Koptjevskaja-Tamm, 2008, p. 6).
1.1 RESEARCH QUESTIONS AND PERSPECTIVES In this thesis, I will argue that it is both possible and worthwhile to seek generalizations for lexical replacement, just as linguists seek generalizations for phonetic and grammatical change. The example concerning Swedish words for ‘pink’ makes it clear that it is difficult, at least at narrower time scales, to separate lexical replacement from other processes,
2
such as semantic change. This thesis will work to answer three research questions, stated here, together with related sub-questions. A. What affects the likelihood of lexical replacement? A1. Is it possible to formulate global, domain independent generalizations? A2. How can local, domain-dependent generalizations be found? B. How does lexical replacement proceed in the semantic domain of color? B1. How does lexical replacement interact with other kinds of lexical change? B2. How does knowledge about the semantics and pragmatics of color (psychophysiology, sociohistory) help elucidate lexical replacement in this domain? C. How do different perspectives on lexical replacement relate to and complement each other? I contend that generalizations for lexical replacement are most successful when they are framed within several complementary perspectives. Some of the most important perspectives are x
x
x
Time scale: what might be a useful generalization from the perspective of many centuries might not be as useful in understanding processes of change in the time frame of a few generations. Semantic domain scope: Some generalizations will be domainindependent, and some will be different depending on the semantic domain. An onomasiological or a semasiological viewpoint.1
I mainly focus on denotative meaning (which part of reality is indicated by a word), for context-less words and the concepts they are connected to.
Briefly: Onomasiological, starting the analysis from a concept; semasiological, starting the analysis from lexical items. The terms will be discussed more in section 2.2.
1
3
1.2 STUDIES AND THESIS STRUCTURE This thesis employs three different time perspectives from which to study lexical replacement – the three studies will cover, respectively, macrotime (the age of Indo-European: several millennia), meso-time (several centuries), and micro-time (a few generations). The first chapter will not be restricted to any particular semantic domain, while the latter two will focus on color. Throughout, the thesis will alternate between a semasiological and an onomasiological perspective. I argue that triangulation of these perspectives can be a fruitful way for approaching this complex issue, and that each perspective gives complementary insights into why, how, and how fast lexical replacement proceeds. Overall, the thesis has seven chapters. Chapter 2 is a general background chapter and is followed by the chapters for the three studies. The three studies of the thesis are summarized in Table 1. The broader the time scale, the greater the amount of data from more languages that can be used, but the analysis will be shallower, lacking the rich detail of individual word histories. The narrower the time scale, the more detailed the information on the process of lexical replacement, but generalizations are also hampered by the small amount of material and the way changes in one word affect other words. Chapter 3 houses the first study, which concerns domain-overriding generalizations of lexical replacement (research question A1). The chapter attempts to explain part of the likelihood (rate) of lexical replacement by building a statistical model using data from 87 Indo-European languages. Part of the material in this chapter has been previously published in Vejdemo and Hörberg (2016). The issue of domain-independent generalizations (research question A2) is discussed in the last section, as a bridge to the rest of the thesis. Chapters 4, 5, and 6 all concern domain-specific generalizations for lexical replacement (research question A2 and B) in the semantic domain of color. Chapter 4 is an introduction to the linguistics of color, and also presents some common methodology of chapters 5 and 6. Chapter 5 is a cross-linguistic synchronic study of the lexicalization strategies of the pink and purple parts of the perceptual color space in seven Germanic languages. From this, diachronic information on lexical replacement and other kinds of change can be inferred (research question B1). Knowledge of the sociohistory of color in the region will be combined with 4
elicitation experiment results (thereby addressing part of research question B2). Part of the material in this chapter has previously been published in Vejdemo, Levisen, Guðmundsdóttir Beck, von Scherpenberg, Næss, Zimmerman, Stockall, and Whelpton (2015). Chapter 6 is an intra-language study of lexical replacement processes concerning pink and purple in Swedish. The chapter combines dictionaries and encyclopedias from the last few centuries, corpus research into historical fiction novels, interviews with speakers and comparisons of elicitation experiment results from two generations of Swedish speakers to gain a fuller picture of lexical replacement (thereby addressing part of research question B1, B2). Chapter 7 contains a general discussion of the research questions and will combine the perspectives of the three studies, thereby specifically reconnecting with research question C.
1.3 STYLE CONVENTIONS When words are discussed, they will be written in italics (röd). Concepts will be written in small capitals (RED), while more loosely defined meanings (often tentative translations) will be written within single quotation marks (ljusröd ‘light red’). Cognate classes are written inside regular quotation marks (“rot”). The reader is reminded that all translations, especially when it comes to color terms, are tentative.
5
Table 1. Organization of the studies in the thesis: the macro study in chapter 3, the meso study in chapter 5, and the micro study in chapter 6
Time scale & scope Method & material
Domain
Chapter 3 Macro: several millennia, 87 language varieties A statistical model tests domainindependent hypotheses about lexical replacement (based on a database of cognate class judgments of a Swadesh list) Core vocabulary
Chapter 5 Meso: several centuries, seven Germanic languages Comparison of variation, using elicitation experiment results, supplemented with dictionary data
Color, with focus on pink and purple
6
Chapter 6 Micro: two generations, one language Comparison of variation and change, using elicitation experiment results, supplemented with interviews, dictionaries, floras, corpora Color, with focus on pink and purple
2 BACKGROUND The difficulty with formulating generalizations for changes in the lexicon stems at least partly from the sheer amount of material to be explained. Ever since the neo-grammarians’ startling revelation that sound change is regular and not random (see e.g. Paul, 1886), there has been a concentrated effort to find generalizations and rules in phonetic change – however, in contrast to the amount of words in the world’s languages, the number of phonemes is relatively small. Similarly, in the last century advances have also been made in finding generalizations and rules for grammaticalization (a term coined by Meillet, 1921) processes, which, simply put, relate to how semantically rich content words change and become semantically poorer function words, or the way in which the grammatical content of function words changes. But the number of function words and grammatical functions is also smaller than the number of content words and phenomena that can be named. The great majority of replacement and change in language is not connected to phonemes or function words, but to semantically rich content words that change into, or are replaced by, other content words. This makes it both important, and difficult, to find generalizations for this kind of change. This background chapter will first introduce some fundamental terminology and assumptions (section 2.1), and then go on to discuss the relationship between lexical replacement and other kinds of lexical change, as well as the semasiological and onomasiological perspectives that might be taken for such changes (2.2). In section 2.3, the term “primary (and secondary) word” is introduced, and section 2.4 turns to where new primary words come from. Section 2.5 argues that there is regularity in lexical change (and its subprocess, lexical replacement), and section 2.7 turns to different hypotheses on why and how such regularity might arise.
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2.1 WORDS AND CONCEPTS Any research into meaning change must take a stance on what meaning is, and there is a rich and terminologically confusing literature on the subject. The aim of this section is to introduce some fundamental distinctions and address the issue of categorical particularism: is it even possible to ever compare the meaning of two words in different languages? This thesis will mainly discuss words and the concepts that words designate. In order to gain a better understanding of the nature of concepts, some further ideas should be established. It could be suggested that Swedish hatt, English hat, and Spanish sombrero all denote the same cross-linguistic semantic category HAT, which somehow exists independently of all of these languages. This makes sense at face value, but is a gross simplification: there very seldom exists an exact, perfect semantic overlap between words like hatt and hat. Differences can often be found, either denotationally (the ranges of objects that the different words can be used for: hat can be used for hard top hats and soft hats in English; Swedish hatt can only be used for the former) or connotationally (the more general associations the words bring forth in the minds of the speaker: for me, even out of context Swedish hatt readily evokes the idea of formal or fancy wear, while English hat does not). The Swedish word hatt could be said to match a language-specific concept HATT, which carries information on possible subsenses, denotation, connotation, morphosyntactic use, etc. In contrast, the English word hat could be said to match a language-specific concept HAT. Haspelmath (2010) makes a distinction between language-particular descriptive categories (categories that are used to describe particular languages); cross-linguistic categories (that, if they exist, have some claim to universality or at least cross-linguistic applicability); and comparative concepts (that are linguist-specific, and are claimed to be useful in cross-linguistic comparison). Categorical particularism is the scholarly position claiming that it is not useful to talk about cross-linguistic categories, but only of language-particular descriptive categories: This, however, would seem to mean that languages become “incommensurable systems” and that comparison is not possible (Boas, 1911; Haspelmath, 2010, p. 681). In order to allow for comparison between languages, Haspelmath (2010, p. 663) suggests that crosslinguistic comparison should be based on comparative concepts created by the researcher, rather than on 8
crosslinguistic categories that are assumed to be instantiated in different languages. “Comparative concepts are concepts created by comparative linguists for the specific purpose of crosslinguistic comparison. Unlike descriptive categories, they are not part of particular language systems and are not needed by descriptive linguists or by speakers. They are not psychologically real, and they cannot be right or wrong. They can only be more or less well suited to the task of permitting crosslinguistic comparison” (Haspelmath, 2010, p. 665. See also 2016). Haspelmath (2010) uses these theoretical tools mainly to discuss morphosyntactic categories (like word classes), but they can also be applied to lexical semantics. This thesis will use the notion of comparative concepts in semantic research, and will deviate from the strict definitions that Haspelmath suggests are necessary for comparative concepts. Several scholars have noted that comparative concepts may be based on the observation of specific cross-linguistic data patterns, which makes them discoveries rather than inventions (Beck, 2016, p. 398; Dahl, 2016, p. 431; Moravcsik, 2016, p. 422). There is good reason to accept vaguely defined comparative concepts: “vague categories with a prototype core and fuzzy boundaries” as expressed by Lander and Arkadiev (2016, p. 411) (See also Dahl, 2016, p. 435; LaPolla, 2016, p. 367). For some comparative concepts, it might be possible to establish rather exact definitions (‘the adjustable tool used to clamp down on and tighten nuts and bolts with edges’), which makes it easy to identify language-specific words (English: adjustable wrench; Swedish; skiftnyckel) so that comparisons can be made. For many semantic comparisons, however, that level of definition is often impractical, if not impossible, and often the definition of the comparative concept remains vague. This does not mean that comparisons cannot be made. I would claim that one semantic example of comparative concepts already in use in linguistic literature is the shared concept alluded to in discussions about translation equivalents. Swedish hund and English dog are translation equivalents because they both match a very similar idea and because they are the most neutral translation that a bilingual speaker would give, if asked to translate one of the terms to the other language. The idea (DOG) that they both match is a comparative concept, even though it is often not defined outright. The discussion should then concern whether the level of care taken to identify the translation equivalents is good enough for whatever task the researcher wants to accomplish, not whether it is right or wrong that hund and dog both match 9
the same comparative concept (cf. the discussion of the pragmatic stance in cross-linguistic research in Koptjevskaja-Tamm, 2008, p. 10). When this thesis compares concepts between different speakers, different languages, or different generations of the same languages, it is, unless otherwise stated, this kind of comparative concept that is intended. Having briefly discussed how concepts and words will be used in this thesis, a few words should be said about referents. This thesis will mainly deal with denotations of words, by which is meant the extension in the real world that a word refers to: the denotation of dog is typically the set of all dogs; the denotation of red is typically the part of the perceptual color spectrum that red refers to. Occasionally, the connotation of a word will also be discussed, by which is meant the associated notions: dog might be associated with loyalty, or pets; red might be associated with danger, lipstick, or roses. I use the vaguer terms “to mean” and “a meaning” when it is not necessary for the discussion at hand to determine or define a concept – instead, “meaning” should be read as “semantic content” and “to mean” as “to have (a certain) semantic content”. While acknowledging that the exact meaning of sign emerges in each occasion of its use, this thesis will take the approach that the meaning of a word can and should also be studied at a more abstract level.
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2.2 LEXICAL REPLACEMENT AND LEXICAL CHANGE Koch (2016, p. 21ff.) writes that the connected linguistic processes of lexical replacement (which he calls change of designation) and semantic change are both instances of the more general process: lexical change. What makes a historical lexical process a case of lexical replacement or a case of semantic change has mainly to do with whether a semasiological or an onomasiological perspective is used. This section will define and exemplify all these terms. A prototypical case of lexical replacement was given in the introduction to this thesis: girl ‘young female person’ replacing maiden ‘young female person’. Parallel to girl replacing maiden, another lexical change (a semantic change) occurred when girl ‘young person’ came to mean girl ‘young female person’. The observation that girl ‘young person’ replaced maiden ‘young female person’ is made from an onomasiological perspective of a lexical change. This means that the analysis starts from a concept or meaning that is assumed not to change (e.g. ‘young female person’) and investigates which words are used to refer to that meaning. The observation that girl used to denote ‘young person’, and then came to denote ‘young female person’, takes a semasiological perspective of this lexical change. This means that the analysis starts from a word (e.g. girl) and investigates which meaning(s) the word can refer to. Semasiology and onomasiology are thus used for two complementary but inverse perspectives from which it is possible to view the connections between words and meaning. The term “semasiology” was first used by Reisig (for an overview of the development of the term, see Nerlich, 2001; 1881), and “onomasiology” was defined as its counterpart by Zauner (1902). Geeraerts (2004, p. 653) notes that: “Semasiology considers lexemes and the way their meanings are manifested. Onomasiology considers concepts and investigates the way they relate to one another through language and the way that they are denoted through language.” Similar definitions can be found in Kleparski and Borkowska (2007, p. 127) and Grondelaers, Speelman, and Geeraerts (2007, p. 989). The assumption that the concept does not change when a word is replaced is only valid for the most prototypical cases of lexical replacement. This thesis will, however, not limit itself to prototypical cases. Different lexical change processes overlap to a great degree, so that a particular historical change might involve both semantic change and lexical replacement.
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There are, of course, several other kinds of lexical change: for instance, sometimes a word is not replaced, but merely altered, as when television was replaced by tv. This kind of lexical form change is often connected to lexical replacement processes, but will not be a focus of this thesis.
2.3 LEXICAL REPLACEMENT AND PRIMARY WORDS So far, prototypical lexical replacement has been loosely defined as a process that occurs when a concept in a language is first primarily designated by one word, and then later by another word. Clearly, there can be many words that denote the same or at least a very similar concept. Kleparski (1997, p. 71) talks about a concept’s primary designating expression and a concept’s secondary designating expressions (called primary and secondary words in the rest of this thesis). The former has the greatest chance to be chosen by speakers to name any of the entities concept may legitimately refer to: the primary word is more neutral and has greater applicability than secondary words. As an example, in English, the concept ADULT FEMALE HUMAN BEING has as its primary word woman but also has several secondary words, like the nouns lady or female. After a word has been replaced (lexical replacement) as the primary word for a concept, it may remain in the language with a slightly different meaning (semantic change) – maiden is still used in English, but is a rare word that denotes a virgin (usually female) or used in constructions like maiden voyage or maiden speech (see Kleparski, 1997 for a detailed semantic history of words for girl in English). A former primary word that is replaced may also remain in the language and continue to denote the original concept as a secondary word. An example is Norwegian Bokmål pike, which was the most common term for ‘girl’ in the beginning of the 20th century, but which has now been superseded by jente. Pike is still used with the meaning ‘girl’, however, though it is seen as old-fashioned (Vejdemo, 2009). The assumption that there is often a single most neutral, most frequent word for a particular concept is useful mostly at a broader time scale – such as observing a change from maiden to girl as the most neutral way of referring to a ‘young female person’ in English. At smaller time scales, the situation becomes more complex – polysemy may occur, and different words might be used by different age groups or social groups in the language community.
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2.4 WHERE DO NEW PRIMARY WORDS COME FROM? When lexical replacement occurs, the new word can come from three principal sources (see also Grzega, 2003, p. 35): a) Speakers make the inference that an existing word in the language could also be used for the meaning in question. This other word is appropriated and given a new meaning. One example is seen in the Modern French word jument replacing the earlier word cavale for ‘mare’; jument originally meant ‘pack horse’. b) An inference is made from a new combination of linguistic elements already existing in the language. An example is seen in how Swedish städare ‘cleaner’ is in the process of being replaced by lokalvårdare ‘building+caretaker’. c) A word, interpreted as having a meaning similar to another word, is borrowed from another language (or dialect). An example is seen in how Swedish personalavdelning ‘employee+department’ is in the process of being replaced by the English loanword human resource (department), or its acronym HR. Several works have sought to build general, domain-overriding taxonomies to document the many different ways that a, b, and c (and other kinds of lexical change) may play out in languages (see e.g. Ullman, (1957). These taxonomies are mainly descriptive and make little attempt to predict what kind of lexical change might happen for a given concept. A discussion of these processes are outside the scope of this thesis, and it suffices to note that two of the most frequently recurring lexical change processes in the taxonomies are when a word comes to be used to denote A) more semantic material than it did before or B) less semantic material. A (or an idea very similar to A) is referred to as “expansion” in (an English translation of) Bréal (1897/1900) and “widening” in Ullman (1957). B (or an idea very similar to B) is referred to as “restriction” in Bréal (1897/1900) and “narrowing” in Ullman (1957). Another productive research area for generalizations on why and how lexemes change can be found in works on borrowing: for instance, it has been shown that words belonging to different word classes have different propensities for being borrowed (process c above). Haspelmath and Tadmor (2009b) use data from 41 languages in the World Loanword Database to show that there is a difference in how likely it is for borrowing to occur 13
(borrowability) in terms of word classes: most importantly, nouns are far more likely to be borrowed than verbs. This echoes earlier findings from, among others, Haugen (1950, p. 224), who looks at the speech of Norwegian immigrants to the United States and finds that nouns are more likely to be borrowed than verbs, which in turn are more likely to be borrowed than adjectives (this can be expressed as nouns > verbs > adjectives). Moravcsik (1975) claims that verbs are seldom borrowed into the recipient language as verbs, but are rather borrowed as nouns that then undergo verbalization. Singh (1980, p. 113) looks at English loanwords in Hindi and finds nouns > verbs > adjectives. Building on Haugen, Muysken (2000, p. 74) suggests instead the hierarchy nouns > adjectives > verbs. Wohlgemuth (2009, p. 292) contains a good overview of the research on this topic and cautions that while nouns do seem to be easier to borrow than verbs, this is mainly due to the fact that words with nouny semantic content are more common in languages than words with verby semantic content. The semantic content, not morphosyntactic features, are what drives the phenomenon, and the pragmatics of language contact situations means that words referring to concrete objects are more important to share than words referring to actions or qualities. These suggested borrowability rules are notably different from what is suggested about lexical replacement in general in Pagel, Atkinson and Meade (2007) (using Indo-European languages) and Vejdemo (2010) (using IndoEuropean and Austronesian data). These studies find that lexical replacement is more likely to affect verbs than nouns. The results for adjectives are inconclusive and vary for different methodologies and different data sets. The discrepancy between the semantic categories for a) the general likelihood for any kind of replacement (where verbs are more likely to be replaced) and b) the likelihood that the replacement happens due to borrowing (where nouns are more likely to be borrowed) may indicate that nouns and verbs undergo different typical replacement strategies. Nouns might be more likely to get replaced by borrowed words (as when Swedish krockkudde ‘lit. crash pillow, airbag’ was replaced by the loanword airbag under influence of the English word), according to strategy c above. Verbs might be more likely than nouns to be replaced by a synonym already present in the language (as when Swedish dinera ‘eat (dinner)’ became rarer and rarer so that it is now in the process of being replaced by the existing äta mat ‘eat food’), according to strategy a or b above. The inconclusive results for adjectives indicate the need for more studies of their replacement processes. 14
2.5 IS THERE REGULARITY IN LEXICAL CHANGE? The sheer amount of diversity in human lexicons, as well as the interdependence and complexity of different kinds of lexical change, has led some researchers to see lexical change as an unpromising object of systematic scientific inquiry. If lexical change is not regular, any attempts to investigate it will be purely descriptive. Lehrer formulates it thus: “Every word has its own history. About the best we have come to hope for is a taxonomy, or classification schema” (1985, p. 283). Several such classification schemas of different kinds of lexical change have been made – some of the most notable by (1886), Darmesteter (1887), Bréal (1897/1900), Stern (1931), and Ullman (1957). These often deal both with the reasons behind lexical change (for instance: people seek to innovate), the linguistic tools used in the change (for instance: metaphor), and the results of lexical change (for instance: the possible referents of a word increase in number.) Classification schemas of different kinds of changes can be very useful, but are, on their own, theoretical constructions that state facts and do not seek to explain them (see Anttila, 1989, pp. 146–148 for a critique of the value of schemas). Hock (1986, p. 308) seems to be of the opinion that explanations and generalizations are difficult to find: “there seems to be no natural constraints on the directions and results of semantic change”. While it might be difficult to formulate strictly causal explanations for lexical change, of the kind that are found in the natural sciences, general tendencies can be sought. Both Lehrer (1985) and Geeraerts (1997) write that some headway might be made – Lehrer (building on the Word Field Theory of Trier (1931) shows that generalizations can be made for specific semantic domains (such as animal terms or gambling terms), and Geeraerts (1997) notes that some statistical generalizations and probabilistic predictions can be sought for semantic and lexical change. This thesis will employ both of these approaches. Traugott and Dasher (2002, p. 1) are also hopeful, and claim that there are “predictable paths for semantic change across different conceptual structures and domains of language function” and that, while each instance of semantic change has its own story, semantic change is highly regular at a macro-level – both within a single language and across languages (Traugott & Dasher, 2002, p. 4). Traugott and Dasher express the opinion that these regularities are not absolute, however – they are “possible, indeed probable, tendencies, not 15
changes that are replicated across every possible meaningful item at a specific point in time in a specific language, such as the Neogrammarians postulated for sound change” (Traugott & Dasher, 2002, p. 1). The same authors (2002, pp. 3–4) further note that extralinguistic factors have a constant effect on the use and interpretation of words, and therefore on lexical change, and this can make it difficult to find patterns. They write that nouns are “particularly susceptible to extralinguistic factors such as change in the nature of the social construction of the referent. For example, the referents of towns, armor, rockets, vehicles, pens, communication devices, etc., have changed considerably over time, as have concepts of disease, hence the meanings attached to the words referring to them have changed in ways not subject to linguistic generalization”. Nonetheless, Traugott and Dasher (2002, p. 94ff) list three general tendencies of lexical change (Æ indicates change): x
x
x
Meanings based in the external described situation Æ meanings based in the internal (evaluative/perceptual/cognitive) described situation. E.g. Old English felan ‘touch’ Æ ‘experience mentally’, Modern English grasp ‘take’ Æ ‘understand’. Meanings based in the external or internal described situation Æ meanings based in the textual and metalinguistic situation. E.g. anyway Æ ‘pragmatic particle for return to previous topic’. Meanings tend to become increasingly based in the speaker’s subjective belief state/attitude toward the proposition. (This is the dominant tendency according to Traugott and Dasher.) E.g. the development of honorifics is ongoing, since yesteryear’s honorifics gradually lose their exalted meaning.
In addition to such domain-independent generalizations, directionality (of change) generalizations can also be found for much more specific semantic domains. Wilkins (1996) shows that names for smaller visible armrelated body parts often become names for larger contiguous body parts (nail Æ finger Æ hand), but not the other way around. Brown and Witkowski (1983) also work with body parts, and show that in small-scale societies, ‘eye’ is more unmarked than ‘face’ – and the latter may be derived by compounding or a derivation of the former. In the domain of color, Berlin and Kay (1969) suggest a particular universal evolutionary sequence according to which colors will appear in a language, and have claimed that this is unidirectional. This sequence will be discussed in more detail in chapter 4. 16
2.6 LEXICAL CHANGE IS NOT UNIFORM The rate of language change is different for different parts of the vocabulary – and different from time period to time period. There is evidence, for instance, that time periods following social and technological change see more language change. Johnson (1996) suggests that when society sees changes in technology, level of education, economy and quantity of information, this can lead to an increase in the rate of language change. She compares questionnaire data on word use that she collected in the 1990s with similar data collected in the 1930s, and shows that, for example, as familiarity with farming declined in the US, so did the knowledge of words pertaining to agriculture and husbandry. Speakers interviewed in the 1990s were often unable to supply synonyms to words like stallion, calve, ram. Juola (2003) makes a similar point. He uses KL-distance, an information theory algorithm that measures entropy, to compare the similarities of documents based on the similarities of the words they contain. Juola (2003) calculates the linguistic distance between different articles in the National Geographic magazine from 1939 to 2000. He finds that the rate of language change has not been uniform. Most notably, English changed less during the Second World War, and then had a period of particularly rapid change in the decades following the war. Juola (2003, p. 90) shows that at time periods as short as a decade, linguistic change is algorithmically perceptible. He theorizes that the social upheaval of the war caused both soldiers and civilians to have new experiences and encounter new technologies, and that this led to changes in the spoken language. Changes in the spoken language then took some years to percolate into the written language of the National Geographic. In Juola (2005, pp. 171–172) the author correlates the amount of linguistic change with the per capita rate of patents in the US over the time period 1930-1980. A significant correlation (r=0.32, pB” alone” (2001, p. 11). Traugott and Dasher's theory does not assume that meaning A will disappear, and there are other voices that caution against seeing elimination of a sense as the necessary end product of a polysemous state (see discussion in Koch, 2016; Nerlich & Clarke, 2001). A final example of a work that supports the idea of a link between polysemy and semantic change is Boussidan (2013), who investigates the amount of polysemy in English corpora through computer models and finds a link between high polysemy and a greater likelihood of semantic change. 26
The interplay between subjectification, polysemy, and semantic change is complex. As stated above, Kleparski argues that polysemy is a vehicle for semantic change – but it can surely also be the other way around: subjectification leads to semantic change, which leads to an increase in the number of senses. Perhaps the most useful statement that can be made is that a change in polysemy is connected to a change in semantics – and that both of these can be caused by subjectification. If a high rate of polysemy is connected to a greater propensity for semantic change, this does not mean that it would lead to a greater propensity for lexical replacement (cf. the results of the conserving effect versus the reducing effects of frequency discussed in 2.7.3). Fewer linguists have been interested in the link between lexical replacement and polysemy than in semantic change and polysemy. Kapitan (1994) studies the survival rates of Latin words in Romance languages, and finds that the more polysemous a linguistic sign (a word) is, the more chance there is that it will not be replaced. Lüdtke (1985, p. 363) notes that there is a possibility, which he considers to be remote, that “an item may get a somewhat longer respite from its inexorable fate of loss of identity […] by acquiring either a different or an additional meaning, if this process goes along with higher frequency of occurrence.” The reasoning is that a polysemous form would be used in many different genres and contexts, which might lead to a greater chance of form retention – it would be more difficult to replace the word, because it is used in more contexts. This would not only be a question of frequency, but also one of diversity: by being anchored in several different semantic networks, a polysemous form might be more entrenched. Turning to (near) synonymy, a lexeme in the mind of a speaker that has many different connections to other lexemes, might be more likely to undergo both semantic change and lexical replacement, due to speakers having more materials from which it is possible to make inferences: if a speaker has both the primary word wireless for RADIO (common in the first two decades of the 20th century) and a more rare synonym radio, the presence of the synonym might make lexical replacement easier. It is thus a reasonable hypothesis that the more semantically close a group of concepts are, the easier it is for speakers to make inferences that word W1 might be used instead of word W2 for a certain concept, and for lexical replacement to occur. Words that have many lexical relations (synonyms, hyponyms, etc.) might be more likely to expand or retract their denotational range of references than words with fewer lexical relations. Concepts that can be expressed by many different (overlapping) words could 27
be more likely to have changes in their lexical inventory than concepts that cannot. Therefore, if there is a way to measure how many semantically close neighboring concepts and/or semantically related words a target concept/word has, this measurement should correlate with the likelihood of lexical replacement for the target concept. Naturally, it is with synonymy as it is with polysemy: more synonyms might lead to a greater propensity for change, or replacement, or a propensity for change or replacement might lead to more synonyms. It is also logical to assume that if a word W1 has a greater number of senses than another word W2, then W1 will also have more potential synonyms: synonymy and polysemy are connected and are both highly relevant both for lexical replacement and semantic change.
2.7.5 SPEAKER AGE EFFECTS An important division within research into language change has historically been between those who believe that change primarily takes place between generations in the imperfect acquisition of language by children and those who believe that large scale change also happens later in life. The basic assumption of the former school of thought is that children make repeated mistakes when learning their first language, and that some of these mistakes are then incorporated into their language (see e.g. Halle, 1962). “The child is exposed to the utterances produced around her, and may intuit a grammar that is different in some way from the grammar of her parents” (Croft, 2000, p. 44). The changes the child makes then become part of a fixed new language for the next generation. Jespersen (1922, pp. 161–162) notes that earlier linguists had many and conflicting views on the matter. He reaches the conclusion that it is not the age of the individual learning a new language element that matters, but that the act of learning is of paramount importance in precipitating language change. Attributing change only, or primarily, to new learners also means that language change should be very abrupt, which is not the case (Croft, 2000, p. 45). Croft further notes (2000, p. 46ff) that the idea that imperfect learning is the only, or major, motor of language change is now mostly abandoned, but that it still can be found in some formalist syntactic theories, such as minimalism. While the exact strength of generational transmission effects on language change is debated, the argument that there are some effects is uncontroversial.
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Something that will be important later on in this thesis is the finding that different age groups innovate to different degrees – several studies find that younger people innovate more than older people (see Southworth, 1990). This also begs the question of if, and if so when, younger speakers stop innovating. Croft (2000, p. 49) notes that after adolescence (ages 6-12), errors in the language acquisition process of children are very rare, and that, after this stage, children’s non-normative language use is similar to the everyday innovations of adults. This means that at some point during childhood, vocabulary increases should stabilize. Interestingly, Hodgson and Ellis (1998) find that earlier acquired words are less likely to disappear from elderly (71–86 years of age) speakers’ inventories. Section 4.2.5 will discuss what is known about age of acquisition in relation to speakers’ color term vocabulary. The typical age of acquisition for a lexical item might be an indication of its level of entrenchment, since words that are acquired earlier might be more mentally entrenched. As discussed in section 2.7.3, entrenchment of a word form can insulate the word form from lexical replacement. Age of acquisition is also highly correlated with frequency (Blumenthal-Dramé, 2013, pp. 39–40). Age of acquisition will also be discussed in more detail in the next chapter, in the context of how likely it is to predict the rate of lexical replacement.
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3 MACRO-PERSPECTIVE: A MODEL OF SOME SEMANTIC AND PRAGMATIC CAUSES OF 4 LEXICAL REPLACEMENT This chapter focuses on research question A1, though A2 will be discussed briefly at the end, in section 3.5. A1. Is it possible to formulate global, domain-independent generalizations for lexical replacement? A2. How can local, domain-dependent generalizations be found? The chapter looks at lexical replacement from a macro time scale perspective (the age of Indo-European, approximately 5,000-8,000 years) and reduces the complex and gradual process of lexical replacement to a binary state: either a replacement has happened or it has not happened. By counting the number of replacements having taken place in 87 Indo-European daughter languages for a list of 176 concepts, a Rate of Replacement measurement may be derived for each concept. Following earlier research (Ladd, Roberts, & Dediu, 2015; Monaghan, 2014; see Pagel et al., 2007; Vejdemo, 2010), this chapter will take such a measurement – specifically one calculated by Pagel et al. (2007) – and use it to construct a statistical model that evaluates several of the proposed semantic and pragmatic factors that were hypothesized to contribute to the rate of lexical replacement (discussed in section 2.7). Specifically, the model will be used to evaluate the claims that the following factors influence the rate of lexical replacement: emotional charge / arousal (discussed earlier in section 2.7.1); word class and imageability (see 2.7.2); entrenchment (operationalized both as frequency and as mutual information, see 2.7.3); synonyms and polysemy (see 2.7.4); and the age of acquisition (see 2.7.5).
A condensed version of this chapter has been published in Vejdemo and Hörberg (2016). Background research, data collection, analysis, and initial model design for that article were done by the author of this thesis, and Hörberg focused on setting up and running the final statistical model. This chapter is substantially longer than the article, and sections 3.5 and 3.6 contain entirely new material. 4
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In this chapter, comparative concepts (e.g. WOMAN) are not defined outside the semantic content alluded to by their English meta-language labels. Their translations into particular languages (e.g. Swedish kvinna, English woman) are assumed to be a close enough match, semantically, to the meaning of the English meta-label. Lexical replacement is treated, in the perspective taken in this chapter, as a fact, not as a process. Its relationship to other lexical change processes, such as semantic change, is not investigated. Section 3.1 will provide some background on lexical replacement – how it can be measured, the role of Swadesh lists in studying it, and some previous statistical models that use Swadesh lists. Section 3.1.4 will discuss some problems with existing statistical models, and motivate why the model in this chapter is structured the way it is. Section 3.2 will present the data and methodology of the new model, while section 3.3 will present and evaluate the model. Section 3.4 summarizes what generalizations about lexical replacement might be assumed based on the model, and section 3.5 addresses the conspicuous absence of semantic domains as a factor in the model, and provides a bridging context to the rest of the thesis. Table 2 shows the place of this chapter within the thesis. Table 2. The place of the present study within the thesis. Time scale & scope Method & material
Domain
Chapter 3 Macro: several millennia, 87 language varieties A statistical model tests domainindependent hypotheses about lexical replacement (based on a database of cognate class judgments of a Swadesh list) Core vocabulary
Chapter 5 Meso: several centuries, seven Germanic languages Comparison of variation, using elicitation experiment results, supplemented with dictionary data
Color, with focus on pink and purple
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Chapter 6 Micro: two generations, one language Comparison of variation and change, using elicitation experiment results, supplemented with interviews, dictionaries, floras, corpora Color, with focus on pink and purple
3.1 BACKGROUND AND METHOD In section 3.1.1, the case is made that the rate of lexical replacement can be measured, and a way to calculate the rate is discussed. In section 3.1.2, the Swadesh lists that are often used as data sources for these kinds of measurements are discussed. Following that, some earlier models that use the rate are presented (3.1.3) and subsequently evaluated (3.1.4).
3.1.1 MEASURING LEXICAL REPLACEMENT: BASIC ASSUMPTIONS Over the years, many researchers have noted that the primary words (the most neutral term for a concept, see section 2.3 for full definition) for lexical concepts are replaced at different rates – and that this rate can be calculated (see “Stability Ranking” in Dolgopolsky (1986) and “Retentiveness” in Lohr (1999), “Rate of Lexical Replacement” in Pagel et al. (2007)). These authors use slightly different methods to calculate the rate, though their end results are very similar. An illustrative example for a very simple method comes from Dahl (2004, p. 262). Dahl contrasts how the Latin word form for the concept THREE (tres) was retained in all the daughter languages he surveyed with how the Latin word for girl (puella) has been replaced as the primary word in all the languages, as shown in Table 3. When two semantically similar words in two different languages are related, they belong to the same cognate class. Thus, since both the Venetian word fia ‘girl’ and French (jeune) fille ‘girl’ are historically developed from Latin filia ‘daughter’, they are related and are therefore considered to belong to the same cognate class. By counting cognate classes, it is possible to quantify the relative likelihood of replacement for THREE and GIRL in the Romance family: the number of cognate class replacements is divided by the number of languages in the sample. To illustrate this: if all languages (15 in the Dahl (2004) sample) use words for THREE from the same cognate class, the rate of lexical replacement can be expressed as 1/15 = 0.07. As can be seen in Table 3, there are 15 different cognate classes for GIRL in the 15 languages: the rate of change can be expressed as 15/15 = 1.00. Note that this “rate of replacement” measurement is not comparable between different language sample sizes: if no replacement occurs for THREE in a sample of 15 languages, the rate would be 1/15. If no replacements occur for TWO in a sample of 100 languages, the rate is 1/100 – in other words, rates are comparable within a sample, not across samples.
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Table 3. Words for GIRL and THREE in selected Romance languages Latin
Asturian
tres
puella
tres
Cata -lan tres
Corsican trè
1
1
1
moza
minyona giuvanotta
1 2 Romanian Romansh Sardini -an trei trais tres 1
1
1
fata
giuvna
pitzinna
11
3
12
3 Sicili -an tri 1
French Galici- Gascon Italian Portu- Proven an guese -cal trois tres tres tre três tres 1
1
1
1
(jeune) rapaza gojata ragazza; menina fille fanciulla 4 5 6 7; 8 9 Spanish Veneti- Walloon an tres tri treus Sum: 1 cognate class 1 1 1 1/15 = 0.07
picciotta muchacha fia; tóxa 12
1
13
4; 14
båcele 15
1 chato 10
Sum: 15 cognate classes 15/15 = 1.00
Sometimes there are two or more synonyms that are equally applicable as primary word for a concept – say ragazza and fanciulla in Italian for GIRL. The researcher would then need to decide whether to choose just one of these terms (at random) or to include both of them in the data set. This kind of measure can also be used for data from language families where, unlike Romance, the proto-language is not well-known. An assumption is made that the proto-language had a single primary word for a certain concept. If the concept is still denoted by the same cognate class in all daughter languages, it seems likely that no replacement has occurred. However, if the concept is denoted by many different cognate classes in the daughter languages, one could say that lexical replacement has indeed occurred for the concept. There are several potential problems with this calculation of a rate of lexical replacement. The first is that there might have been several primary expressions in the proto-language at some point. Fortunately, very close synonyms rarely stay synonymous, but often diverge, at least slightly, in meaning. Any such state of synonymy thus only holds for brief moments in time. Another potential problem could be borrowing. Several daughter languages might in fact undergo lexical replacement for a concept, but this diachronic diversity could then be hidden by a common loanword being incorporated into all the languages. This can be countered by using sets of concepts that are very resistant to borrowing. The example of Romance words for GIRL was used to illustrate the general principles behind using cognate classes to estimate the rate of lexical 33
replacement. In the following sections, specific instantiations of these principles will be discussed.
3.1.2 LEXICAL REPLACEMENT AND SWADESH LISTS Databases with Swadesh lists are routinely used for investigations into lexical replacement, and this section will discuss their strengths and weaknesses. Swadesh (1950) proposes lists of diachronically very stable concepts, with the aim of gathering lexical denotations for a set of concepts from as many languages as possible: these lists are now referred to as Swadesh lists. The most commonly used versions are the 100-word Swadesh list and the 200-word Swadesh list. The original purpose of the lists was to investigate the historical relationship between different languages, based on the assumption that the concepts in the lists would undergo replacement at the same constant rate over time. This assumption was later proved to be false by, among others, Rea (1958); Bergsland and Vogt (1962); and Dyen, James, and Cole (1967). Nonetheless, Swadesh lists are still routinely used by field workers, as they are one of the few quantifiable methods used to determine the relative closeness of two or more languages. The present study does not involve investigating genealogical relationships of languages. The genetic relationships of the languages are unimportant for comparing the relative rate of change (assessed from all the languages) of one concept to the relative rate of change of another concept (assessed from the same languages). Whatever the genetic relationships between the languages, this state of affairs will affect all the concepts in a language in the same way. A key assumption when using cognate classes to measure relative rates of replacement is that the shared human physiology and world experience make humans categorize the world in similar ways. Some comparative concepts, like STONE or TO SLEEP, should often have matches in languages across the world. The rate of lexical replacement is a feature of such a comparative concept and is assumed to, at least to a certain extent, account for the lexical replacement rate of the matching words in each language. The fact that these words are pre-selected for their supposed stability means that the Swadesh lists may not be a good representative sample of the entire vocabulary of a language. Even so, they are often chosen for investigations into lexical replacement. There are two main reasons for this. The first reason is the availability of data. There are several published databases with Swadesh wordlists from hundreds of languages, where the data 34
is tagged with cognate class judgments. Examples include Dyen, Kruskal and Black (1992) on Indo-European, the IELex (http://ielex.mpi.nl/) and the Austronesian Basic Vocabulary Database (Greenhill, Blust, & Gray, 2008). The second issue is the possible problem of borrowing, mentioned in section 3.1.1. This should be less of an issue with the Swadesh data, since the items included in a Swadesh list are pre-selected for low likelihood of borrowing – nonetheless, this assumption will be tested on the new model in section 3.2. How different are the concepts on the Swadesh list from the language as a whole? Their language-specific translations skew towards higher frequency compared to the vocabulary as a whole (Kapitan, 1994, p. 239; Piantadosi, 2014, p. 1116). The Swadesh list concepts are also, as was originally intended by Swadesh, less likely to be replaced over time. Sankoff (1970) shows that the Swadesh lists do have a lower rate of replacement. He calculates and compares a rate of replacement (called λm) for two sources: a) 1077 comparative concepts from Buck (1949), which has translations and cognate judgments from 31 Indo-European languages, and b) 159 Swadesh list comparative concepts from Dyen et al. (1992), which has translations and cognate judgments from 95 Indo-European language varieties. Sankoff (1970) is able to show that, as a set, the Swadesh comparative concepts generally have a lower rate of replacement than the set of comparative concepts from Buck (1949). This is illustrated in the histogram in Figure 1, where the X-axis is the rate of replacement and the Y-axis is the proportion of meanings: approximately 20% of the Swadesh meanings had a rate of replacement between 0.32-0.40 λm while approximately 15% of the Buck meanings fall into the same bracket. The Buck list words approach a normal distribution when it comes to different rates of replacement, while it is clear that the Swadesh list is skewed to the left: the Swadesh list has more stable concepts (i.e. with a lower rate of replacement)5 than the Buck list. The Buck list of concepts is not as obviously pre-selected for stability as is the Swadesh list, and is a better sample of a natural language lexicon. Yet the Buck list is not a random list of words either, since the author’s intention was to trace the concepts’ lexicalizations back to Sanskrit and Old High
Unfortunately the digitized data from Buck (1949) used in Sankoff (1970) is no longer available (David Sankoff, p.c.), and a redigitalization of the data in the Buck dictionary would require substantial amounts of time and effort.
5
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German: concepts like SUN and STONE are included; concepts like CAR and TELEPHONE are not.
Figure 1. Proportion of meanings with different rates of change. Figure redone from Sankoff (1970, p. 567, figure 2). What is the effect of the skewed nature of the Swadesh data on models that try to use it to predict the rate of replacement for the entire mental lexicon? The models will certainly be better at predicting the behavior of other frequent, stable concepts, than they are at accounting for the variation in replacement rates for sets of infrequent, unstable concepts.
3.1.3 EARLIER MODELS OF LEXICAL REPLACEMENT This section will present several recent endeavors to statistically model lexical replacement. These models will be evaluated in section 3.1.4, and a new model will be presented from section 3.2 and forward. Pagel et al. (2007) present a model that partly accounts for the rate of lexical replacement, based on frequency and word class. The authors calculate the rate of lexical replacement for 200 Swadesh items by using cognate class categorizations originally gathered by Dyen et al. (1967) and weighting this by also taking the historic relationships of the languages into consideration. This weighting is unnecessary if the goal is to compare the difference between concept rates, and in practice the difference between the results of the Pagel method and the simple method used as an example in section 3.1.1 is negligible: a correlation test shows a near perfect match (R=0.93 p
