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Seeing Patterns and Learning to Do Things and what that has to do with language David Tuggy SIL-Mexico.

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1 Seeing Patterns and Learning to Do Things and what that has to do with language David Tuggy SIL-Mexico

2 Is “the language faculty” a black box? Is language something totally different from the rest of what we do in our minds? Is language something totally different from the rest of what we do in our minds? If not, how are they connected? What does what we do mentally in general tell us about language? If not, how are they connected? What does what we do mentally in general tell us about language? (And what does language tell us about our mental capacities and activities generally?) (And what does language tell us about our mental capacities and activities generally?)

3 Cognitive Grammar (CG) claims that much that we find in language dovetails with what we know about other aspects of cognition. Cognitive Grammar (CG) claims that much that we find in language dovetails with what we know about other aspects of cognition. Language is amazing, but it is not totally different from or unrelated to the rest of our mental activities. Language is amazing, but it is not totally different from or unrelated to the rest of our mental activities. Non-linguistic cognition is pretty amazing too. Non-linguistic cognition is pretty amazing too.

4 Outline I plan to divide this talk into two sections: I plan to divide this talk into two sections: I.We have amazing abilities to Acquire complex and flexible habits (learn to do things) Acquire complex and flexible habits (learn to do things) Compare and categorize experiences (see patterns and apply them in novel ways) Compare and categorize experiences (see patterns and apply them in novel ways) II. Understanding these abilities can clarify our understanding of what language is and how it functions. In particular We should be careful not to simplify by setting learning and the application of patterns against each other as if they were mutually exclusive. We should be careful not to simplify by setting learning and the application of patterns against each other as if they were mutually exclusive.

5 We are good at learning to do things Think about what is involved in driving a car. Think about what is involved in driving a car. One way to assess it is to consider what it would take to teach a robot to do the same. One way to assess it is to consider what it would take to teach a robot to do the same. There are a host of more-basic skills that must be mastered, that are recruited into the skill of driving. There are a host of more-basic skills that must be mastered, that are recruited into the skill of driving.

6 We are good at learning to do things For instance (on the perception side of things): For instance (on the perception side of things): Binocular visual perception: triangulation and depth perception. Binocular visual perception: triangulation and depth perception. Perception of 3-dimensional space and assessment of your position in it. Perception of 3-dimensional space and assessment of your position in it. Calculation of your, and your car’s, motion, rate of motion, direction of motion, etc. Calculation of your, and your car’s, motion, rate of motion, direction of motion, etc. Calculation of other vehicles’, and pedestrians’, etc. motion, rate, direction, etc. Calculation of other vehicles’, and pedestrians’, etc. motion, rate, direction, etc.

7 We are good at learning to do things (still on the perception side of things): (still on the perception side of things): Perception of where the parts of your body are with respect to each other and to the immediate surroundings (like the car seat, gear shift, steering wheel.) Perception of where the parts of your body are with respect to each other and to the immediate surroundings (like the car seat, gear shift, steering wheel.) Hearing car sounds, horns, and road noise, and evaluation of their significance. Hearing car sounds, horns, and road noise, and evaluation of their significance. Seeing and recognizing details like turn signals and brake lights. Seeing and recognizing details like turn signals and brake lights. Knowing where your mirrors are, and how to interpret what you see in them. Knowing where your mirrors are, and how to interpret what you see in them.

8 We are good at learning to do things More on the motor side of things: More on the motor side of things: Turning your head and eyes for optimum seeing. Turning your head and eyes for optimum seeing. Knowing how to move other body parts. Knowing how to move other body parts. Knowing how to move (without watching) to the controls of the car and then move the controls. Knowing how to move (without watching) to the controls of the car and then move the controls. Assessing what your motions will do. Assessing what your motions will do. Assessing and controlling how hard, fast and far the motions will/should carry. Assessing and controlling how hard, fast and far the motions will/should carry. Adjusting all of the above to the perceptions mentioned before, in real time. Adjusting all of the above to the perceptions mentioned before, in real time.

9 We are good at learning to do things These (and other) skills are combined and coordinated in various sophisticated, highly flexible ways, into such higher-order skills as: These (and other) skills are combined and coordinated in various sophisticated, highly flexible ways, into such higher-order skills as: Starting and accelerating Starting and accelerating Steering to the right or to the left Steering to the right or to the left Staying on the road and in your lane Staying on the road and in your lane Shifting gears Shifting gears Slowing and stopping, not running into cars ahead Slowing and stopping, not running into cars ahead Changing lanes, passing other vehicles Changing lanes, passing other vehicles Obeying traffic signals and signs. Obeying traffic signals and signs.

10 We are good at learning to do things These in turn are likely to form part of such ordinary activities as: These in turn are likely to form part of such ordinary activities as: Going to work. Going to work. Running an errand. Running an errand. Visiting your parents. Visiting your parents. The whole package is so complex that it takes considerable time to learn to do it well The whole package is so complex that it takes considerable time to learn to do it well We continue to upgrade and relearn these skills even after we have mastered them. We continue to upgrade and relearn these skills even after we have mastered them.

11 We are good at learning to do things They become so ordinary to us that we can do them on “autopilot”, as it were, hardly paying any attention to what we are doing, much less taking in the full complexity of it all. They become so ordinary to us that we can do them on “autopilot”, as it were, hardly paying any attention to what we are doing, much less taking in the full complexity of it all. We adapt them with exquisite precision to new situations. We adapt them with exquisite precision to new situations. The consequences of doing them poorly are likely to be lethal. The consequences of doing them poorly are likely to be lethal. Yet we regularly and almost unthinkingly trust ourselves and thousands of others to do them right (or at least well enough). Yet we regularly and almost unthinkingly trust ourselves and thousands of others to do them right (or at least well enough).

12 We are good at learning to do things Besides the perceptual and motor-related skills are more “autonomous” ones; Besides the perceptual and motor-related skills are more “autonomous” ones; E.g. evaluation of other cars’ motions and inferences about their drivers’ intentions, reading signs, judgment of the passage of time, calculation of odds, calculations about what speed to take a corner or a speed bump at, and comparison of the result with the anticipated situation, etc. etc. E.g. evaluation of other cars’ motions and inferences about their drivers’ intentions, reading signs, judgment of the passage of time, calculation of odds, calculations about what speed to take a corner or a speed bump at, and comparison of the result with the anticipated situation, etc. etc.

13 We are good at learning to do things Language is a set of skills of this sort. Language is a set of skills of this sort. It involves coordinating hugely complex muscular, perceptual, and “autonomous” cognitive skills. It involves coordinating hugely complex muscular, perceptual, and “autonomous” cognitive skills.

14 We are good at learning to do things Many levels of such skills are recruited as parts of other, higher-level skills. Many levels of such skills are recruited as parts of other, higher-level skills. We can say “I wouldn’t have believed that she would have said anything of the sort” and understand it in context while hardly paying any attention to it, certainly without consciously realizing its enormous complexity. We can say “I wouldn’t have believed that she would have said anything of the sort” and understand it in context while hardly paying any attention to it, certainly without consciously realizing its enormous complexity.

15 We are good at learning to do things CG recognizes this, defining a language as a “structured inventory of conventionalized linguistic units”. CG recognizes this, defining a language as a “structured inventory of conventionalized linguistic units”. A “unit” is a skill we have mastered, a cognitive routine we can run through without having to put “constructive effort” into it. A “unit” is a skill we have mastered, a cognitive routine we can run through without having to put “constructive effort” into it. There are hierarchies upon hierarchies of such skills involved in our use of language. There are hierarchies upon hierarchies of such skills involved in our use of language.

16 What is it that we learn to do? An important point is that though we learn these skills (linguistic or otherwise) from our experiences, they cannot be equated with particular actual experiences. An important point is that though we learn these skills (linguistic or otherwise) from our experiences, they cannot be equated with particular actual experiences. Not every neuron that fired will fire again in exactly the same way the next time we implement the skill (e.g. of perceiving a car braking on the road ahead, or of saying “she wouldn’t’ve said it”). Not every neuron that fired will fire again in exactly the same way the next time we implement the skill (e.g. of perceiving a car braking on the road ahead, or of saying “she wouldn’t’ve said it”).

17 What is it that we learn to do? Rather these are patterns of activation. Rather these are patterns of activation. They permit a certain amount of “slop” or leeway. They permit a certain amount of “slop” or leeway. This “slop” or leeway is extremely important. This “slop” or leeway is extremely important. It is what permits us to recognize a new situation as one of a kind we’ve seen before. It is what permits us to recognize a new situation as one of a kind we’ve seen before. It also permits us to act in a new way that is nevertheless one of a kind we have done before. It also permits us to act in a new way that is nevertheless one of a kind we have done before.

18 Extracting patterns CG talks about this in terms of all the “units” being “schematic” to one degree or another. CG talks about this in terms of all the “units” being “schematic” to one degree or another. Think “Schema” = “Pattern”. Think “Schema” = “Pattern”. There are higher-level (more abstract) and lower-level (more specific) patterns, and patterns of many kinds There are higher-level (more abstract) and lower-level (more specific) patterns, and patterns of many kinds It is “patterns all the way down”, as far as language is concerned. It is “patterns all the way down”, as far as language is concerned.

19 Extracting patterns Schemas arise as experiences are compared and commonalities noted. Schemas arise as experiences are compared and commonalities noted. A schema embodies the commonalities of its subcases. A schema embodies the commonalities of its subcases. Consider the (already schematic yet still rather specific) concept of a pencil. Consider the (already schematic yet still rather specific) concept of a pencil.

20 Extracting patterns As this concept is compared to the similar concept of a ballpoint pen, there are notable similarities. As this concept is compared to the similar concept of a ballpoint pen, there are notable similarities.

21 Extracting patterns These similarities together constitute a schema (pattern) we can call ‘writing instrument’. These similarities together constitute a schema (pattern) we can call ‘writing instrument’.

22 Extracting patterns This kind of relationship is traditionally represented in CG by an arrow from schema to subcase: A  B means “A is schematic for B; B is a subcase of A.” This kind of relationship is traditionally represented in CG by an arrow from schema to subcase: A  B means “A is schematic for B; B is a subcase of A.”

23 Extracting patterns This relationship is by nature asymmetrical. This relationship is by nature asymmetrical. Every specification of the schema (pattern) holds true of the subcases; Every specification of the schema (pattern) holds true of the subcases; Not vice versa. Not vice versa.

24 Extracting patterns There is an interesting sense in which either the subcase(s) or the pattern can be seen as “basic” to the other. There is an interesting sense in which either the subcase(s) or the pattern can be seen as “basic” to the other.

25 Extracting patterns (1) The schema is extracted from, and comes into being because of, the subcases. In this sense the system is built “bottom-up” (1) The schema is extracted from, and comes into being because of, the subcases. In this sense the system is built “bottom-up” (2) Once it is estab-lished (learned), the schema legitimizes (sanctions) its subcases in “top-down” fashion. (2) Once it is estab-lished (learned), the schema legitimizes (sanctions) its subcases in “top-down” fashion.

26 Applying patterns productively Particularly, a well-established schema can sanction novel structures. Particularly, a well-established schema can sanction novel structures. This includes “partial sanction”, where the “subcase” contradicts some of the schema’s specifications. This includes “partial sanction”, where the “subcase” contradicts some of the schema’s specifications.

27 Extracting and applying patterns This is the way linguistic rules work under CG. This is the way linguistic rules work under CG. Rules are simply schemas. Applying a rule is letting the rule sanction a more specific subcase. Rules are simply schemas. Applying a rule is letting the rule sanction a more specific subcase. If the subcase is a new one, the rule is applied productively. If the subcase is a new one, the rule is applied productively. Like any other linguistic structures, rules are part of the language to the extent that they are learned conventionally (thus known and known to be known by all in the relevant group.) Like any other linguistic structures, rules are part of the language to the extent that they are learned conventionally (thus known and known to be known by all in the relevant group.) Once learned, they can sanction novel structures. Once learned, they can sanction novel structures.

28 Learning and using patterns E.g. a kid may learn the words sugary and salty, and by comparing them, extract a schema FOOD-y. E.g. a kid may learn the words sugary and salty, and by comparing them, extract a schema FOOD-y. FOOD-y is a nascent rule, and the child may use it to invent new words like vinegary or orangey. FOOD-y is a nascent rule, and the child may use it to invent new words like vinegary or orangey.

29 Learning & Patterns From all of this it should be clear that learning things (establishing units) and extracting schemas (making generalizations) and applying them are not mutually-exclusive activities. From all of this it should be clear that learning things (establishing units) and extracting schemas (making generalizations) and applying them are not mutually-exclusive activities.

30 Learning & Patterns Everything we have learned (e.g. all the established structures in the diagram below) are generalizations (schemas, patterns). Everything we have learned (e.g. all the established structures in the diagram below) are generalizations (schemas, patterns).

31 Learning & Patterns The schemas aren’t much good to us until we have learned them (mastered them as units). The schemas aren’t much good to us until we have learned them (mastered them as units). Once we have done so, we can use them to come up with new subcases, which may in turn be learnt. Once we have done so, we can use them to come up with new subcases, which may in turn be learnt.

32 Learning & Patterns Different people can learn slightly different units, as long as their system is close enough to somebody else’s that they can talk. Different people can learn slightly different units, as long as their system is close enough to somebody else’s that they can talk. Vinegary or orangey may be learned, but if not, they are still understandable because they are sanctioned by the schema (rule) FOOD-y. Vinegary or orangey may be learned, but if not, they are still understandable because they are sanctioned by the schema (rule) FOOD-y.

33 Learning & Patterns Knowing (having mastered) a schema and knowing (having mastered) a subcase are not mutually-exclusive propositions. Knowing (having mastered) a schema and knowing (having mastered) a subcase are not mutually-exclusive propositions. To the contrary, knowing the subcases helps extract the schema, and knowing the schema reinforces the subcases. To the contrary, knowing the subcases helps extract the schema, and knowing the schema reinforces the subcases.

34 The traditional contrast between Regularity and Irregularity (Shifting gears — downshifting??—) (Shifting gears — downshifting??—) In most linguistics of the last 100 years, the contrast between what is regular and what is irregular is given enormous importance. In most linguistics of the last 100 years, the contrast between what is regular and what is irregular is given enormous importance. (Regular = according to rule, i.e. it fits a schema) (Regular = according to rule, i.e. it fits a schema)

35 The traditional contrast between Regularity and Irregularity It is often considered important to maximize the regular and minimize the irregular in our models of language (so as to be “scientific”). It is often considered important to maximize the regular and minimize the irregular in our models of language (so as to be “scientific”). The problem is it has been assumed that only irregular things are learned. The problem is it has been assumed that only irregular things are learned.

36 The traditional contrast between Regularity and Irregularity It is assumed that: Regular = systematic = predictable = produced by rule. It is assumed that: Regular = systematic = predictable = produced by rule. Irregular = idiosyncratic = arbitrary = learned Irregular = idiosyncratic = arbitrary = learned There is assumed to be a dichotomy between these two categories. There is assumed to be a dichotomy between these two categories.

37 The traditional contrast between Regularity and Irregularity This difference is typically made into part of the architecture of linguistics. The regular/predictable is the province of grammar, the irregular is the province of the lexicon. This difference is typically made into part of the architecture of linguistics. The regular/predictable is the province of grammar, the irregular is the province of the lexicon.

38 The traditional contrast between Regularity and Irregularity The system assumes nice neat “modules”. The system assumes nice neat “modules”. It is therefore considered important to establish if a particular kind of structure is to be accounted for “in the grammar” or “in the lexicon.” It is therefore considered important to establish if a particular kind of structure is to be accounted for “in the grammar” or “in the lexicon.”

39 The traditional contrast between Regularity and Irregularity Structures are taken to be of fundamentally different sorts, and are processed in very different ways, if they are “in the grammar”, than if they are “in the lexicon”. Structures are taken to be of fundamentally different sorts, and are processed in very different ways, if they are “in the grammar”, than if they are “in the lexicon”.

40 The traditional contrast between Regularity and Irregularity So, if a word like sugary, or a phrase like over the top, could be produced by rule, the presumption is that in fact it is produced by rule. So, if a word like sugary, or a phrase like over the top, could be produced by rule, the presumption is that in fact it is produced by rule.

41 The traditional contrast between Regularity and Irregularity The schema is real, the subcases are epiphenomenal. The schema is real, the subcases are epiphenomenal. In effect, if you first learned the specific structure, as soon as you learn how to produce it by rule, you forget it and remember only the rule. In effect, if you first learned the specific structure, as soon as you learn how to produce it by rule, you forget it and remember only the rule.

42 The traditional contrast between Regularity and Irregularity All members of the category alike are produced by the rule rather than learned. All members of the category alike are produced by the rule rather than learned. This is justified because it makes the model simpler and more predictive. (Science is all about prediction, right?) This is justified because it makes the model simpler and more predictive. (Science is all about prediction, right?)

43 The traditional contrast between Regularity and Irregularity Now this was so obviously wrong for many words that the model was modified: morphology (word- formation) was distinguished from syntax (“real” grammar), Now this was so obviously wrong for many words that the model was modified: morphology (word- formation) was distinguished from syntax (“real” grammar), because (oversimplifying) so often many examples of a morphological rule had clearly been learned. because (oversimplifying) so often many examples of a morphological rule had clearly been learned.

44 The traditional contrast between Regularity and Irregularity As a result, morphological structures and rules were taken to be different in kind from syntactic structures and rules; they were taken care of in a different “module”. As a result, morphological structures and rules were taken to be different in kind from syntactic structures and rules; they were taken care of in a different “module”.

45 The CG view For CG, the dimensions of the predictability distinction are gradual, and though they tend to line up, they are not exactly parallel. For CG, the dimensions of the predictability distinction are gradual, and though they tend to line up, they are not exactly parallel.

46 The CG view The distinction between what is produced by rule and what is learned is of especial interest to CG. The distinction between what is produced by rule and what is learned is of especial interest to CG. It is the only one of these four that is directly cognitive (dealing with how the system processes the structure). It is the only one of these four that is directly cognitive (dealing with how the system processes the structure).

47 The CG view It is closely tied to the two abilities we have been discussing. It is closely tied to the two abilities we have been discussing. Producing something by rule is using a schema to sanction it, especially if it itself is not (yet) learnt. Producing something by rule is using a schema to sanction it, especially if it itself is not (yet) learnt. Learning is (of course) learning, routinizing a skill, making a sequence of cognitive activations into a unit, then recalling that unit, as needed, from cognitive storage (memory). Learning is (of course) learning, routinizing a skill, making a sequence of cognitive activations into a unit, then recalling that unit, as needed, from cognitive storage (memory).

48 The computer analogy A standard (and largely useful) to talk about these issues is on the analogy of a computer. A standard (and largely useful) to talk about these issues is on the analogy of a computer. Learned information is analogous to what is stored on the hard drive, and information produced by rule is analogous to information produced by a program and not stored. Learned information is analogous to what is stored on the hard drive, and information produced by rule is analogous to information produced by a program and not stored.

49 The computer analogy This makes it less than immediately obvious that the distinction is one of degree. This makes it less than immediately obvious that the distinction is one of degree. What degree is there between information that is on the hard disk and information that is not? What degree is there between information that is on the hard disk and information that is not? In a sense, none. In a sense, none.

50 The computer analogy But that’s like saying there is an absolute, binary, modular difference between the word giraffe written here on the screen and giraffe here, or in a book. But that’s like saying there is an absolute, binary, modular difference between the word giraffe written here on the screen and giraffe here, or in a book. It’s true in a sense, but for most purposes it’s much more important to see that it’s the same word (pattern = schema) either place. It’s true in a sense, but for most purposes it’s much more important to see that it’s the same word (pattern = schema) either place.

51 The computer analogy For information from a program or from the hard disk to be useful, it has to be brought to working memory (RAM). For information from a program or from the hard disk to be useful, it has to be brought to working memory (RAM). Once it’s there, it doesn’t much matter where it came from. Once it’s there, it doesn’t much matter where it came from. The same information (pattern = schema) can be in both places at once, and transferred back and forth. The same information (pattern = schema) can be in both places at once, and transferred back and forth.

52 The computer analogy There is not a dichotomic difference between kinds of information that are on the hard drive and those that are produced by computation. There is not a dichotomic difference between kinds of information that are on the hard drive and those that are produced by computation. Once it’s in working memory, you can’t necessarily tell, from the kind of information it is, where it came from. Once it’s in working memory, you can’t necessarily tell, from the kind of information it is, where it came from.

53 The computer analogy The original information, the program that massages it, and the resulting computed data can all be together on the hard drive, or all together in the working memory, or in both, at the same time, and still be accessible. The original information, the program that massages it, and the resulting computed data can all be together on the hard drive, or all together in the working memory, or in both, at the same time, and still be accessible.

54 Non-linguistic cognition again What’s 9 x 8? What’s 9 x 8? How did you figure it? How did you figure it? 10 x 8 = 80, -8 = x 8 = 80, -8 = x 9 = 90, -(9 x 2 = 18), = x 9 = 90, -(9 x 2 = 18), = 72 8 x 8 = 64, +8 = 72 8 x 8 = 64, +8 = 72 Or just, oh yeah, 9 x 8 = 72. Or just, oh yeah, 9 x 8 = 72. You can figure (compute it, produce it by rule) in any of a number of different ways, or just remember it. You can figure (compute it, produce it by rule) in any of a number of different ways, or just remember it. Different ones can retrieve a date (say your father’s birthday) in different ways. Different ones can retrieve a date (say your father’s birthday) in different ways. For most practical purposes, how you get it doesn’t matter at all, as long as you get it right. For most practical purposes, how you get it doesn’t matter at all, as long as you get it right.

55 Humans aren’t computers anyway Two important differences between computers’ and humans’ cognition are (1) salience and (2) how storage works. Two important differences between computers’ and humans’ cognition are (1) salience and (2) how storage works.

56 Humans aren’t computers anyway Patterns in humans’ minds differ in salience (cognitive prominence). Non-salient patterns are less clearly “there”. Salient patterns “stand out” and attract attention. Patterns in humans’ minds differ in salience (cognitive prominence). Non-salient patterns are less clearly “there”. Salient patterns “stand out” and attract attention.

57 Humans aren’t computers anyway The result is that categories are not homogenous. Some members may be novel, produced by rule, others, while sanctioned by the rule, are also learned in their own right. The result is that categories are not homogenous. Some members may be novel, produced by rule, others, while sanctioned by the rule, are also learned in their own right.

58 Humans aren’t computers anyway And the cases which have been learned differ in their salience according to their usage. And the cases which have been learned differ in their salience according to their usage.

59 Humans aren’t computers anyway Repetition increases salience; all else being equal, often-repeated structures are entrenched with ever-greater salience. Repetition increases salience; all else being equal, often-repeated structures are entrenched with ever-greater salience. This may give a better picture of the general way a category might develop : This may give a better picture of the general way a category might develop : And so forth. And so forth.

60 Humans aren’t computers anyway (To repeat :) (To repeat :) Repetition increases salience; all else being equal often-repeated structures are entrenched with ever-greater salience. Repetition increases salience; all else being equal often-repeated structures are entrenched with ever-greater salience. (Repetition isn’t the only thing that enhances salience, but we won’t go into the others here.) (Repetition isn’t the only thing that enhances salience, but we won’t go into the others here.) ∴ frequency counts correlate highly with salience. Common structures are especially important. ∴ frequency counts correlate highly with salience. Common structures are especially important.

61 Humans aren’t computers anyway Humans start storing experiences automatically, but need repetition to learn. Humans start storing experiences automatically, but need repetition to learn. (Computers store on command, and only need one command.) (Computers store on command, and only need one command.) Humans can’t very well avoid learning what they experience over and over. Again, frequency counts are a useful index of likelihood of being established. Humans can’t very well avoid learning what they experience over and over. Again, frequency counts are a useful index of likelihood of being established. Whether or not a structure is (ir)regular or (un)predictable is a much less useful indicator. Whether or not a structure is (ir)regular or (un)predictable is a much less useful indicator.

62 What difference does all this make? So what? What does all this have to do with linguistics? So what? What does all this have to do with linguistics? I would like to suggest 6 maxims having to do with this difference between learning a pattern and calculating it (producing it by rule). They contradict much of the received wisdom of traditional linguistics. I would like to suggest 6 maxims having to do with this difference between learning a pattern and calculating it (producing it by rule). They contradict much of the received wisdom of traditional linguistics. They bear especially on the “modular” architecture of many models. They bear especially on the “modular” architecture of many models. They affect phonology, semantics, lexicon, and grammar alike. They affect phonology, semantics, lexicon, and grammar alike.

63 Background for the maxims The maxims generally take the form: “You can’t assume 100% computation and 0% storage, or verce visa. It is an empirical question how much of each.” The maxims generally take the form: “You can’t assume 100% computation and 0% storage, or verce visa. It is an empirical question how much of each.” I won’t question that what is unpredictable yet known must have been learned. I won’t question that what is unpredictable yet known must have been learned. But I do question the assumption that what is predictable or can be produced by rule therefore is not learned. But I do question the assumption that what is predictable or can be produced by rule therefore is not learned.

64 Background for the maxims Many cognitive scientists have concluded that humans (in comparison with current digital computers) vastly maximize storage (with sophisticated retrieval) and minimize computation. Many cognitive scientists have concluded that humans (in comparison with current digital computers) vastly maximize storage (with sophisticated retrieval) and minimize computation. I.e., generally, we learn more than we need to, not less. Experts are those that have learned more, not that can figure things faster. I.e., generally, we learn more than we need to, not less. Experts are those that have learned more, not that can figure things faster. Our cognitive system has lots of redundancy. Our cognitive system has lots of redundancy. So (surprise surprise) does language. So (surprise surprise) does language.

65 Maxim #1 Frequently linguists have argued that some member(s) of Category X are computed (=predictable=produced by rule), or, as the case might be, irregular (=unpredictable =learned=in the lexicon). Frequently linguists have argued that some member(s) of Category X are computed (=predictable=produced by rule), or, as the case might be, irregular (=unpredictable =learned=in the lexicon). They then conclude that all members of Category X are treated the same way. They then conclude that all members of Category X are treated the same way.

66 Maxim #1 E.g. Chomsky (1967 – Lexicalist Hypothesis): E.g. Chomsky (1967 – Lexicalist Hypothesis): Derived nominals are IRREGULAR. (cites exx.) “A lexical treatment of DN’s is the natural way to capture this irregular behavior.” Derived nominals are IRREGULAR. (cites exx.) “A lexical treatment of DN’s is the natural way to capture this irregular behavior.” Crucial assumption: if some DN’s (the exx. cited) are lexical, all are. Crucial assumption: if some DN’s (the exx. cited) are lexical, all are.

67 Maxim #1 CG denies this gratuitous assumption. Rather CG denies this gratuitous assumption. Rather Showing that one member of a class is learned or computed does not show that all members of the class are treated the same way. Showing that one member of a class is learned or computed does not show that all members of the class are treated the same way. I.e. I.e. What happens to one form doesn’t have to happen to all of them.

68 Maxim #1 What happens to one form doesn’t have to happen to all of them. Think of –er nominalizations. Are they lexical? Novel ones like flinger or gulper are presumably produced by rule. Others are clearly learned. Think of –er nominalizations. Are they lexical? Novel ones like flinger or gulper are presumably produced by rule. Others are clearly learned. flinger < screamer < swimmer < reader < computer < propeller < rocker < ruler < drawer flinger < screamer < swimmer < reader < computer < propeller < rocker < ruler < drawer So, are –er nominalizations learned, or produced by rule? Answer: It depends. So, are –er nominalizations learned, or produced by rule? Answer: It depends.

69 Maxim #1 What happens to one form doesn’t have to happen to all of them. flinger < screamer < swimmer < reader < computer < propeller < rocker < ruler < drawer flinger < screamer < swimmer < reader < computer < propeller < rocker < ruler < drawer Some forms are well-learnt and well-established, others may be novel and only allowed because sanctioned by the rule. This is a more realistic model. Some forms are well-learnt and well-established, others may be novel and only allowed because sanctioned by the rule. This is a more realistic model.

70 Maxim #1 What happens to one form doesn’t have to happen to all of them. Some forms are computed, some are learned and retrieved from memory. You will have to check each case: it is an empirical issue. Some forms are computed, some are learned and retrieved from memory. You will have to check each case: it is an empirical issue. Objection: This is redundant: it violates simplicity. Why should we posit that people learn things when there’s a perfectly good way to figure them? Objection: This is redundant: it violates simplicity. Why should we posit that people learn things when there’s a perfectly good way to figure them? Answer: It is good that the model is redun- dant— that is true to the cognitive reality. Answer: It is good that the model is redun- dant— that is true to the cognitive reality.

71 Maxim #1 What happens to one form doesn’t have to happen to all of them. Arguing otherwise is like arguing that a computer can’t have on its hard disk information that could be calculated by a program, because that would be redundant. Arguing otherwise is like arguing that a computer can’t have on its hard disk information that could be calculated by a program, because that would be redundant. Whether or not it’s redundant, it happens. Whether or not it’s redundant, it happens. Restating: Restating: It is ultimately an empirical issue whether a particular linguistic form is stored in language speakers’ minds or whether it is computed from other information. It is ultimately an empirical issue whether a particular linguistic form is stored in language speakers’ minds or whether it is computed from other information.

72 Maxim #1 What happens to one form doesn’t have to happen to all of them. Saying that it is an empirical issue doesn’t mean there is necessarily any easy empirical test to let you know. Saying that it is an empirical issue doesn’t mean there is necessarily any easy empirical test to let you know. It does mean that in principle it could be either way, and you must examine relevant data to settle the question in a given case. It does mean that in principle it could be either way, and you must examine relevant data to settle the question in a given case.

73 Maxim #2 Chomsky 1965 (and almost everybody else): Linguistic theory is concerned primarily with an ideal speaker- listener, in a completely homogenous speech-community, who knows its language perfectly, and is unaffected by such grammatically irrelevant conditions as memory limitations, distractions, shifts of attention and interest, and errors (random or characteristic) in applying his knowledge of the language in actual performance. Linguistic theory is concerned primarily with an ideal speaker- listener, in a completely homogenous speech-community, who knows its language perfectly, and is unaffected by such grammatically irrelevant conditions as memory limitations, distractions, shifts of attention and interest, and errors (random or characteristic) in applying his knowledge of the language in actual performance. “Primarily” = in practice, “only”; “grammatically irrelevant” begs important questions. “Primarily” = in practice, “only”; “grammatically irrelevant” begs important questions. Speech communities are not homogenous, however: far from it. And this fact is relevant. Speech communities are not homogenous, however: far from it. And this fact is relevant.

74 Maxim #2 Some speakers’ computing or learning a form doesn’t necessarily mean all speakers do it. Some speakers’ computing or learning a form doesn’t necessarily mean all speakers do it. Your doing it doesn’t mean everybody else has to.

75 Maxim #2 Your doing it doesn’t mean everybody else has to. Shifting from second to third gear may be perfectly automatic for one person, and require considerable thought and calculation for another. Shifting from second to third gear may be perfectly automatic for one person, and require considerable thought and calculation for another. For a friend “that was all she wrote” was a clichéd, dead metaphor he pulled off the shelf. For me it was brand new, made me laugh out loud. For a friend “that was all she wrote” was a clichéd, dead metaphor he pulled off the shelf. For me it was brand new, made me laugh out loud.

76 Maxim #2 Your doing it doesn’t mean everybody else has to. Relatedly, one type of computation by one speaker doesn’t guarantee the same computation by another: Relatedly, one type of computation by one speaker doesn’t guarantee the same computation by another: Un[[believabl]y] vs. un[[believe]ably] vs. [unbelief]able]y], vs. [unbelievable]y, etc. Un[[believabl]y] vs. un[[believe]ably] vs. [unbelief]able]y], vs. [unbelievable]y, etc. hangman = V + O (guy who hangs a man) or V + S (man who hangs people) hangman = V + O (guy who hangs a man) or V + S (man who hangs people) Like calculating 8 x 9 in different ways: who cares how you did it? The result is the same (near enough). Like calculating 8 x 9 in different ways: who cares how you did it? The result is the same (near enough).

77 Maxim #2 Your doing it doesn’t mean everybody else has to. Restating: Restating: It is ultimately an empirical issue whether a particular form is learned by a particular individual speaker, or whether he (or she) computes it in one way or another. It is ultimately an empirical issue whether a particular form is learned by a particular individual speaker, or whether he (or she) computes it in one way or another.

78 Maxim #3 Most of us have had the experience of “tumbling to” an analysis of something that had previously been monomorphemic to us. Most of us have had the experience of “tumbling to” an analysis of something that had previously been monomorphemic to us. E.g. rue + th = ruth(less) vile + th = filth like true + th = truth heal + th = health E.g. rue + th = ruth(less) vile + th = filth like true + th = truth heal + th = health Similarly, derivedness can fade. Awesome used to be more saliently awe + some for me. Similarly, derivedness can fade. Awesome used to be more saliently awe + some for me. Moral: what has been exclusively accessed from memory or exclusively computed can start to be processed the other way too. Moral: what has been exclusively accessed from memory or exclusively computed can start to be processed the other way too.

79 Maxim #3 You can change the way you do it. Restating: Restating: It is ultimately an empirical issue whether a particular form that’s always been processed in one way by a particular speaker, will be processed exclusively in that way in the future. It is ultimately an empirical issue whether a particular form that’s always been processed in one way by a particular speaker, will be processed exclusively in that way in the future.

80 Maxim #4 Maxim #4 is in a way the same thing as #3: it just recognizes that you can make such changes as #3 repeatedly. Maxim #4 is in a way the same thing as #3: it just recognizes that you can make such changes as #3 repeatedly. Having computed ru-th or fil-th one time, you very likely won’t bother to run through the computation the next time. Having computed ru-th or fil-th one time, you very likely won’t bother to run through the computation the next time. But you might the time after that. But you might the time after that.

81 Maxim #4 You don’t have to do next time what you did this time. Restating: Restating: It is ultimately an empirical issue how a particular form is processed by a particular speaker on a particular occasion. It is ultimately an empirical issue how a particular form is processed by a particular speaker on a particular occasion.

82 Maxim #5 Nothing stops you from bringing a form up from memory, then checking it by computation. Nothing stops you from bringing a form up from memory, then checking it by computation. Or computing it, then thinking “Yes, that’s right, I remember that”. Or computing it, then thinking “Yes, that’s right, I remember that”. Our minds have enough parallel processing capacity to do both simultaneously. Our minds have enough parallel processing capacity to do both simultaneously.

83 Maxim #5 You can do both at the same time. Restating: Restating: It is ultimately an empirical issue for a particular form, on a particular occasion, whether a particular speaker exclusively calculates it, exclusively retrieves it from storage, or does both in some degree, either sequentially or simultaneously. It is ultimately an empirical issue for a particular form, on a particular occasion, whether a particular speaker exclusively calculates it, exclusively retrieves it from storage, or does both in some degree, either sequentially or simultaneously.

84 Maxim #6 These considerations apply to polysemy as well. These considerations apply to polysemy as well. Some have claimed that certain meanings are always derived from certain others, e.g. that Shakespeare w ‘The literary work(s) written by Shakespeare’, is necessarily accessed via Shakespeare p ‘the person William Shakespeare’. Some have claimed that certain meanings are always derived from certain others, e.g. that Shakespeare w ‘The literary work(s) written by Shakespeare’, is necessarily accessed via Shakespeare p ‘the person William Shakespeare’.

85 Maxim #6 This fits a rule (schema) for naming literary works by their authors. This fits a rule (schema) for naming literary works by their authors.

86 Maxim #6 The same rule can be used productively to let you use a name such as Harry Smith to refer to what Harry Smith wrote. The same rule can be used productively to let you use a name such as Harry Smith to refer to what Harry Smith wrote.

87 Maxim #6 You might say that Shakespeare (as opposed to Harry Smith) is lexically marked to undergo this particular kind of metonymic extension; You might say that Shakespeare (as opposed to Harry Smith) is lexically marked to undergo this particular kind of metonymic extension; The extended meaning Shakespeare w then need not itself be learned, and listed in the lexicon. The extended meaning Shakespeare w then need not itself be learned, and listed in the lexicon.

88 Maxim #6 CG’s position on this should, by now, be no surprise. You can do it either way. CG’s position on this should, by now, be no surprise. You can do it either way. You can access Shakespeare w through Shakespeare p. You can access Shakespeare w through Shakespeare p.

89 Maxim #6 However, Shakespeare w can also become established in its own right and so linked that you can also access it directly. However, Shakespeare w can also become established in its own right and so linked that you can also access it directly. So what if it’s redundant; it happens. So what if it’s redundant; it happens.

90 Maxim #6 You can go the long way to get to a meaning or go to it directly. Restating: Restating: It is ultimately an empirical issue whether a meaning is activated only as a result of a computational process starting with another meaning, or activated directly, or both. It is ultimately an empirical issue whether a meaning is activated only as a result of a computational process starting with another meaning, or activated directly, or both. (for a particular meaning in the mind of a particular speaker on a particular occasion) (for a particular meaning in the mind of a particular speaker on a particular occasion)

91 The import of the Maxims These Maxims have obvious applications to the way the lexicon is conceived, but also to phonology, syntax, and semantics. These Maxims have obvious applications to the way the lexicon is conceived, but also to phonology, syntax, and semantics. If CG is right on these points, the architecture of language must look rather different than what many other theories have portrayed it to be. If CG is right on these points, the architecture of language must look rather different than what many other theories have portrayed it to be. We will zip past a few ways it affects things. We will zip past a few ways it affects things.

92 The import of the Maxims: the Lexicon-Grammar distinction Obviously, it is not going to be possible to simply state, of many classes of structures or of many particular structures, “These are part of the lexicon, not part of the grammar”, and act as if that ended the matter. Obviously, it is not going to be possible to simply state, of many classes of structures or of many particular structures, “These are part of the lexicon, not part of the grammar”, and act as if that ended the matter. By the same token, you won’t be able to say “These are always produced by the grammar, and not learned.” By the same token, you won’t be able to say “These are always produced by the grammar, and not learned.” Lots of structures will be in-between, or oscillating between, in various ways. Lots of structures will be in-between, or oscillating between, in various ways.

93 The import of the Maxims: the Lexicon-Grammar distinction You will be a lot better off if your theory doesn’t make that mean that they are drastically changing their nature and functions each time they cross from one category to the other. You will be a lot better off if your theory doesn’t make that mean that they are drastically changing their nature and functions each time they cross from one category to the other.

94 The import of the Maxims: the Lexicon-Grammar distinction You will be a lot better off if your theory doesn’t make that mean that they are drastically changing their nature and functions each time they cross from one category to the other. You will be a lot better off if your theory doesn’t make that mean that they are drastically changing their nature and functions each time they cross from one category to the other.

95 The import of the Maxims: the Lexicon-Grammar distinction This assumes, of course, that Lexicon is defined as the repository of what is learned & not produced by rule. It is also true under all other definitions of the lexicon I know. This assumes, of course, that Lexicon is defined as the repository of what is learned & not produced by rule. It is also true under all other definitions of the lexicon I know. For me, the lexicon is most usefully viewed as the set of structures clearly learned in fully detailed form (at least with all their phonemes specified.) For me, the lexicon is most usefully viewed as the set of structures clearly learned in fully detailed form (at least with all their phonemes specified.) You may (if you wish) add “relatively simple in their morphemic structure.” You may (if you wish) add “relatively simple in their morphemic structure.”

96 The import of the Maxims: the Lexicon-Grammar distinction All these parameters (learnedness, schematicity, complexity) are matters of degree. All these parameters (learnedness, schematicity, complexity) are matters of degree. In this way, the lexicon differs only in degree from the grammar, and from what is not (yet) part of the language. In this way, the lexicon differs only in degree from the grammar, and from what is not (yet) part of the language.

97 The import of the Maxims: the Lexicon-Grammar distinction Like this: Like this:

98 The import of the Maxims: the Lexicon-Grammar distinction Salty would be clearly lexical for most English speakers, vinegary is less so because it is not as thoroughly learnt, may be learnt by some but not others, etc. Salty would be clearly lexical for most English speakers, vinegary is less so because it is not as thoroughly learnt, may be learnt by some but not others, etc. FOOD-y would be less lexical because part of it is too schematic (its phonemes are not specified.) FOOD-y would be less lexical because part of it is too schematic (its phonemes are not specified.) N-Adjr would be even less so, and more clearly part of the “grammar”. N-Adjr would be even less so, and more clearly part of the “grammar”. But they should all be basically the same sort of structure. (CG describes them so.) But they should all be basically the same sort of structure. (CG describes them so.)

99 The import of the Maxims: Conventional expressions (Langacker 1987) (Langacker 1987) “This dichotomous perspective [of syntax vs. lexicon] made it inevitable that a large body of data belonging to neither category would be mostly ignored. I refer here to the huge set of stock phrases, familiar collocations, formulaic expressions, and standard usages that can be found in any language and thoroughly permeate its use. … “This dichotomous perspective [of syntax vs. lexicon] made it inevitable that a large body of data belonging to neither category would be mostly ignored. I refer here to the huge set of stock phrases, familiar collocations, formulaic expressions, and standard usages that can be found in any language and thoroughly permeate its use. …

100 The import of the Maxims: Conventional expressions “This is why a seemingly perfect knowledge of the grammar of a language (in the narrow sense) does not guarantee fluency in it; learning its full complement of conventional expressions is probably by far the largest task involved in mastering it. “This is why a seemingly perfect knowledge of the grammar of a language (in the narrow sense) does not guarantee fluency in it; learning its full complement of conventional expressions is probably by far the largest task involved in mastering it.

101 The import of the Maxims: the Lexicon-Grammar distinction “Yet conventional expressions have received so little attention that I found it necessary to invent this term for the class as a whole. … The grammar [i.e. the linguistic description] of a language is responsible for listing its full set of conventional expressions (such as go for a walk, absolutely incredible, have a good time, … cheap imitation, the seconds are ticking away, and so on, and so on). To furnish such a list would obviously be a vast undertaking, for there are many thousands of such expressions, and new ones are always forming. … “Yet conventional expressions have received so little attention that I found it necessary to invent this term for the class as a whole. … The grammar [i.e. the linguistic description] of a language is responsible for listing its full set of conventional expressions (such as go for a walk, absolutely incredible, have a good time, … cheap imitation, the seconds are ticking away, and so on, and so on). To furnish such a list would obviously be a vast undertaking, for there are many thousands of such expressions, and new ones are always forming. …

102 The import of the Maxims: the Lexicon-Grammar distinction “The issue of whether conventional expressions should be included in a grammar is factual rather than methodological in a framework taking seriously the goal of psychological reality in linguistic description. If a speaker does in fact learn a large set of conventional expressions as fixed units, it is incumbent on the grammar to represent this fact by providing an inventory of these expressions. “The issue of whether conventional expressions should be included in a grammar is factual rather than methodological in a framework taking seriously the goal of psychological reality in linguistic description. If a speaker does in fact learn a large set of conventional expressions as fixed units, it is incumbent on the grammar to represent this fact by providing an inventory of these expressions.

103 The import of the Maxims: the Lexicon-Grammar distinction “The simplest description that accurately accommodates all the data must by definition include such a list.*” —Langacker 1987:35-36, 41 “The simplest description that accurately accommodates all the data must by definition include such a list.*” —Langacker 1987:35-36, 41 [*Footnote*: With apologies to Sapir, we can say that not only do all grammars leak, they also list (massively).] [*Footnote*: With apologies to Sapir, we can say that not only do all grammars leak, they also list (massively).]

104 The import of the Maxims: Phonology An obvious application to phonology is that all common rule-governed forms will tend to be learned (stored). An obvious application to phonology is that all common rule-governed forms will tend to be learned (stored). A “rule” may tell you that the v of liv ‘leaf’ devoices word-final. This does not mean that you don’t learn livz ‘leaves’, livd ‘leaved’, and lif ‘leaf’, in their own right. A “rule” may tell you that the v of liv ‘leaf’ devoices word-final. This does not mean that you don’t learn livz ‘leaves’, livd ‘leaved’, and lif ‘leaf’, in their own right.

105 The import of the Maxims: Phonology “Suppletion” thus overlaps massively with rule-governed phonology, and often proves decisive in language change. “Suppletion” thus overlaps massively with rule-governed phonology, and often proves decisive in language change. E.g. people might (and in fact some do) start saying lifs ‘leaves’, or lift ‘leaved’ using the salient singular form as “basic” and recomputing the others, directly contradicting the rule. E.g. people might (and in fact some do) start saying lifs ‘leaves’, or lift ‘leaved’ using the salient singular form as “basic” and recomputing the others, directly contradicting the rule. (Phonological systems empirically don’t always change the ways the rules would lead you to expect. This is one reason why.) (Phonological systems empirically don’t always change the ways the rules would lead you to expect. This is one reason why.)

106 The import of the Maxims: Semantics vs. Pragmatics One of the major criteria linguists seem to use to decide what is “pragmatic” as opposed to “semantic” is whether something is (in some degree) predictable (especially predictable from the context.) One of the major criteria linguists seem to use to decide what is “pragmatic” as opposed to “semantic” is whether something is (in some degree) predictable (especially predictable from the context.)

107 The import of the Maxims: Semantics vs. Pragmatics E.g. the meaning Shakespeare w ‘Shakespeare’s works’, is a pragmatic extension (because it’s predictable) of the ‘real’ meaning Shakespeare p ‘the person William Shakespeare’. E.g. the meaning Shakespeare w ‘Shakespeare’s works’, is a pragmatic extension (because it’s predictable) of the ‘real’ meaning Shakespeare p ‘the person William Shakespeare’.

108 The import of the Maxims: Semantics vs. Pragmatics As already argued, nothing stops both meanings being learned, conventionally associated with the phonological form ˈʃ ejkspir, and thus ‘real’ meanings. As already argued, nothing stops both meanings being learned, conventionally associated with the phonological form ˈʃ ejkspir, and thus ‘real’ meanings.

109 The import of the Maxims: Semantics vs. Pragmatics “Semantics is conventionalized pragmatics”. “Semantics is conventionalized pragmatics”. A lot more gets conventionalized (learned and known to have been learned by all the relevant speakers) than might seem strictly necessary. A lot more gets conventionalized (learned and known to have been learned by all the relevant speakers) than might seem strictly necessary. A lot of what is presented as pragmatics is in fact semantic. A lot of what is presented as pragmatics is in fact semantic.

110 Summary It has traditionally been assumed in linguistics that what is regular, systematic and predictable is not learned but rather produced by rule, while what is irregular, idiosyncratic and arbitrary is learned. It has traditionally been assumed in linguistics that what is regular, systematic and predictable is not learned but rather produced by rule, while what is irregular, idiosyncratic and arbitrary is learned.

111 Summary It is normally assumed as well that these distinctions are binary and coincide with each other so exactly as to be practically equivalent. It is normally assumed as well that these distinctions are binary and coincide with each other so exactly as to be practically equivalent. Important aspects of the architecture of many theoretical models depend on these assumptions, notably the modular distinction between lexicon (where the irregular, idiosyncratic, arbitrary and learned structures reside) and grammar (the domain of rules for producing the unlearned, regular, systematic, and predictable phenomena of language). Important aspects of the architecture of many theoretical models depend on these assumptions, notably the modular distinction between lexicon (where the irregular, idiosyncratic, arbitrary and learned structures reside) and grammar (the domain of rules for producing the unlearned, regular, systematic, and predictable phenomena of language).

112 Summary CG maintains, on the contrary, that the distinctions are all gradual rather than binary, and that they do not coincide exactly. In particular, much that is regular, systematic and in some degree predictable may nevertheless be learned. CG maintains, on the contrary, that the distinctions are all gradual rather than binary, and that they do not coincide exactly. In particular, much that is regular, systematic and in some degree predictable may nevertheless be learned. This has important implications for the structure of the CG framework, notably for the ways lexicon and other aspects of grammar grade into each other. This has important implications for the structure of the CG framework, notably for the ways lexicon and other aspects of grammar grade into each other.

113 Summary If CG is right on these points, the architecture of language must look rather different than what many other theories have portrayed it to be. If CG is right on these points, the architecture of language must look rather different than what many other theories have portrayed it to be.

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