Hannah BarrantesLEGAL LOGIC AND TECHNIQUE In general, the subject Legal Technique and logic has been helpful in determining the right questions to be asked in examining and studying cases, as well as the relevance of both the dissenting and concurring statements of judges in decisions. It made the study, not only fluid, but have also shown the sense and rationale why lawyers should at all times think on their feet.

Logic is not just mere philosophy, it also entails aspects mimicking other fields of knowledge and organizing thoughts for greater studies or systems of thought. Below are the different forms of logic, its aspects, and how necessarily it helped me reach the conclusion of Law as a system, trial as a mean to interpret the law and show its different perspectives, and its application to Legal Cases.

LOGIC AS SCIENCE

Some people are profoundly disturbed by the fact that reason alone can't generate truths. When the use of mathematics and logic in science is explained to them they respond, "If mathematics and logic can't produce absolute truths, then they produce only untruths or partial truths, and are therefore worthless." This sentence is itself an example of nonsense clothed in the appearance of logic.It must be admitted at the outset that science is not in the business of finding absolute truths. Science proceeds as if there are no absolute truths, or if there are such truths, we can never know what they are; as the pre-Socratic skeptics observed: If we were to stumble upon an absolute truth, we'd have no way to be certain it is an absolute truth. The models and theories of science are approximations to naturenever perfect. But in most cases we know rather well how good they are. We can state quantitatively the limits of uncertainty of numeric results, and their range of applicability. Yet there's always the possibility that we may find exceptions to one of our accepted laws, or may even find alternative theories that do a better job than older ones.

Some critics of science attack this process of science, on the grounds that it cannot produce absolute truths. Theirs is a black/white view of the scientific process. Never mind that they have not proposed any other process that is capable of producing anything near the power and comprehensiveness of present science. They say that "Theory X" isn't perfect therefore it is "wrong".

The results and predictions of a theory, being well tested, will not crumble if the theory is someday modified, drastically changed, or even replaced with another theory. The results or predictions of a theory are not all suddenly rendered "wrong" when a theory is modified or replaced. These results and predictions may be improved in precision or scope. Sometimes the predictions of a new theory have greater scope than the old one, predicting things the old one didn't (and things that we never had observed or tested before). Very often a new theory is sought because the old one, while its predictions were mostly correct, predicted a few things that just weren't confirmed by good experiments. We'll need to say more about this later.

The fact that science claims no absolute truths is seized upon by people who hold strong religious beliefs and who dislike those conclusions of science that run counter to their emotional convictions. To them, if a thing is not absolutely and finally true, it is false, and therefore the methods used to formulate it must be flawed.

The futility of searching for absolutes.

Though the philosophers of ancient Greece developed formal logic, and got a good start toward mathematics, they realized the limitations of logic and the futility of seeking absolutes. Here are a few comments about this dilemma.

Only one thing is certainthat is, nothing is certain. If this statement is true, it is also false.Ancient paradoxThe gods did not reveal from the beginningAll things to us; but in the course of timeThrough seeking, men found that which is better.But as for certain truth, no man has known it,Nor will he know it; neither of the gods,Nor yet of all the things of which I speak.And even if by chance he were to utterThe final truth, he would himself not know it;For all is but a woven web of guesses.

Xenophanes (c. 570-c. 480 BCE) Greek philosopher.We know nothing in reality; for truth lies in an abyss.Democritus, (c. 420 BCE) Greek philosopher.None of us knows anything, not even whether we know or do not know, nor do we know whether not knowing and knowing exist, nor in general whether there is anything or not.Metrodorus of Chios (c. 4th century BCE) Greek philosopherThis only is certain, that there is nothing certain; and nothing more miserable and yet more arrogant than man.Pliny ("The Elder") (23-79) Roman naturalist. (Gaius Plinius Secundus).All we know of the truth is that the absolute truth, such as it is, is beyond our reach.Nicholas of Cusa (1401-64) German cardinal, mathematician, philosopher. De Docta Ignorantia (Learned Ignorance)

These folks who made these skeptical comments are not saying that "We can't know anything, so why bother?" They are saying that we can't "know" in the absolute sense, that we have no way to know if there are any absolute truths, and we wouldn't be able to prove the absoluteness of an absolute truth if we accidentally stumbled on one. Today we express it differently: "Science describes nature, it does not explain." Science attempts to answer "how" questions, but not "why" questions.

Science has progressed by rejecting much of its past history, past practices and past theory. Though the sciences arose from a muddled mix of mysticism, magic and speculation, scientists eventually realized that those modes of thought were prone to error and simply not productive. So chemists reject the theories of the alchemists, astronomers reject the theory underlying astrology. Mathematicians reject the number-mysticism of the Pythagoreans. Physicists, when they bother to think about their discipline's roots, acknowledge the pre-scientific contributions of the ancient Greeks in mathematics, Democritus' view that nature is lawful, and also their attitude of seeking knowledge for its own sake. But they are embarrassed by the Greek teachings about physics, for most of these have all been consigned to the trash-heap of history.

Even those early ideas that happened to be in harmony with our present views seem based upon faulty methodology or were simply speculation. Sometimes a few of those guesses seemed surprisingly close to our modern views, at least superficially. But when examined in detail the similarity breaks down. Democritus' atomic theory, for example, was based on no hard evidence, had no historical connection with modern atomic theory, and its details bore no resemblance to what we now know about atoms. Once in a while, if you speculate wildly enough, you get lucky. Too many textbooks make a "big deal" out of such accidental similarities.

Scientific method

So, how does science arrive at its results? Some people speak of the "scientific method" as a set of "rules" for doing science. Too often such rules are presented in schools as a "recipe" for doing science, and even have numbered steps! That's misleading. At the other extreme, someone said that scientific method is "Doing one's damndest with one's mind." I know many have said better things about it, but here's some observations on scientific method.How Science really works.

Even casual observation shows us that nature, as perceived by our senses, has reliable regularities and patterns of behavior.Through more precise and detailed study we found that many of these regularities can be modeled, often with mathematical models of great precision.

Sometimes these models break down when extended (extrapolated) beyond their original scope of validity. Sometimes extrapolation of a model beyond its original scope actually works. This warns us that we had better rigorously test each model for validity, and these tests should be capable of exposing any flaws in the modelflaws capable of demonstrating that the model isn't true.

Even when a model survives such testing, we should only grant it "provisional" acceptance, because cleverer people with more sophisticated measuring techniques may in the future expose some other deficiencies of the model.

When models are found to be incomplete or deficient, we often fix them by tweaking their details till they work well enough to agree with observations.

When rapid advances in experimental observations occur, a model may be found so seriously inadequate to accommodate the new data that we may scrap a large part of it and start over with a new model. Relativity and quantum mechanics are historical examples. These situations are often called "scientific revolutions."

When such upheavals occur, and old models are replaced with new ones, that doesn't mean the old ones were totally "wrong", nor does it mean their underlying concepts were invalid. They still work within their scope of applicability. Newton's physics wasn't suddenly wrong, nor were its predictions found unreliable or incorrect when we adopted Einstein's relativity. Relativity had greater scope than Newtonian physics, but it also rested on a different conceptual basis.

Past experience has shown that mathematical models of nature have tremendous advantages over the earlier, more appealing, models which used analogies to familiar everyday phenomena of our direct sensory experience. Mathematical models are less burdened with emotional baggage, being "pure" and abstract. Mathematics provides seemingly infinite adaptability and flexibility as a modeling structure. If a some natural phenomena can't be modeled by known mathematics, we invent new forms of mathematics to deal with them.

The history of science has been a process of finding successful descriptive models of nature. First we found the easy ones. As science progressed, scientists were forced to tackle the more subtle and difficult problems. So powerful are our models by now that we often delude ourselves into thinking that we must be very clever to have been able to figure out how nature "really" works. We may even imagine that we have achieved "understanding". But on sober reflection we realize that we have simply devised a more sophisticated and detailed description.

Whatever models or theories we use, they usually include some details or concepts that do not relate directly to observed or measurable aspects of nature. If the theory is successful we may think that these details are matched in nature, and are "real" even though they are not experimentally verifiable. Their reality is supposed to be demonstrated by the fact that the theory "works" to predict things we can verify and continue to verify. This is not necessarily so. Scientists often speak of energy, momentum, wave functions and force fields as if they were on the same status as objects of everyday experience such as rocks, trees and water. In a practical sense (for getting answers) this may not matter. But on another level, a change of scientific model may do away with a force field as an conceptual entity, but it wouldn't do away with a forest, mountain or lake.

Science progresses through trial and error, mostly error. Every new theory or law must be skeptically and rigorously tested before acceptance. Most fail, and are swept under the rug, even before publication. Others, like the luminiferous ether, flourish for a while, then their inadequacies accumulate till they are intolerable, and are quietly abandoned when something better comes along. Such mistakes will be found out. There's always someone who will delight in exposing them. Science progresses by making mistakes, correcting the mistakes, then moving on to other matters. If we stopped making mistakes, scientific progress would stop.

What do scientists really think about 'reality'?

Scientists speak in a language that uses everyday colloquial words with specialized (and often different) meanings. When a scientist says something has been found to be 'true', what is meant isn't any form of absolute truth. Likewise scientists' use of 'reality' and 'belief' don't imply finality or dogmatism. But if we inquire whether a scientist believes in an underlying reality behind our sense impressions, we are compounding two tricky words into a philosophical question for which we have no way to arrive at a testable answer. I'd be inclined to dismiss the entire question as meaningless, and not waste time discussing it, or any other such questions. Yet a few scientists and philosophers disagree, and wax eloquent in writing and speaking about such questions.

The notion that we can find absolute and final truths is naive, but still appealing to many people, especially non-scientists. If there are any underlying "truths" of nature, our models are at best only close approximations to themuseful descriptions that "work" by correctly predicting nature's behavior. We are not in a position to answer the philosophical question "Are there any absolute truths?" We can't determine whether there is an underlying "reality" to be discovered. And, though our laws and models (theories) become better and better, we have no reason to expect they will ever be perfect. So we have no justification for absolute faith or belief in any of them. They may be replaced someday by something quite different in concept. At least they will be modified. But that won't make the old models "untrue". All this reservation and qualification about truth, reality, and belief, doesn't matter. It isn't relevant to doing science. We can do science quite well without 'answering' these questions, questions that may not have any answers. Science limits itself to more finite questions for which we can arrive at practical answers.

Also, we've learned that not all questions we can ask have answers that we can find. Any question that is in principle or in practice untestable, is not considered a valid scientific question. We like to think that scientists don't waste time on those, but they seem to pop up in discussion and in books quite often. (Many people think unanswerable questions are the most profound and important ones. Questions like "What is the meaning of it all," or "What jump-started the universe?" I think that scientists should set these aside for the philosophers to chew on, and get on with the business of answering more accessible questions.) The First Philosopher, John Holden

Scientists and a Law Student: THE IMPACT OF IT.

Scientists find it nave that there is an absolute truth, that is why like in Science, they always tend to challenge the truth to systematic methods to which every step entails new knowledge to achieve or overcome. In Legal studies, I always thought of the laws language and how necessarily decisions differ from one another. Reviewing the dissenting opinions of Justice Teehankee and our lesson about Logic is a Science, I now conclude that laws, no matter how clear they were, may be viewed in a different perspective through different procedures or system.

LOGIC OF CONCEPTS AND ANALOGICAL MEANING OF CONCEPTS

Logical theory begins with the concept of an argument. An argument, as the word is used in logic and in intellectual contexts generally, is reasoning that has been put into words. When you put your reasoning into words, you produce what logicians call an argument. Simple enough, but for the purposes of logical theory, a more precise definition is needed. Most logic textbooks include a more detailed definition, usually one that sounds much like this:An argument is one or more statements, called premises, offered as a reason to believe that a further statement, called the conclusion, is true, that is, corresponds to reality.

It is true that in some contexts we use the word argument differently, to refer to people angrily yelling at each other, or to people having a heated emotional dispute. But in logic, and in academic and intellectual contexts generally, the word just means one or more premises offered as reasons or as evidence for the truth of a conclusion.

When we listen to an argument, it is sometimes difficult to tell which statements are premises and which statement is the conclusion. This is why the English language contains what logicians call argument indicator words. To tell your audience that you are drawing your conclusion, introduce your statement using a word or phrase such as therefore, in conclusion, thus, consequently, and so on. To indicate a premise, introduce a statement using words such as because, since, for the reason that, and so on. Premise and conclusion indicator words help your audience follow the flow of your reasoning.

Valid, Invalid, and Sound Deductive ArgumentsA deductive argument that succeeds in showing that its conclusion must be true if its premises all are true is called a valid deductive argument. A deductive argument that fails to show that its conclusion must be true if its premises are true is called an invalid deductive argument.Thus a valid argument may be defined as a deductive argument in which it is the case that if the premises are true then the conclusion must be true. An invalid argument may be defined as a deductive argument in which it is not the case that if the premises are true the conclusion must be true.

Both of the following arguments are deductive, because each obviously aims to show that its conclusion must be true if its premises all are true. However, only the first is valid, the second is invalid:

All human beings are mammals.All mammals are warm-blooded.Therefore it must be that all human beings are warm-blooded.All human beings are mammals.All dogs are mammals.Therefore it must be that all human beings are dogs.

Do you see the difference between these two arguments? Again: Not all reasoning is equal. Some reasoning is better than other reasoning.

When logic students first learn the concept of validity, they almost always find one thing extremely puzzling. An argument can be valid even though it has false premises and a false conclusion. Consider the following deductive argument:

All students are millionaires.All millionaires are Buddhists.Therefore all students must be Buddhists.

Although the premises are false, and although the conclusion is false, the argument is valid. It is valid simply because if the premises were to be true then the conclusion would have to be true as well. The argument fits the definition of a valid argument. Does this seem puzzling to you? The premises are false, and yet the argument is perfectly valid! This shows that true premises are not required for validity. In logic, valid does not mean true. An argument is valid as long as it is the case that if the premises are true then the conclusion must be true. True premises are not required.

However, validity is not all we want in a deductive argument. We normally also want truth. If an argument is valid, and in addition its premises are all true, then the argument is called a sound argument. Thus, a sound argument has two characteristics:All of its premises are true.It is valid.Since truthcorrespondence with realityis the ultimate goal of reasoning, soundness is the ultimate goal of deductive argumentation, not mere validity. You know youve made it if your deductive argument is sound as well as valid. The following argument is both valid and sound:

All whales are mammals.All mammals are animals.Therefore it must be that all whales are animals.

The previous argument, about students and Buddhists, was valid, but unsound.

Strong, Weak, and Cogent Inductive Arguments

An inductive argument that succeeds in showing that its conclusion is probably (but not certainly) true if its premises are true is called a strong inductive argument. An inductive argument that fails to show that its conclusion is probably (but not certainly) true if its premises are true is called a weak inductive argument.

Thus a strong argument may be defined as an inductive argument in which it is the case that if the premises are true then the conclusion is probably true. A weak argument may be defined as an inductive argument in which it is not the case that if the premises are true then the conclusion is probably true.

Both of the following arguments are inductive, because each aims to show that its conclusion is probably (but not certainly) true. However, the first is strong while the second is weak:In all of recorded history, it has never snowed 6 inches in Dallas in August.Therefore, it probably will not snow 6 inches in Dallas next August.Joe is a member of the Democratic Party.

Some known Communists have been members of the Democratic Party.Therefore Joe is probably a Communist.

Again, not all reasoning is equal. Some acts of reasoning are better than others. Do you agree?Many logic students find this aspect of strength puzzling at first: An inductive argument can be strong even though it has false premises and a false conclusion. Consider the following inductive argument:

For the past six months it has been snowing every day in Dallas, it is below 30 degrees in Dallas, and the sky in Dallas is full of snow clouds. Therefore it will probably snow in Dallas today.

Although the premise is false, and although the conclusion is false, the argument is strong. It is strong because if the premise were to be true then the conclusion would probably be true as well: If the premise is true, then the conclusion is likely to be true although not certain. The argument fits the definition of a strong argument!But strength is not all we want in an inductive argument. We normally also want truth. If an argument is strong, and in addition its premises are all true, then the argument is called a cogent argument. Thus, a cogent inductive argument has two properties:All of its premises are true.It is strong.Since truth is the ultimate goal of reasoning, cogency is the ultimate goal of inductive argumentation. The following argument is both strong and cogent:

Most cars burn gasoline. The Presidential Limousine is a car.Therefore, the Presidential Limousine probably burns gasoline. The earlier argument, about Dallas and snow, was strong but not cogent.

Consistency, Implication, and EquivalenceWe have been using our faculty of reason to judge deductive arguments as valid or invalid and to assess the strength of inductive arguments, but we also use reason when we decide whether or not two of our beliefs stand in logical conflict and when we look for certain logical relations among our beliefs. For this reason, logical theory also studies the logical relationships that exist between declarative statements and the logical properties of statements. Four terms are especially important: consistency, inconsistency, implication, and equivalence. Here are the first two definitions:

Two statements are consistent if and only if it is possible both are trueTwo statements are inconsistent if and only if it is not possible both are true.For example, the following statements, given their standard meanings, are consistent:Sue is 33 years old.Sue is an accountant.And the following statements, given their standard meanings, are inconsistent:Sue is 33 years old.Sue is a teenager.

Next:

One statement implies a second statement if and only if it is not possible that the first statement is true and the second statement is false.In other words, a statement P implies a statement Q when and only when it is the case that if P is true then Q is true. For example, in the following case, the first sentence implies the second:Sam is 33 years old.Sam is older than 21.

However, in the next case, the first sentence does not imply the second:

Sam is a Republican.Sam is a millionaire.Next:

Two statements P and Q are equivalent if and only if P implies Q and Q implies P.In other words, two statements are equivalent when and only when it is not possible that they differ as to truth and falsity: if one is true then the other is true and if one is false then the other is false. In the following case, the two statements are logically equivalent.Ann is taller than Bob.Bob is shorter than Ann.But these two statements are not equivalent:Ann is older than Bob.Bob is 33 years old.

Necessity and Contingency

We also use our faculty of reason when we decide whether a statement is necessary or contingent, and logic is concerned to define the relevant terminology so that our thinking can be as clear as possible on this matter as well. Four additional terms are important: necessary truth, necessary falsehood, contingent truth, contingent falsehood. Here are the definitions:A statement is necessarily true if it is true and it cannot possibly be false.

In other words, it is true in all possible circumstances, there are no possible circumstances in which it would be false. For the purposes of logical theory, a possible circumstance is defined as any circumstance whose description is not self-contradictory. This is the broadest concept of possibility humanly and consistently conceivable.

A statement is necessarily false if it is false and it cannot possibly be true.In other words, it is false in all possible circumstances, there are no possible circumstances in which it would be true.For example, the following statements, given their standard meanings of course, are all necessarily true:

All triangles have three sides.The derivative of a constant is zero.The number 3 is greater than the number 2.Given their standard meanings, the following statements are necessarily false:All triangles have 9 sides.1 + 1 = 5.The number 12 is less than the number 3.

Next:

A statement is contingently true if it is true but there are possible circumstances in which it would be false.In other words, it is true but it might have been false if circumstances had been sufficiently different.A statement is contingently false if it is false but there are possible circumstances in which it would be true.In other words, it is false but it might have been true if circumstances had been sufficiently different.Examples of contingent truth would include:

Crosby, Stills, and Nash performed at Woodstock in 1969.It is sunny in Seattle on September 9, 2011.And examples of contingent falsehoods would include:Bob Dylan performed at Woodstock in 1969.Richard Nixon was elected President in 1960.

What concept taught me

Knowing the meaning of concept and its distinction from reality and fantasy taught me to identify sound deductive and inductive reasoning because of the stain of reality that should be present especially in legal arguments.

LANGUAGE AS THE EXPRESSION OF THOUGHT

We should search for the ancestry of language not in prior systems of animal communication but in prior representational systems.' (Bickerton, 1990:23 [emphasis added, JRH])

This quotation makes a negative point and a positive point, given added emphasis above. The idea that language, and by implication much of its current complex structure, arose from pre-linguistic representational systems has attracted attention and not much criticism. A goal of evolutionary linguistics is to explain the origins of the structure found in language. It can be agreed that little of the distinctively complex structure of modern languages can be attributed to ancestry in animal communication systems1. But how much of the complex structure of modern languages can be attributed to ancestry in pre-linguistic representational systems? Sampson (1997) expressed a view opposed to Bickerton's.

` ... it is not plausible that our internal representation of statements, which we use in order to reason and draw inferences in other modes, will map in a simple element-by-element fashion into the words with which we express those statements in speech. ... Nobody really has the least idea what is physically going on in the head when we reason, but I agree that whatever goes on is likely to relate in a fairly abstract way to the words of spoken utterances, which are adapted to the necessary linearity of speech and to the fact that speaker and hearer are working with separate models of reality.' Sampson, 1997:100)

`It is occasionally suggested that language evolved as a medium of internal knowledge representation for use in the computations underlying reasoning. But although there may be a languagelike representational medium -- ``the language of thought,' or ``mentalese'' (Fodor 1975) -- it clearly cannot be English, Japanese, and so on. Natural languages are hopeless for this function: They are needlessly serial, rife with ambiguity (usually harmless in conversational contexts, but unsuited for long-term knowledge representation), complicated by alternations that are relevant only to discourse (e.g. topicalization), and cluttered with devices (such as phonology and much of morphology) that make no contribution to reasoning.' (Pinker & Bloom, 1990:714)

Much of the structure of language has no role in a system for the internal representation of thought.Much of the structure of language has a role in systems for the external expression of thought, which includes communication.A corollary of these propositions, not pursued in detail here, is:

Pressure for effective expression of thought, including communication, may explain much of the structure of language.In the next section, to start this argument, independent characterizations of non-linguistic mental representations and the structure of language are set out. The following sections conduct a survey of the central layers of the structure of any language, its phonology, morphology and syntax, arguing in all cases that the structuring concerned plays no role in the representation of thought, but defines, or constitutes, the mapping of thoughts onto linguistic expressions.

Mental Representation

In a polemic passage, Chomsky (1980:229-230) disparages the idea of communication as the essential function of language, preferring to see language as enabling the expression of thought. I will not quibble over the term `essential' here; I will use `communication' and `expression of thought' interchangeably in this paper, but the latter term has the virtue of highlighting a clear separation between language and thought. Linguistic form, in this view, is something different from thought itself, which is `expressed' in language. Thought which remains unexpressed does not take linguistic form. Much of our thought is of this unexpressed kind, i.e. not in language. Yet unexpressed thought is not formless or contentless, and so one can speak meaningfully of it as a kind of representation.

It is assumed here that the existence of nonlinguistic representations is unproblematic, contrary to the views of a few philosophers (e.g. Stich (1983), Judge (1985), Schiffer (1989), Horst (1996)). Beyond the assumption of their existence, no particularly strong further assumptions are made here about mental representations. For example, the view of nonlinguistic representations taken here is compatible with, but not dependent on, distributed connectionist views of how to code the input to the expression of thought. But the argument pursued here will naturally emphasize dissimilarities between language structure and the structure of nonlinguistic mental representation.

Nonlinguistic mental representations are possessed by animals and prelinguistic infants for remembering and thinking about events in the world. They are derived from extero- and intero-perception, such as perceptions of light, heat, touch, sound, thirst and hunger. Nonlinguistic mental representations are often referred to as constituting the `language of thought' (as in Fodor, 1975) or `mentalese'. The language metaphor, implicit in both Fodor's title and the `-ese' suffix, is attractive because it alludes implicitly to the complex structure of thought. But the language metaphor is also misleading. Fodor's Language of Thought clearly does not have much of the structure of a public language, such as French or Swahili. Indeed, it is exactly the non-language-like features of nonlinguistic mental representations that are at the core of my argument here. The essential differences between an internal (cognitive) representation system and a communication system are as follows.

A communication system maps external forms (such as speech sounds or manual signs), via mental structures, to meanings (where many, if not all, meanings relate to external objects, events or situations). A communication system is typically public, shared by many individuals2.

A representation system lacks the mapping to external forms, and merely provides mental structures which relate to, or denote, external situations. There would be no practical advantage in having a representation system which was not in some way related to the world outside the mind possessing it.

Thus a communication system properly includes a representation system. There are elements in a communication system that are not part of the inherent representation system. Analogously, there are elements in a computer system which relate only to keyboard and screen functions and not to the core business of computation. Any aspects of a communication system which pertain only to the mapping between external forms (i.e. sounds or signs) and the internal cognitive representation system are not part of the representation system per se.

Nonlinguistic mental representations are non-temporal; all parts of the representation of a remembered event are simultaneously present to the mind. Nonlinguistic mental representations are multi-dimensional; for example, they are often diagrammed on paper as networks, with hierarchical relationships between the parts, and/or as composed of features (which can be seen as dimensions). Nonlinguistic mental representations do not exist in the same medium as the external forms to which they are mapped by the structure of a language; specifically, they are non-acoustic and non-manual. With nonlinguistic mental representations, no issue of ambiguity arises; they are what they are (although mental representations may be vague or general).

By contrast, utterances are temporal. Utterances in spoken language are acoustic events, and in sign language, manual events. The raw unprocessed speech signal which reaches the eardrum is a complex sound wave, no more than a temporal sequence of variations in air pressure. The variations are more or less strong surges and declines in pressure, with periods of stillness. At any instant in time, the only information immediately available in this signal is the relative strength of the change in air-pressure, a single (positive or negative) number. At bottom, the whole rich linguistic fabric of an utterance, from phonemic oppositions (e.g. what makes a `b' different from an `s') through syllables, morphemes, words and phrases to clauses and sentences, is signalled by this temporal sequence of air-pressure variations. Thus utterances are linear or one-dimensional sequences of events; any perceived imposition of further dimensions on the signal (e.g. by intonation) arises from knowledge of the mapping between utterances and the nonlinguistic mental representations of their meanings. The term `one-dimensional' emphasizes that the events or `landmarks' in the temporal sequence are distinguished by their values on a single parameter, that of relative pressure. (In sign language, admittedly, some degree of simultaneity is present in the manual signals.) Utterances are frequently ambiguous; as computational linguists know to their cost, ambiguity, especially local ambiguity, is rife in language. Ambiguity arises at all levels of linguistic structure. For instance, the utterance `I'm coming to get you' is ambiguous between a threat and a promise of help; the sentence Visiting relatives can be boring can be understood as describing at least two different situations; the word list, like many other English words, has many senses; phonetically, in English a plosive where voicing commences simultaneously with release can be interpreted as either `voiced', as in beer, or `voiceless', as in spear. These are examples contributing to the many-to-one mapping between nonlinguistic representations and linguistic strings. (In fact, given the existence of synonymy and paraphrase, the overall mapping is many-to-many.) The art of Language

Language in the Study of Law

This is one crucial part because it is now stressed that a lawyer should not just be understood verbally but also through writing which entails a greater work. In examinations, the usual type of questions is essay writing or legal argumentation. When we talked about the Language of Concepts, I already knew after the session how important conceptualization is, clear cut of what you want to prove, before adding sentences to it. Language also has structure and it is important to be intricate in its most basic unit which is the word more than anything else.

CHARACTERISTICS OF REASONING AND FALLACIES

Characteristics of Inductive Reasoning

Observation about what must be true. Inductive reasoning does not use syllogisms, but series of observations, in order to reach a conclusion. The most basic kind of inductive reasoning is called generalization. You generalize whenever you make a general statement (all salesmen are pushy) based on observations with specific members of that group (the last three salesmen who came to my door were pushy). You also generalize when you make an observation about a specific thing based on other specific things that belong to the same group (my girlfriends cousin Ed is a salesman, so he will probably be pushy.) When you use specific observations as the basis of a general conclusion, you are said to be making an inductive leap.

The fallacy most often associated with generalization is hasty generalization, which you commit when you make an inductive leap that is not based on sufficient information. Look at the following five statements and try to determine when the line is crossed. 1) Microsoft is a sexist company. It has over 5,000 employees and not a single one of them is female.

2) Microsoft is a sexist company. I know twenty people who applied for jobs there--ten men and ten women. Though all of them were equally qualified, all of the men got jobs there and none of the women did.

3) Microsoft is a sexist company. I have five female friends who have applied for jobs there, and all of them lost out to less qualified men. Characteristics of Deductive Reasoning

A deductive argument offers two or more assertions that lead automatically to a conclusion. Though they are not always phrased in syllogistic form, deductive arguments can usually be phrased as "syllogisms," or as brief, mathematical statements in which the premises lead inexorably to the conclusion. The following is an example of a sound deductive syllogism: Premise: All dogs have four legs. Premise: Rover is a dog, Conclusion: Rover has four legs. As long as the first two sentences in this argument are true, there can be no doubt that the final statement is correct--it is a matter of mathematical certainty. Deductive arguments are not spoken of as "true" or "false," but as "sound" or "unsound." A sound argument is one in which the premises guarantee the conclusions, and an unsound argument is one in which the premises do not guarantee the conclusions. A deduction can be completely true, yet unsound. It can also be sound, yet demonstrably untrue. Consider the following two arguments: All Southern presidents in this century were Baptists. Jimmy Carter was a Baptist. Jimmy Carter was a Southern president in the 20th century. (True but unsound) All Southern presidents in this century were Republicans. Jimmy Carter was a Southern president in the 20th century. Jimmy Carter was a Republican. (Sound but untrue) The classic syllogism: All men are mortal Socrates is a man Therefore, Socrates is mortal Heres an example of the syllogism in an argument: Laws making marijuana illegal should be repealed. People should have the right to use any substance they wish No laws should prevent citizens from exercising their rights. Anything that promotes prosperity is good. The free-enterprise system is something that promotes prosperity. Therefore, the free-enterprise system is good. Fallacies of Deductive Reasoning Ad Hominem: an argument that attacks an individual's character or behavior rather than the issue at hand. For example, if you argue against gun control because the second amendment entitles US citizens the right to bear arms, and your opponent says that most people who defend the second amendment are ignorant, backwoods fanatics, which are an ad hominem fallacy. Aside from the irrelevance of the personal attack, this example shows that the issue of the second amendment is a threatening premise to the opposition. Oversimplification: supplying neat and easy explanations for large and complicated phenomena. No wonder drug abuse is out of control. Look at how the courts have hobbled police officers. Red Herring: an argument that contains an irrelevant premise in order to divert attention from what is being argued. For example, if you are debating the fuel efficiency of several different makes of car and your opposition introduces the importance of buying domestic vehicles, that is a red herring. The new premise diverts attention away from the issue of fuel efficiency. Non-Sequitur: Literally translated to "It does not follow," this fallacy draws conclusions from premises that do not necessarily apply. For example, "Guns should be outlawed. My neighbor has a gun in his house and he is in favor of euthanasia." This would be a non-sequitur. The two issues are unrelated enough that a conclusion about gun control cannot be drawn from a premise on euthanasia. False Dichotomy: Otherwise known as the "either/or fallacy," this is an argument that makes the assumption that there are only two alternatives available when there may be many more. For instance, "Do we want a defense policy that relies on nuclear annihilation, or do we want one that is geared to reduce global tensions?" This is a false dichotomy because other options may exist. Nevertheless, be wary of arguments in which there really are only two alternatives. Straw Man: an argument that misrepresents the opposition's view by putting it in terms that makes it seem more vulnerable. For example, if someone says, "those people who oppose rapid advances in technology want us to 'go back to the caves,'" it is a straw man fallacy. Someone who opposes rapid advances in technology would not likely claim such a premise.

Begging the Question: an argument containing a premise that is really a restatement of the conclusion. If someone is arguing that marijuana should be legalized, and one of the premises is that "naturally growing plants should not be restricted," that premise is begging the question. These fallacies can be extremely subtle. False Analogy: Arguments often employ analogies, the validity of which must be judged by the analyst. A statement such as, "experimental drugs like the abortion pill should not be distributed to the public; look what happened with Thalidomide" could be a false analogy. The two are different in almost every way except for the inference that they are labeled "experimental." Hasty Generalization: Arguments can contain conclusions that are based on incomplete evidence or unrepresentative samples. Arguments that employ surveys are at risk of this fallacy. If an argument states, "based on a poll taken at the student union, most students eat on campus," the sample may not be representing the students who do not utilize the student union. Be wary of arguments that contain the words "always" or "never." Post Hoc, Ergo Propter Hoc: Literally translated as "after this, therefore because of this, this fallacy occurs when an argument assumes causation based on the succession of time. For instance, someone might claim that since President Clinton entered the Whitehouse, crime in the United States has tripled, implying causation. When analyzed, however, it may be found that, while the statement is true, the two premises are entirely unrelated. False Analogy: the claim of persuasive likeness when no significant likeness exists. Deductive Inferences

When an argument claims that the truth of its premises guarantees the truth of its conclusion, it is said to involve a deductive inference. Deductive reasoning holds to a very high standard of correctness. A deductive inference succeeds only if its premises provide such absolute and complete support for its conclusion that it would be utterly inconsistent to suppose that the premises are true but the conclusion false.

Notice that each argument either meets this standard or else it does not; there is no middle ground. Some deductive arguments are perfect, and if their premises are in fact true, then it follows that their conclusions must also be true, no matter what else may happen to be the case. All other deductive arguments are no good at alltheir conclusions may be false even if their premises are true, and no amount of additional information can help them in the least.

Inductive Inferences

When an argument claims merely that the truth of its premises make it likely or probable that its conclusion is also true, it is said to involve an inductive inference. The standard of correctness for inductive reasoning is much more flexible than that for deduction. An inductive argument succeeds whenever its premises provide some legitimate evidence or support for the truth of its conclusion. Although it is therefore reasonable to accept the truth of that conclusion on these grounds, it would not be completely inconsistent to withhold judgment or even to deny it outright.

Inductive arguments, then, may meet their standard to a greater or to a lesser degree, depending upon the amount of support they supply. No inductive argument is either absolutely perfect or entirely useless, although one may be said to be relatively better or worse than another in the sense that it recommends its conclusion with a higher or lower degree of probability. In such cases, relevant additional information often affects the reliability of an inductive argument by providing other evidence that changes our estimation of the likelihood of the conclusion.

It should be possible to differentiate arguments of these two sorts with some accuracy already. Remember that deductive arguments claim to guarantee their conclusions, while inductive arguments merely recommend theirs. Or ask yourself whether the introduction of any additional informationshort of changing or denying any of the premisescould make the conclusion seem more or less likely; if so, the pattern of reasoning is inductive 2010, PBworks

Fallacies and totality of logic in the persona of the laws

One thing I learned is that logic and fallacies cannot be separated. I have learned that when answering legal conflicts, we should first argue in the logical level, finding fallacies of every arguments or act through logic. After successfully arguing logically, that should only be the time wherein laws will be in the picture.

CONCLUSION

Laws will always be written and are there, but there are different perspective through which a judge tends to judge an act as violation or obedience of the law. Lawyers are there to aid the courts in realigning justice in its most practical sense, and just blabbering about the law is not enough. Systems and operation of Logic should play a part. This is what my paper stands for. The explicit giving of examples and explanation and its direct legal application in a law students life is what makes a logical argument as a technique.