Combining Texts

All the ideas for 'fragments/reports', 'The Establishment of Scientific Semantics' and 'Intro: Theories of Vagueness'

unexpand these ideas     |    start again     |     specify just one area for these texts


25 ideas

3. Truth / F. Semantic Truth / 1. Tarski's Truth / a. Tarski's truth definition
'"It is snowing" is true if and only if it is snowing' is a partial definition of the concept of truth [Tarski]
     Full Idea: Statements of the form '"it is snowing" is true if and only if it is snowing' and '"the world war will begin in 1963" is true if and only if the world war will being in 1963' can be regarded as partial definitions of the concept of truth.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.404)
     A reaction: The key word here is 'partial'. Truth is defined, presumably, when every such translation from the object language has been articulated, which is presumably impossible, given the infinity of concatenated phrases possible in a sentence.
4. Formal Logic / D. Modal Logic ML / 3. Modal Logic Systems / h. System S5
S5 collapses iterated modalities (◊□P→□P, and ◊◊P→◊P) [Keefe/Smith]
     Full Idea: S5 collapses iterated modalities (so ◊□P → □P, and ◊◊P → ◊P).
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §5)
     A reaction: It is obvious why this might be controversial, and there seems to be a general preference for S4. There may be confusions of epistemic and ontic (and even semantic?) possibilities within a single string of modalities.
5. Theory of Logic / A. Overview of Logic / 6. Classical Logic
A language: primitive terms, then definition rules, then sentences, then axioms, and finally inference rules [Tarski]
     Full Idea: For a language, we must enumerate the primitive terms, and the rules of definition for new terms. Then we must distinguish the sentences, and separate out the axioms from amng them, and finally add rules of inference.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.402)
     A reaction: [compressed] This lays down the standard modern procedure for defining a logical language. Once all of this is in place, we then add a semantics and we are in business. Natural deduction tries to do without the axioms.
5. Theory of Logic / I. Semantics of Logic / 1. Semantics of Logic
Semantics is the concepts of connections of language to reality, such as denotation, definition and truth [Tarski]
     Full Idea: Semantics is the totality of considerations concerning concepts which express connections between expressions of a language and objects and states of affairs referred to by these expressions. Examples are denotation, satisfaction, definition and truth.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.401)
     A reaction: Interestingly, he notes that it 'is not commonly recognised' that truth is part of semantics. Nowadays truth seems to be the central concept in most semantics.
A language containing its own semantics is inconsistent - but we can use a second language [Tarski]
     Full Idea: People have not been aware that the language about which we speak need by no means coincide with the language in which we speak. ..But the language which contains its own semantics must inevitably be inconsistent.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.402)
     A reaction: It seems that Tarski was driven to propose the metalanguage approach mainly by the Liar Paradox.
5. Theory of Logic / I. Semantics of Logic / 4. Satisfaction
A sentence is satisfied when we can assert the sentence when the variables are assigned [Tarski]
     Full Idea: Here is a partial definition of the concept of satisfaction: John and Peter satisfy the sentential function 'X and Y are brothers' if and only if John and Peter are brothers.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.405)
     A reaction: Satisfaction applies to open sentences and truth to closed sentences (with named objects). He uses the notion of total satisfaction to define truth. The example is a partial definition, not just an illustration.
Satisfaction is the easiest semantical concept to define, and the others will reduce to it [Tarski]
     Full Idea: It has been found useful in defining semantical concepts to deal first with the concept of satisfaction; both because the definition of this concept presents relatively few difficulties, and because the other semantical concepts are easily reduced to it.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.406)
     A reaction: See Idea 13339 for his explanation of satisfaction. We just say that a open sentence is 'acceptable' or 'assertible' (or even 'true') when particular values are assigned to the variables. Then sentence is then 'satisfied'.
5. Theory of Logic / K. Features of Logics / 2. Consistency
Using the definition of truth, we can prove theories consistent within sound logics [Tarski]
     Full Idea: Using the definition of truth we are in a position to carry out the proof of consistency for deductive theories in which only (materially) true sentences are (formally) provable.
     From: Alfred Tarski (The Establishment of Scientific Semantics [1936], p.407)
     A reaction: This is evidently what Tarski saw as the most important first fruit of his new semantic theory of truth.
7. Existence / D. Theories of Reality / 10. Vagueness / b. Vagueness of reality
Objects such as a cloud or Mount Everest seem to have fuzzy boundaries in nature [Keefe/Smith]
     Full Idea: A common intuition is that a vague object has indeterminate or fuzzy spatio-temporal boundaries, such as a cloud. Mount Everest can only have arbitrary boundaries placed around it, so in nature it must have fuzzy boundaries.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §5)
     A reaction: We would have to respond by questioning whether Everest counts precisely as an 'object'. At the microscopic or subatomic level it seems that virtually everything has fuzzy boundaries. Maybe boundaries don't really exist.
7. Existence / D. Theories of Reality / 10. Vagueness / c. Vagueness as ignorance
If someone is borderline tall, no further information is likely to resolve the question [Keefe/Smith]
     Full Idea: If Tek is borderline tall, the unclarity does not seem to be epistemic, because no amount of further information about his exact height (or the heights of others) could help us decide whether he is tall.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: One should add also that information about social conventions or conventions about the usage of the word 'tall' will not help either. It seems fairly obvious that God would not know whether Tek is tall, so the epistemic view is certainly counterintuitive.
The simplest approach, that vagueness is just ignorance, retains classical logic and semantics [Keefe/Smith]
     Full Idea: The simplest approach to vagueness is to retain classical logic and semantics. Borderline cases are either true or false, but we don't know which, and, despite appearances, vague predicates have well-defined extensions. Vagueness is ignorance.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: It seems to me that you must have a rather unhealthy attachment to the logicians' view of the world to take this line. It is the passion of the stamp collector, to want everything in sets, with neatly labelled properties, and inference lines marked out.
The epistemic view of vagueness must explain why we don't know the predicate boundary [Keefe/Smith]
     Full Idea: A key question for the epistemic view of vagueness is: why are we ignorant of the facts about where the boundaries of vague predicates lie?
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §2)
     A reaction: Presumably there is a range of answers, from laziness, to inability to afford the instruments, to limitations on human perception. At the limit, with physical objects, how do we tell whether it is us or the object which is afflicted with vagueness?
7. Existence / D. Theories of Reality / 10. Vagueness / f. Supervaluation for vagueness
Supervaluationism keeps true-or-false where precision can be produced, but not otherwise [Keefe/Smith]
     Full Idea: The supervaluationist view of vagueness is that 'tall' comes out true or false on all the ways in which we can make 'tall' precise. There is a gap for borderline cases, but 'tall or not-tall' is still true wherever you draw a boundary.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: [Kit Fine is the spokesperson for this; it preserves classical logic, but not semantics] This doesn't seem to solve the problem of vagueness, but it does (sort of) save the principle of excluded middle.
Vague statements lack truth value if attempts to make them precise fail [Keefe/Smith]
     Full Idea: The supervaluationist view of vagueness proposes that a sentence is true iff it is true on all precisifications, false iff false on all precisifications, and neither true nor false otherwise.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: This seems to be just a footnote to the Russell/Unger view, that logic works if the proposition is precise, but otherwise it is either just the mess of ordinary life, or the predicate doesn't apply at all.
Some of the principles of classical logic still fail with supervaluationism [Keefe/Smith]
     Full Idea: Supervaluationist logic (now with a 'definite' operator D) fails to preserve certain classical principles about consequence and rules of inference. For example, reduction ad absurdum, contraposition, the deduction theorem and argument by cases.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: The aim of supervaluationism was to try to preserve some classical logic, especially the law of excluded middle, in the face of problems of vagueness. More drastic views, like treating vagueness as irrelevant to logic, or the epistemic view, do better.
The semantics of supervaluation (e.g. disjunction and quantification) is not classical [Keefe/Smith]
     Full Idea: The semantics of supervaluational views is not classical. A disjunction can be true without either of its disjuncts being true, and an existential quantification can be true without any of its substitution instances being true.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: There is a vaguely plausible story here (either red or orange, but not definitely one nor tother; there exists an x, but which x it is is undecidable), but I think I will vote for this all being very very wrong.
Supervaluation misunderstands vagueness, treating it as a failure to make things precise [Keefe/Smith]
     Full Idea: Why should we think vague language is explained away by how things would be if it were made precise? Supervaluationism misrepresents vague expressions, as vague only because we have not bothered to make them precise.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §3)
     A reaction: The theory still leaves a gap where vagueness is ineradicable, so the charge doesn't seem quite fair. Logicians always yearn for precision, but common speech enjoys wallowing in a sea of easy-going vagueness, which works fine.
7. Existence / D. Theories of Reality / 10. Vagueness / g. Degrees of vagueness
A third truth-value at borderlines might be 'indeterminate', or a value somewhere between 0 and 1 [Keefe/Smith]
     Full Idea: One approach to predications in borderline cases is to say that they have a third truth value - 'neutral', 'indeterminate' or 'indefinite', leading to a three-valued logic. Or a degree theory, such as fuzzy logic, with infinite values between 0 and 1.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: This looks more like a strategy for computer programmers than for metaphysicians, as it doesn't seem to solve the difficulty of things to which no one can quite assign any value at all. Sometimes you can't be sure if an entity is vague.
People can't be placed in a precise order according to how 'nice' they are [Keefe/Smith]
     Full Idea: There is no complete ordering of people by niceness, and two people could be both fairly nice, nice to intermediate degrees, while there is no fact of the matter about who is the nicer.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: This is a difficulty if you are trying to decide vague predicates by awarding them degrees of truth. Attempts to place a precise value on 'nice' seem to miss the point, even more than utilitarian attempts to score happiness.
If truth-values for vagueness range from 0 to 1, there must be someone who is 'completely tall' [Keefe/Smith]
     Full Idea: Many-valued theories still seem to have a sharp boundary between sentences taking truth-value 1 and those taking value less than 1. So there is a last man in our sorites series who counts as 'completely tall'.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: Lovely. Completely nice, totally red, perfectly childlike, an utter mountain, one hundred per cent amused. The enterprise seems to have the same implausibility found in Bayesian approaches to assessing evidence.
How do we decide if my coat is red to degree 0.322 or 0.321? [Keefe/Smith]
     Full Idea: What could determine which is the correct function, settling that my coat is red to degree 0.322 rather than 0.321?
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §4)
     A reaction: It is not just the uncertainty of placing the coat on the scale. The two ends of the scale have all the indeterminacy of being red rather than orange (or, indeed, pink). You are struggling to find a spot on the ruler, when the ruler is placed vaguely.
9. Objects / B. Unity of Objects / 3. Unity Problems / e. Vague objects
Vague predicates involve uncertain properties, uncertain objects, and paradoxes of gradual change [Keefe/Smith]
     Full Idea: Three interrelated features of vague predicates such as 'tall', 'red', 'heap', 'child' are that they have borderline cases (application is uncertain), they lack well-defined extensions (objects are uncertain), and they're susceptible to sorites paradoxes.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: The issue will partly depend on what you think an object is: choose from bundles of properties, total denial, essential substance, or featureless substance with properties. The fungal infection of vagueness could creep in at any point, even the words.
Many vague predicates are multi-dimensional; 'big' involves height and volume; heaps include arrangement [Keefe/Smith]
     Full Idea: Many vague predicates are multi-dimensional. 'Big' of people depends on both height and volume; 'nice' does not even have clear dimensions; whether something is a 'heap' depends both the number of grains and their arrangement.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: Anyone who was hoping for a nice tidy theory for this problem should abandon hope at this point. Huge numbers of philosophical problems can be simplified by asking 'what exactly do you mean here?' (e.g. tall or bulky?).
If there is a precise borderline area, that is not a case of vagueness [Keefe/Smith]
     Full Idea: If a predicate G has a sharply-bounded set of cases falling in between the positive and negative, this shows that merely having borderline cases is not sufficient for vagueness.
     From: R Keefe / P Smith (Intro: Theories of Vagueness [1997], §1)
     A reaction: Thus you might have 'pass', 'fail' and 'take the test again'. But there seem to be two cases in the border area: will decide later, and decision seems impossible. And the sharp boundaries may be quite arbitrary.
21. Aesthetics / C. Artistic Issues / 7. Art and Morality
Musical performance can reveal a range of virtues [Damon of Ath.]
     Full Idea: In singing and playing the lyre, a boy will be likely to reveal not only courage and moderation, but also justice.
     From: Damon (fragments/reports [c.460 BCE], B4), quoted by (who?) - where?