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All the ideas for 'fragments/reports', 'Elusive Knowledge' and 'A Tour through Mathematical Logic'

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26 ideas

4. Formal Logic / B. Propositional Logic PL / 2. Tools of Propositional Logic / b. Terminology of PL
A 'tautology' must include connectives [Wolf,RS]
     Full Idea: 'For every number x, x = x' is not a tautology, because it includes no connectives.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.2)
4. Formal Logic / B. Propositional Logic PL / 2. Tools of Propositional Logic / c. Derivation rules of PL
Deduction Theorem: T∪{P}|-Q, then T|-(P→Q), which justifies Conditional Proof [Wolf,RS]
     Full Idea: Deduction Theorem: If T ∪ {P} |- Q, then T |- (P → Q). This is the formal justification of the method of conditional proof (CPP). Its converse holds, and is essentially modus ponens.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.3)
4. Formal Logic / C. Predicate Calculus PC / 2. Tools of Predicate Calculus / d. Universal quantifier ∀
Universal Generalization: If we prove P(x) with no special assumptions, we can conclude ∀xP(x) [Wolf,RS]
     Full Idea: Universal Generalization: If we can prove P(x), only assuming what sort of object x is, we may conclude ∀xP(x) for the same x.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.3)
     A reaction: This principle needs watching closely. If you pick one person in London, with no presuppositions, and it happens to be a woman, can you conclude that all the people in London are women? Fine in logic and mathematics, suspect in life.
Universal Specification: ∀xP(x) implies P(t). True for all? Then true for an instance [Wolf,RS]
     Full Idea: Universal Specification: from ∀xP(x) we may conclude P(t), where t is an appropriate term. If something is true for all members of a domain, then it is true for some particular one that we specify.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.3)
4. Formal Logic / C. Predicate Calculus PC / 2. Tools of Predicate Calculus / e. Existential quantifier ∃
Existential Generalization (or 'proof by example'): if we can say P(t), then we can say something is P [Wolf,RS]
     Full Idea: Existential Generalization (or 'proof by example'): From P(t), where t is an appropriate term, we may conclude ∃xP(x).
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.3)
     A reaction: It is amazing how often this vacuous-sounding principles finds itself being employed in discussions of ontology, but I don't quite understand why.
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / e. Axiom of the Empty Set IV
Empty Set: ∃x∀y ¬(y∈x). The unique empty set exists [Wolf,RS]
     Full Idea: Empty Set Axiom: ∃x ∀y ¬ (y ∈ x). There is a set x which has no members (no y's). The empty set exists. There is a set with no members, and by extensionality this set is unique.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 2.3)
     A reaction: A bit bewildering for novices. It says there is a box with nothing in it, or a pair of curly brackets with nothing between them. It seems to be the key idea in set theory, because it asserts the idea of a set over and above any possible members.
4. Formal Logic / F. Set Theory ST / 4. Axioms for Sets / n. Axiom of Comprehension
Comprehension Axiom: if a collection is clearly specified, it is a set [Wolf,RS]
     Full Idea: The comprehension axiom says that any collection of objects that can be clearly specified can be considered to be a set.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 2.2)
     A reaction: This is virtually tautological, since I presume that 'clearly specified' means pinning down exact which items are the members, which is what a set is (by extensionality). The naïve version is, of course, not so hot.
5. Theory of Logic / A. Overview of Logic / 5. First-Order Logic
In first-order logic syntactic and semantic consequence (|- and |=) nicely coincide [Wolf,RS]
     Full Idea: One of the most appealing features of first-order logic is that the two 'turnstiles' (the syntactic single |-, and the semantic double |=), which are the two reasonable notions of logical consequence, actually coincide.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.3)
     A reaction: In the excitement about the possibility of second-order logic, plural quantification etc., it seems easy to forget the virtues of the basic system that is the target of the rebellion. The issue is how much can be 'expressed' in first-order logic.
First-order logic is weakly complete (valid sentences are provable); we can't prove every sentence or its negation [Wolf,RS]
     Full Idea: The 'completeness' of first order-logic does not mean that every sentence or its negation is provable in first-order logic. We have instead the weaker result that every valid sentence is provable.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.3)
     A reaction: Peter Smith calls the stronger version 'negation completeness'.
5. Theory of Logic / J. Model Theory in Logic / 1. Logical Models
Model theory reveals the structures of mathematics [Wolf,RS]
     Full Idea: Model theory helps one to understand what it takes to specify a mathematical structure uniquely.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.1)
     A reaction: Thus it is the development of model theory which has led to the 'structuralist' view of mathematics.
Model theory 'structures' have a 'universe', some 'relations', some 'functions', and some 'constants' [Wolf,RS]
     Full Idea: A 'structure' in model theory has a non-empty set, the 'universe', as domain of variables, a subset for each 'relation', some 'functions', and 'constants'.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.2)
Model theory uses sets to show that mathematical deduction fits mathematical truth [Wolf,RS]
     Full Idea: Model theory uses set theory to show that the theorem-proving power of the usual methods of deduction in mathematics corresponds perfectly to what must be true in actual mathematical structures.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], Pref)
     A reaction: That more or less says that model theory demonstrates the 'soundness' of mathematics (though normal arithmetic is famously not 'complete'). Of course, he says they 'correspond' to the truths, rather than entailing them.
First-order model theory rests on completeness, compactness, and the Löwenheim-Skolem-Tarski theorem [Wolf,RS]
     Full Idea: The three foundations of first-order model theory are the Completeness theorem, the Compactness theorem, and the Löwenheim-Skolem-Tarski theorem.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.3)
     A reaction: On p.180 he notes that Compactness and LST make no mention of |- and are purely semantic, where Completeness shows the equivalence of |- and |=. All three fail for second-order logic (p.223).
5. Theory of Logic / J. Model Theory in Logic / 2. Isomorphisms
An 'isomorphism' is a bijection that preserves all structural components [Wolf,RS]
     Full Idea: An 'isomorphism' is a bijection between two sets that preserves all structural components. The interpretations of each constant symbol are mapped across, and functions map the relation and function symbols.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.4)
5. Theory of Logic / J. Model Theory in Logic / 3. Löwenheim-Skolem Theorems
The LST Theorem is a serious limitation of first-order logic [Wolf,RS]
     Full Idea: The Löwenheim-Skolem-Tarski theorem demonstrates a serious limitation of first-order logic, and is one of primary reasons for considering stronger logics.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.7)
5. Theory of Logic / K. Features of Logics / 4. Completeness
If a theory is complete, only a more powerful language can strengthen it [Wolf,RS]
     Full Idea: It is valuable to know that a theory is complete, because then we know it cannot be strengthened without passing to a more powerful language.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 5.5)
5. Theory of Logic / K. Features of Logics / 10. Monotonicity
Most deductive logic (unlike ordinary reasoning) is 'monotonic' - we don't retract after new givens [Wolf,RS]
     Full Idea: Deductive logic, including first-order logic and other types of logic used in mathematics, is 'monotonic'. This means that we never retract a theorem on the basis of new givens. If T|-φ and T⊆SW, then S|-φ. Ordinary reasoning is nonmonotonic.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 1.7)
     A reaction: The classic example of nonmonotonic reasoning is the induction that 'all birds can fly', which is retracted when the bird turns out to be a penguin. He says nonmonotonic logic is a rich field in computer science.
6. Mathematics / A. Nature of Mathematics / 3. Nature of Numbers / e. Ordinal numbers
An ordinal is an equivalence class of well-orderings, or a transitive set whose members are transitive [Wolf,RS]
     Full Idea: Less theoretically, an ordinal is an equivalence class of well-orderings. Formally, we say a set is 'transitive' if every member of it is a subset of it, and an ordinal is a transitive set, all of whose members are transitive.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], 2.4)
     A reaction: He glosses 'transitive' as 'every member of a member of it is a member of it'. So it's membership all the way down. This is the von Neumann rather than the Zermelo approach (which is based on singletons).
6. Mathematics / B. Foundations for Mathematics / 6. Mathematics as Set Theory / a. Mathematics is set theory
Modern mathematics has unified all of its objects within set theory [Wolf,RS]
     Full Idea: One of the great achievements of modern mathematics has been the unification of its many types of objects. It began with showing geometric objects numerically or algebraically, and culminated with set theory representing all the normal objects.
     From: Robert S. Wolf (A Tour through Mathematical Logic [2005], Pref)
     A reaction: His use of the word 'object' begs all sorts of questions, if you are arriving from the street, where an object is something which can cause a bruise - but get used to it, because the word 'object' has been borrowed for new uses.
11. Knowledge Aims / A. Knowledge / 4. Belief / a. Beliefs
The timid student has knowledge without belief, lacking confidence in their correct answer [Lewis]
     Full Idea: I allow knowledge without belief, as in the case of the timid student who knows the answer but has no confidence that he has it right, and so does not believe what he knows.
     From: David Lewis (Elusive Knowledge [1996], p.429)
     A reaction: [He cites Woozley 1953 for the timid student] I don't accept this example (since my views on knowledge are rather traditional, I find). Why would the student give that answer if they didn't believe it? Sustained timid correctness never happens.
11. Knowledge Aims / B. Certain Knowledge / 3. Fallibilism
To say S knows P, but cannot eliminate not-P, sounds like a contradiction [Lewis]
     Full Idea: If you claim that S knows that P, and yet grant that S cannot eliminate a certain possibility of not-P, it certainly seems as if you have granted that S does not after all know that P. To speak of fallible knowledge just sounds contradictory.
     From: David Lewis (Elusive Knowledge [1996], p.419)
     A reaction: Starting from this point, fallibilism seems to be a rather bold move. The only sensible response seems to be to relax the requirement that not-P must be eliminable. Best: in one epistemic context P, in another not-P.
13. Knowledge Criteria / A. Justification Problems / 1. Justification / b. Need for justification
Justification is neither sufficient nor necessary for knowledge [Lewis]
     Full Idea: I don't agree that the mark of knowledge is justification, first because justification isn't sufficient - your true opinion that you will lose the lottery isn't knowledge, whatever the odds; and also not necessary - for what supports perception or memory?
     From: David Lewis (Elusive Knowledge [1996])
     A reaction: I don't think I agree. The point about the lottery is that an overwhelming reason will never get you to knowing that you won't win. But good reasons are coherent, not statistical. If perceptions are dubious, justification must be available.
13. Knowledge Criteria / C. External Justification / 6. Contextual Justification / a. Contextualism
Knowing is context-sensitive because the domain of quantification varies [Lewis, by Cohen,S]
     Full Idea: The context-sensitivity of 'knows' is a function of contextual restrictions on the domain of quantification.
     From: report of David Lewis (Elusive Knowledge [1996]) by Stewart Cohen - Contextualism Defended p.68
     A reaction: I think the shifting 'domain of quantification' is one of the most interesting features of ordinary talk. Or, more plainly. 'what are you actually talking about?' is the key question in any fruitful dialogue. Sophisticated speakers tacitly shift domain.
We have knowledge if alternatives are eliminated, but appropriate alternatives depend on context [Lewis, by Cohen,S]
     Full Idea: S knows P if S's evidence eliminates every alternative. But the nature of the alternatives depends on context. So for Lewis, the context sensitivity of 'knows' is a function of contextual restrictions ln the domain of quantification.
     From: report of David Lewis (Elusive Knowledge [1996]) by Stewart Cohen - Contextualism Defended (and reply) 1
     A reaction: A typical modern attempt to 'regiment' a loose term like 'context'. That said, I like the idea. I'm struck by how the domain varies during a conversation (as in 'what we are talking about'). Domains standardly contain 'objects', though.
26. Natural Theory / A. Speculations on Nature / 5. Infinite in Nature
Archelaus was the first person to say that the universe is boundless [Archelaus, by Diog. Laertius]
     Full Idea: Archelaus was the first person to say that the universe is boundless.
     From: report of Archelaus (fragments/reports [c.450 BCE]) by Diogenes Laertius - Lives of Eminent Philosophers 02.Ar.3
27. Natural Reality / G. Biology / 3. Evolution
Archelaus said life began in a primeval slime [Archelaus, by Schofield]
     Full Idea: Archelaus wrote that life on Earth began in a primeval slime.
     From: report of Archelaus (fragments/reports [c.450 BCE]) by Malcolm Schofield - Archelaus
     A reaction: This sounds like a fairly clearcut assertion of the production of life by evolution. Darwin's contribution was to propose the mechanism for achieving it. We should honour the name of Archelaus for this idea.