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All the ideas for 'works', 'Explaining Explanation' and 'A Tour through Mathematical Logic'

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29 ideas

1. Philosophy / F. Analytic Philosophy / 7. Limitations of Analysis
Paradox: why do you analyse if you know it, and how do you analyse if you don't? [Ruben]
     Full Idea: The alleged paradox of analysis asserts that if one knew what was involved in the concept, one would not need the analysis; if one did not know what was involved in the concept, no analysis could be forthcoming.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 1)
     A reaction: This is the sort of problem that seemed to bug Plato a lot. You certainly can't analyse something if you don't understand it, but it seems obvious that you can illuminatingly analyse something of which you have a reasonable understanding.
1. Philosophy / G. Scientific Philosophy / 1. Aims of Science
Realism is the only philosophy of science that doesn't make the success of science a miracle [Putnam]
     Full Idea: Realism….is the only philosophy science which does not make the success of science a miracle.
     From: Hilary Putnam (works [1980]), quoted by Alexander Bird - Philosophy of Science Ch.4
     A reaction: This was from his earlier work; he became more pragmatist and anti-realist later. Personally I approve of the remark. The philosophy of science must certainly offer an explanation for its success. Truth seems the obvious explanation.
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.
7. Existence / D. Theories of Reality / 4. Anti-realism
Putnam says anti-realism is a bad explanation of accurate predictions [Putnam, by Okasha]
     Full Idea: Putnam's 'no miracle' argument says that being an anti-realist is akin to believing in miracles (because of the accurate predictons). …It is a plausibility argument - an inference to the best explanation.
     From: report of Hilary Putnam (works [1980]) by Samir Okasha - Philosophy of Science: Very Short Intro (2nd ed) 4
     A reaction: [not sure of ref] Putnam later backs off from this argument, but my personal realism rests on best explanation. Does anyone want to prefer an inferior explanation? The objection is that successful theories can turn out to be false. Phlogiston, ether.
14. Science / A. Basis of Science / 4. Prediction
The 'symmetry thesis' says explanation and prediction only differ pragmatically [Ruben]
     Full Idea: The 'symmetry thesis' holds that there is only a pragmatic, or epistemic, but no logical, difference between explaining and predicting. …The only difference is in what the producer of the deduction knows just before the deduction is produced.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 4)
     A reaction: He cites Mill has holding this view. It seems elementary to me that I can explain something but not predict it, or predict it but not explain it. The latter case is just Humean habitual induction.
14. Science / D. Explanation / 1. Explanation / a. Explanation
Usually explanations just involve giving information, with no reference to the act of explanation [Ruben]
     Full Idea: Plato, Aristotle, Mill and Hempel believed that an explanatory product can be characterized solely in terms of the kind of information it conveys, no reference to the act of explaining being required.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 1)
     A reaction: Achinstein says it's about acts, because the same information could be an explanation, or a critique, or some other act. Ruben disagrees, and so do I.
14. Science / D. Explanation / 1. Explanation / c. Direction of explanation
An explanation needs the world to have an appropriate structure [Ruben]
     Full Idea: Objects or events in the world must really stand in some appropriate 'structural' relation before explanation is possible.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 7)
     A reaction: An important point. These days people talk of 'dependence relations'. Some sort of structure to reality (mainly imposed by the direction of time and causation, I would have thought) is a prerequisite of finding a direction to explanation.
14. Science / D. Explanation / 2. Types of Explanation / a. Types of explanation
Most explanations are just sentences, not arguments [Ruben]
     Full Idea: Typically, full explanations are not arguments, but singular sentences, or conjunctions thereof.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 6)
     A reaction: This is mainly objecting to the claim that explanations are deductions from laws and facts. I agree with Ruben. Explanations are just information, I think. Of course, Aristotle's demonstrations are arguments.
14. Science / D. Explanation / 2. Types of Explanation / g. Causal explanations
The causal theory of explanation neglects determinations which are not causal [Ruben]
     Full Idea: The fault of the causal theory of explanation was to overlook the fact that there are more ways of making something what it is or being responsible for it than by causing it. …Causation is a particular type of determinative relation.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 7)
     A reaction: The only thing I can think of is that certain abstract facts are 'determined' by other abtract facts, without being 'caused' by them. A useful word.
14. Science / D. Explanation / 2. Types of Explanation / j. Explanations by reduction
Reducing one science to another is often said to be the perfect explanation [Ruben]
     Full Idea: The reduction of one science to another has often been taken as paradigmatic of explanation.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 5)
     A reaction: It seems fairly obvious that the total reduction of chemistry to physics would involve the elimination of all the current concepts of chemistry. Could this possibly enhance our understanding of chemistry? I would have thought not.
14. Science / D. Explanation / 4. Explanation Doubts / a. Explanation as pragmatic
Facts explain facts, but only if they are conceptualised or named appropriately [Ruben]
     Full Idea: Facts explain facts only when the features and the individuals the facts are about are appropriately conceptualized or named.
     From: David-Hillel Ruben (Explaining Explanation [1990], Ch 5)
     A reaction: He has a nice example that 'Cicero's speeches stop in 43 BCE' isn't explained by 'Tully died then', if you don't know that Cicero was Tully. Ruben is not defending pragmatic explanation, but to this extent he must be right.