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Deductive Closure and Knowledge

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Epistemic ClosureClosure Principles Formalized+1 moreEpistemic Closure and Logical Closure PrinciplesSkeptical Scenarios and Knowledge Closure
knowledge closure deduction entailment

Core Idea

The closure principle asserts that knowledge is closed under known entailment: if you know that P, and you know that P entails Q, then you know Q (at least absent defeating conditions). This principle faces pressure from skeptical scenarios where you know ordinary propositions but arguably don't know skeptical scenarios are false, yet the latter follows from the former. Debates over closure reveal tensions between our intuitions about knowledge and about skepticism.

How It's Best Learned

Test closure with examples: you know your car is in the driveway, you know this entails the driveway exists, so do you know the driveway exists? Examine skeptical challenges to closure and alternative closure principles.

Common Misconceptions

Explainer

From your study of epistemic closure, you have the basic principle in hand: knowledge can "close" under certain operations. Deductive closure makes this precise for the operation of known entailment. The principle says: if you know P, and you know that P entails Q, then you know Q. This seems almost trivially obvious — how could you know a fact and know what follows from it, yet fail to know what follows? If you know the bank is open on Saturday, and you know that "the bank is open on Saturday" entails "the bank is open on some day this weekend," surely you know the bank is open some day this weekend.

The trouble begins when you apply the principle to skeptical scenarios. Here is the standard puzzle. You believe — and seem to know — that you are sitting in a room reading. You also know that "I am sitting in a room reading" entails "I am not a brain in a vat being fed experiences of sitting and reading." By closure, you therefore know that you are not a brain in a vat. But wait: do you actually know that? The whole point of the skeptical scenario is that if you were a brain in a vat, everything would look exactly the same to you. Your evidence does not distinguish between the two situations. Many philosophers, following Descartes, have the strong intuition that you *cannot* know you are not a brain in a vat. But if closure is true, and you *do* know ordinary things, then you must know the skeptical hypothesis is false. Something has to give.

This generates three main responses. Skeptics accept closure and deny that you know ordinary propositions: since you can't know you're not a brain in a vat, you can't know much of anything. Closure deniers (like Dretske and Nozick) reject the closure principle itself — they argue that knowledge requires that your belief *track* the truth in the actual world, and ordinary beliefs can track truth without your belief-forming process being sensitive to exotic skeptical scenarios. On this view, you can know your car is in the driveway without being able to rule out every far-fetched alternative. Contextualists take yet another path: they argue that the word "know" is context-sensitive, and in ordinary conversational contexts the standards are low enough that you know everyday facts, but in skeptical philosophical contexts the standards rise and you no longer "know" anything. None of these responses is without cost, which is what makes deductive closure one of epistemology's central pressure points: it forces you to choose between closure, common-sense knowledge, and the intelligibility of skepticism.

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Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicIntroduction to Predicate Logic (First-Order Logic)First-Order Logic SyntaxTerms and Atomic Formulas in FOLVariable Binding and ScopeOpen and Closed Formulas in First-Order LogicVariable Substitution and Capture-Avoidance in First-Order LogicQuantifier Instantiation Rules in First-Order Proof SystemsUniversal Quantification: Meaning and ScopeFree Variables and Bound VariablesSubstitution and Instantiation in Predicate LogicTerms and Atomic FormulasFormulas and Well-Formed ExpressionsStructures and InterpretationsModel Interpretation and SatisfactionInterpretation, Truth, and Satisfaction of FormulasLogical Consequence and EntailmentSoundness Theorem and Validity of Proof SystemsDeductive Reasoning and Formal Proof SystemsFirst-Order ResolutionPropositional ResolutionSemantic Tableaux (Propositional)Semantic Tableaux (First-Order)Decidable Fragments of First-Order LogicGödel's Completeness Theorem for First-Order LogicGödel's Incompleteness TheoremsIntroduction to Intuitionistic LogicIntroduction to Modal LogicA Priori and A Posteriori KnowledgeRationalism vs. EmpiricismThe Problem of InductionPopper's FalsificationismFalsifiability as the Criterion of DemarcationThe Falsifiability Criterion and Its ProblemsKuhn's Paradigm TheoryNormal Science and AnomaliesThomas Kuhn and Paradigm ShiftsScientific Progress and Convergence to TruthScientific RealismNaturalism About Semantic FactsPropositions and Semantic ContentTruth Conditions and MeaningFormal Language and Natural Language SemanticsTwo-Dimensional SemanticsModal Semantics and Possible WorldsPossible Worlds Semantics for KnowledgeClosure Principles FormalizedDeductive Closure and Knowledge

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