A topic in the Open Knowledge Graph — a free, open map of 15,290 topics and the order to learn them in.

Metaphor and Semantic Innovation

College Depth 113 in the knowledge graph I know this Set as goal
2topics build on this
752prerequisites beneath it
See this on the map →
Compositionality and Semantic ValuesLiteral Meaning and Speaker Meaning+4 moreMetaphor and Cultural Semantics: The Untranslatable in Meaning
metaphor meaning semantics

Core Idea

Metaphorical language extends meaning beyond literal content by mapping structure from a source domain onto a target domain. When we say 'Time is money,' we map economic structure onto temporal structure. Metaphor is a systematic way of extending and organizing conceptual structure.

How It's Best Learned

Collect examples of metaphors and study how they map properties from source to target domain. Compare conceptual metaphor theory with speech act approaches to understand different aspects of metaphorical understanding.

Explainer

From your study of compositionality and the distinction between literal and speaker meaning, you know that sentences derive their meaning from the meanings of their parts and the way those parts are combined, and that what a speaker means can diverge from what their words literally say. Metaphor sits at the intersection of these insights: a metaphorical utterance uses words with established literal meanings to communicate something that cannot be reduced to those literal meanings. The philosophical question is how metaphor works — whether it is a decorative deviation from literal language, a pragmatic act of the speaker, or a fundamental cognitive mechanism that shapes how we think.

Conceptual metaphor theory, developed by George Lakoff and Mark Johnson, argues for the strongest claim: metaphor is not primarily a feature of language but a feature of thought. When we say "time is money," we are not making a stylistic choice — we are revealing an underlying conceptual mapping that organizes how we reason about time. The source domain (money/economics) projects its relational structure onto the target domain (time): time can be spent, wasted, saved, invested, budgeted, and run out of. Each of these expressions is licensed by the mapping, and together they form a systematic network of inferences. The mapping is asymmetric — we understand time through money, not money through time — and selective: it highlights certain aspects of the target (time as a limited resource) while suppressing others (time as lived experience, as memory, as rhythm).

This systematicity distinguishes conceptual metaphors from mere comparisons or analogies. A comparison says "A is like B in some respect," leaving both domains independent. A conceptual metaphor restructures the target domain by importing the inferential architecture of the source. "Argument is war" licenses not just "he attacked my position" but an entire framework: arguments have sides, they can be won or lost, positions are defended or surrendered, points are targeted. Removing the metaphor does not reveal a pre-existing literal structure underneath — for many abstract domains, the metaphor provides the only conceptual structure available. This is why the claim that metaphors are "merely ornamental" and could always be replaced by literal language is wrong: stripping the metaphor would not simplify the description but remove the inferential organization that makes the domain thinkable.

The implications extend into science, philosophy, and everyday cognition. Scientific discourse is saturated with metaphors that are not decorative but constitutive: "gene expression," "natural selection," "electric current," "force fields." These metaphors shape which inferences are available and which aspects of the phenomenon are foregrounded. The atom-as-solar-system metaphor licenses reasoning about orbits and central mass but suppresses quantum indeterminacy. Understanding metaphor as semantic innovation — as a mechanism that extends and reorganizes meaning beyond what literal composition provides — reveals that much of our conceptual life depends on structural projections between domains. Metaphor is not a departure from serious thought; it is one of the primary engines by which serious thought advances.

What did you take from this?

Topics in reflective domains aren't scored by quiz answers. Read, reflect, and mark when you've thought it through.

Quiz me anyway →

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 SemanticsMetaphor and Semantic Innovation

Longest path: 114 steps · 752 total prerequisite topics

Prerequisites (6)

Leads To (1)