| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Examines how linguistic expressions encode and convey meaning, including lexical semantics, compositional semantics, truth conditions, reference, quantification, scope, entailment, presupposition, aspect, modality, and semantic features. Excludes pragmatic inference, discourse structure, or world knowledge except where required to compute literal meaning. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates at the level of morphemes, words, phrases, and sentences; temporal scale concerns interpretive processes; organizational scale spans semantic fields, argument structures, and logical forms. |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Meanings, semantic features, predicates, arguments, referents, events, propositions, truth values, possible worlds, thematic roles, semantic types (e.g., e, t), quantifiers, variables, domains of discourse. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Truth conditions, entailment relations, semantic compatibility, selectional restrictions, argument structure, scope relations, monotonicity, reference stability, type requirements, aspectual class. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Lexical meaning types; semantic roles (agent, theme, experiencer); predicate types (eventive, stative); quantifier classes; modality types; aspect classes; semantic features; type-theoretic categories. |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Variable assignments, domain sizes, quantifier scope, event parameters, reference resolution states, type constraints, polarity contexts, intensional parameters (possible-world index). |
| | Parameterization | How variables encode and represent the system’s state. | Encoded through typed logical forms, λ-calculus expressions, feature bundles, event-structure representations, quantifier-binding structures, scope hierarchies, domain specifications. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Treating meaning as strictly truth-conditional; assuming stable reference; ignoring polysemy; idealizing lexical entries; treating context as fixed; modeling quantifier scope via clean hierarchies; assuming discrete semantic types. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Breakdowns occur with ambiguity, vagueness, metaphor, context-dependence, pragmatic enrichment, indexicals, cross-linguistic variation in meaning categories, or constructions with underspecified interpretation. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Assumes meaning composition is rule-governed; semantics interfaces systematically with syntax; lexical items have structured semantic representations; logical forms exist; entailment relations are computable. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes meanings are mentally represented; truth conditions correspond to cognitive representations of situations; formal semantic categories reflect genuine linguistic universals; interpretation relies on structured internal mappings. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Type constraints must align across expressions; scope assignment must be internally consistent; variable binding must follow syntactic structure; lexical meanings must combine compositionally; entailment relations must follow semantic rules. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Requires alignment among lexical semantics, compositional rules, quantifier scope mechanisms, event semantics, type theory, and semantic–syntactic interface conditions to form a unified interpretive system. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Truth-value judgments, entailment patterns, paraphrase judgments, ambiguity detection, scope preference data, acceptability tied to semantic constraints, lexical-relatedness ratings, presupposition projection behavior, quantifier interaction patterns, event-structure interpretations. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Internal meanings not directly observable; truth-value judgments rely on world knowledge; subtle scope differences difficult to elicit; presuppositions may be confused with pragmatics; lexical-semantic nuance often hidden; introspective judgments vary across individuals. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Truth-value outcomes (true/false), acceptability scales, similarity ratings, scalar-implicature rates, entailment validity scores, reaction-time units, ERP/FMRI activation metrics for semantic anomalies. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Semantic-judgment surveys, truth-value judgment tasks, entailment tests, lexical-relatedness questionnaires, self-paced reading, eye-tracking systems, EEG/ERP (N400), fMRI semantic-network recordings, computational semantic parsers. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Definitions of truth condition, entailment, presupposition, implicature, ambiguity, polysemy, scope, quantifier type, event structure, semantic type (e, t, ⟨e,t⟩, etc.), intensional parameter. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Collecting truth-value judgments; creating paraphrase tasks; eliciting lexical-relatedness ratings; testing scope resolution via controlled stimuli; running semantic anomaly paradigms; coding entailment relations; generating minimal semantic contrasts. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Randomized semantic-judgment tasks; structured elicitation of scope/ambiguity; truth-value survey administration; controlled sentence–picture matching; event-structure diagnostics; cross-linguistic semantic-field elicitation. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Sampling across lexical items, syntactic frames, semantic roles, quantifier types, context conditions, languages, dialects, speaker groups, and varying world-knowledge assumptions. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Truth-value judgment tables; entailment matrices; lexical-relatedness datasets; ambiguity-resolution logs; reaction-time files; ERP anomaly waveforms; semantic-type annotations; scope-disambiguation tables. |
| | Resolution | The granularity or precision with which data is captured. | Determined by granularity of semantic distinctions, clarity of elicitation materials, temporal resolution of ERP or eye-tracking tools, task sensitivity to subtle scope interactions, and consistency of truth-value judgments. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Standardizing judgment-task instructions; validating truth-value stimuli; calibrating ERP equipment; ensuring consistent coding of semantic roles; checking inter-annotator agreement for entailment classification; verifying parser accuracy. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Judgment inconsistency; ambiguity misclassification; confounds with pragmatics; cultural/world-knowledge bias; ERP signal noise; parser misinterpretation; stimulus-design artifacts; participant misunderstanding. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Compositionality (meaning of a whole derives from parts + structure); scope relations; entailment laws; monotonicity patterns; lexical semantic-field relations; argument-structure correspondences; cross-linguistic universals in quantification and negation. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Stable semantic types; fixed truth-conditional relations for logical operators; consistent argument–predicate mappings; invariant thematic-role patterns; reproducible entailment and presupposition behavior. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Predicate–argument structure building; type-driven interpretation; quantifier binding; event-structure construction; reference resolution; variable assignment; presupposition triggering; scope-taking mechanisms. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Lexical meaning → composition → semantic structure; syntactic representation → LF derivation → interpretation; quantifier introduction → scope assignment → truth-condition computation; event predicate → argument saturation → aspectual interpretation. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Truth conditions, reference, denotation, entailment, presupposition, implicature (at boundary), quantifier scope, lambda abstraction, semantic type, event structure, intensionality, modality, thematic roles. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Predicate types (stative, eventive); modality types (epistemic, deontic); quantifier classes (existential, universal, proportional); aspectual classes (achievement, accomplishment, state, activity); semantic relations (synonymy, antonymy, hyponymy). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | λ-calculus expressions; semantic-type signatures; truth-condition equations; quantifier-binding formulas; event-semantic representations (e.g., e, t, v types); intensional operators; semantic composition rules (function application, predicate modification). |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Montague grammar; Davidsonian event semantics; neo-Davidsonian predicate decomposition; dynamic semantics; situation semantics; distributional semantic models; type-driven semantic parsers. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Fully discrete meanings; perfectly stable denotations; binary truth values without gradience; strict compositionality; unambiguous scope; single-inheritance semantic hierarchies; idealized possible-world structures. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Failures with vagueness, polysemy, metaphor, pragmatics intrusion, contextual underspecification, idioms, non-literal language, cross-linguistic semantic gaps, and noisy or ambiguous referential environments. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Compositional semantics; type theory; event semantics; universal quantification frameworks; semantic–syntactic interface theories; intensional semantics; dynamic-update semantics; integrated semantic–pragmatic models. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Links to logic (formal systems), philosophy (reference, truth), psychology (concept representation), AI/ML (semantic parsing, embedding models), cognitive science (conceptual structure), and neuroscience (meaning processing). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating quantifier scope contexts, ambiguity triggers, aspectual cues, truth-condition variables, reference sets, and presupposition environments to test semantic predictions; constructing minimal contrasts to isolate specific semantic operations. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Observing natural interpretation patterns in conversation, corpora, or comprehension tasks; documenting semantic variation across dialects and languages; tracking spontaneous ambiguity resolution; studying presupposition failures or entailment judgments without manipulation. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Testing compositional predictions; validating entailment and contradiction relations; evaluating scope preferences; testing presupposition projection; confirming semantic-type constraints; verifying event-structure interpretations; checking truth-conditional outcomes. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Re-running truth-value judgment tasks; replicating paraphrase and entailment tests; re-evaluating ambiguity-resolution experiments; repeating ERP/N400 semantic-anomaly studies; verifying scope-interaction results across participant groups or languages. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Analyzing truth-value distributions; modeling acceptability/interpretation patterns; computing semantic-similarity metrics; evaluating reaction-time differences in semantic processing; quantifying presupposition persistence; measuring frequency of semantic alternations in corpora. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing truth-conditional vs dynamic-semantic models; evaluating Montague vs event semantics; contrasting type-logical systems; comparing distributional semantic models vs formal ones; contrasting scopal-parsing algorithms; testing predictions of intensional vs extensional models. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying judgment inconsistencies; distinguishing semantic from pragmatic errors; correcting misclassified entailment relations; detecting ambiguity contamination in stimuli; managing world-knowledge confounds; filtering parser misinterpretation; addressing noise in ERP semantic responses. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Randomizing trial order; balancing lexical frequencies; controlling for contextual bias; standardizing instructions; using blinded coding; ensuring cross-linguistic neutrality of stimuli; avoiding semantic tasks that implicitly test world knowledge instead of meaning. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent reevaluation of semantic datasets; reanalysis of entailment/implicature patterns; external critique of logical-form derivations; replication of semantic anomaly results; cross-linguistic verification of semantic universals; comparison to alternative semantic frameworks. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Refining semantic-type systems; updating event-structure theories; revising quantifier-scope mechanisms; modifying presupposition-projection models; adjusting lexical semantic fields; integrating new empirical or cross-linguistic evidence; revising intensional-semantics assumptions. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of stimuli sets, task instructions, coding protocols, world-knowledge assumptions, interpretation criteria, model assumptions, and cross-linguistic sampling procedures. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Avoiding culturally biased stimuli; ensuring informed consent in experiments; respecting linguistic diversity; protecting participant privacy; avoiding overclaims about semantic universals; responsibly handling ambiguous or misleading examples. |