| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Examines the processes by which emotions arise, are experienced, expressed, shaped, regulated, and used to motivate behavior. Includes affective appraisal, emotional expression, motivational drives, reward systems, regulatory strategies, stress responses, and adaptive behavioral functions. Excludes purely cognitive processing unless shaped by affective states, and excludes social emotions unless mediated through internal affective mechanisms. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates at organism-level and psychological timescales: milliseconds-to-seconds for appraisal and arousal, minutes-to-hours for regulation, and developmental trajectories across lifespan shaping affective patterns. |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Emotional states, affective valence and arousal, motivational drives, reward signals, physiological responses, appraisal processes, affect-regulation strategies, stress hormones, autonomic responses. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Intensity, valence, arousal, motivational strength, persistence, regulation success, physiological activation, thresholds of emotional triggering, resilience, mood stability, hedonic value. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Basic emotions, complex emotions, intrinsic vs extrinsic motivation, appetitive vs aversive drives, automatic vs controlled regulation, cognitive reappraisal, suppression, avoidance, approach tendencies, mood states. |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Arousal level, valence value, autonomic indicators (heart rate, GSR), cortisol or stress markers, motivational activation, reward expectation, regulation effort, emotional duration, variability, and recovery time. |
| | Parameterization | How variables encode and represent the system’s state. | Encoded through physiological readings, self-report scales, behavioral measures, computational affect parameters, appraisal-rule sets, reward-prediction signals, emotional-intensity curves. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Treating emotions as discrete categories; assuming constant motivation; ignoring cultural variation; modeling regulation as linear or rational; assuming stable baseline affect; treating appraisal rules as uniform across individuals. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Break down under trauma, chronic stress, psychiatric conditions, strong cultural modulation, multitasking environments, emotion–cognition entanglement, or when physiological signals lack clear mapping to subjective experience. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Assumes emotions serve adaptive functions; affect arises from appraisals and physiological activation; regulation processes follow systematic strategies; motivation directs behavior through value and reward structures. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes coherence between physiological arousal and subjective emotion; motivation reliably predicts behavior; regulation strategies have measurable outcomes; emotional categories map onto consistent biological systems. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Affective constructs must align with motivational models; physiological, cognitive, and behavioral indicators must converge; regulation strategies must map logically onto emotional processes; appraisal frameworks must be internally consistent. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | Requires integration between emotional appraisal, physiological activation, motivational drive systems, and regulation strategies; metrics must support a unified affective–motivational architecture. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Facial expressions, vocal tone, posture and gesture changes, autonomic arousal (heart rate, GSR), cortisol levels, pupil dilation, approach/avoidance behaviors, self-reported emotion states, motivational persistence, regulation attempts (reappraisal, suppression). |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Subjective emotion may not map cleanly onto physiology; covert motivation unobservable; micro-expressions too fast to reliably detect; cultural variation obscures expression; physiological noise limits precision; regulation strategies may occur internally without visible behavior. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Arousal indices, valence scales, heart-rate change (bpm), galvanic skin response units, cortisol concentrations, emotion-intensity ratings, reaction-time delays, approach-avoidance distances, regulation-success scores. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Physiological sensors (HR, GSR), hormone assays, eye-trackers, facial-expression coders (FACS), EEG/ERP, fMRI, self-report inventories, motivational tasks, behavioral coding software. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | Definitions of emotional valence, arousal, motivation strength, regulation success, stress response, reappraisal, suppression, reward expectation, intrinsic vs extrinsic motivation. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Presenting affective stimuli; measuring physiological responses; administering motivation tasks; instructing regulation strategies; coding expressive behavior; collecting hormone samples; recording approach/avoidance decisions. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Controlled lab experiments; repeated trials; randomized stimulus presentation; emotion-induction procedures; longitudinal tracking of affect; multimodal recordings (behavioral + physiological + self-report). |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Sampling across emotional intensities; sampling individuals with different motivational profiles; sampling across contexts (stress vs baseline); sampling trials for regulation attempts; sampling timepoints across emotional episodes. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Time-series physiological data; emotion-rating tables; reaction-time logs; facial-action codes; hormone-level datasets; regulation-performance metrics; verbal self-reports; multimodal behavioral recordings. |
| | Resolution | The granularity or precision with which data is captured. | Determined by sensor precision, sampling frequency of physiological data, temporal fidelity of emotion coding, accuracy of hormone assays, granularity of self-report scales, and resolution of multimodal synchronization. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Calibrating sensors; verifying hormone-assay accuracy; standardizing facial-expression coding; ensuring consistent stimulus intensity; validating regulation-task scoring; confirming inter-rater reliability for behavioral coding. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Physiological noise; participant reactivity; misinterpreted expressions; self-report bias; sensor drift; timing errors; hormone-sample degradation; fatigue or habituation effects during long tasks. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Consistent appraisal–arousal–behavior loops; predictable approach/avoidance tendencies; reward–motivation curves; habituation and sensitization patterns; stress-response cycles; regulation efficacy curves (e.g., reappraisal reduces intensity, suppression increases physiological load). |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Core affect dimensions (valence, arousal); stability of motivational drives; repeating physiological patterns under specific emotions; consistent recovery trajectories; persistent regulatory-strategy profiles across contexts. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Appraisal mechanisms; autonomic-arousal mechanisms; reward-prediction mechanisms; drive-activation mechanisms; emotional-learning mechanisms; regulatory mechanisms (reappraisal, suppression, avoidance, rumination, distraction). |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Stimulus → appraisal → arousal → emotion → behavior; cue → motivation activation → action selection; emotion → regulation attempt → affective outcome; stressor → sympathetic activation → recovery pathway. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Valence, arousal, appraisal, motivation, reward, regulation strategy, coping mechanism, affective threshold, prediction error, emotional resilience, hedonic value, autonomic activation, recovery curve. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Basic vs complex emotions; intrinsic vs extrinsic motivation; approach vs avoidance drives; automatic vs controlled regulation; adaptive vs maladaptive strategies; acute vs chronic affective states; high vs low arousal emotions. |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Arousal–recovery functions; reward-prediction error equations; habituation/sensitization curves; appraisal-weighting models; regulation-effectiveness functions; stress–response models; utility-based motivational equations. |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Appraisal theory models; opponent-process models; reinforcement-based motivation models; dual-process emotion/regulation models; predictive-processing emotion models; autonomic-activation models; cognitive–affective integration frameworks. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Discrete-emotion models; linear arousal systems; single-drive motivational models; simplified regulation strategies (e.g., pure reappraisal only); noise-free recovery curves; uniform appraisal rules; homogeneous physiological baselines. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Failures in trauma, chronic stress, neurodivergence, psychiatric disorders, pharmacological modulation, extreme arousal, cultural variability, or when physiological and subjective emotion diverge sharply. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Appraisal–arousal–behavior integration; motivational–affective coupling theories; reinforcement–emotion integration; stress–coping models; predictive-processing frameworks; cognitive–affective interaction theories. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Links to neuroscience (limbic systems, reward pathways), endocrinology (cortisol, adrenaline), behavioral economics (reward valuation), sociology (emotion norms), anthropology (cultural emotion scripts), and AI (reward/prediction-error models). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Manipulating emotional stimuli (images, sounds, narratives), altering motivational incentives, inducing stress, varying regulation strategies (reappraisal, suppression), modifying reward structures, or adjusting arousal levels to test causal effects on affective and motivational processes. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Observing spontaneous emotional responses, naturalistic coping behaviors, motivational persistence, stress responses, and real-world affect regulation without intervention; monitoring emotion–behavior associations. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Testing predicted emotion–arousal curves; validating motivational-drive effects on behavior; evaluating regulation-effort outcomes; confirming appraisal predictions; testing reward-prediction models; evaluating physiological–subjective convergence. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating emotion-induction tasks; replicating physiological measurements; reproducing regulation-effects across participants; validating reward-related behaviors in new samples; confirming stress responses in multiple paradigms. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Analyzing emotion intensity distributions; modeling arousal–recovery curves; computing effect sizes of regulation strategies; examining correlations between physiological and subjective affect; evaluating motivational persistence; fitting reinforcement/motivation models. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing appraisal vs physiological-first theories; contrasting motivational-drive models; evaluating predictive-processing vs reinforcement-based affect models; comparing regulation-strategy frameworks; assessing dual-process vs integrated affective models. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Noise in physiological sensors; variability in emotional responsiveness; inaccurate self-reports; habituation effects; participant fatigue; confounding motivational influences; unintended stimulus interpretation; calibration drift in instrumentation. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Randomizing stimuli; counterbalancing order effects; blinding experimenters; controlling for baseline affect; standardizing instructions; matching participants across demographic/clinical categories; minimizing demand characteristics. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Independent coding of emotional expressions; review of physiological preprocessing; replication across labs; evaluation of regulation-scoring procedures; critique of model assumptions; reassessment of theoretical interpretations. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating appraisal rules; revising motivational-drive models; refining regulation strategy taxonomies; modifying affect–behavior mapping assumptions; recalibrating reward-processing theories; incorporating new neuroscientific findings. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of stimuli sets, induction paradigms, reward structures, physiological-preprocessing steps, data exclusions, regulation-instruction scripts, and analytic parameters. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Ensuring emotional safety of participants; minimizing distress during induction; providing debriefing and support; maintaining confidentiality; avoiding coercive motivational incentives; ensuring accurate, non-misleading reporting. |