Science Analysis Template
These are the structural patterns found across all Scientific Disciplines
Carrier / Substance
This table identifies what actually carries choice in microeconomic analysis. A carrier here is the concrete unit to which preferences, constraints, and decision rules are attributed. Each binary isolates a different way that decision-bearing substance can be specified—individual or aggregate, discrete or continuous, stable or unstable—before any optimization or behavioral reasoning is applied. The table’s role is to lock down the bearer of choice, not the act of choosing.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Carrier / Substance – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Individual Agent | A single person or firm treated as the locus where preferences, constraints, and decisions reside. | household; worker; firm | Representative Population | A constructed aggregate treated as if it were a single chooser. | representative agent; market demand agent |
| Discrete / Continuous | Option Set | A finite set of distinct alternatives available to the chooser. | job offers; product menu; policy choices | Choice Interval | A continuous range over which a decision variable may vary. | quantity axis; hours-worked range |
| Equilibrium / Non-equilibrium | Settled Preference Structure | A stable ordering and constraint set that does not induce internal conflict. | stable tastes; fixed budget | Unsettled Preference Structure | A preference or constraint configuration in flux. | adapting consumer; learning firm |
| Open / Closed | Information-Exposed Agent | The chooser receives new information during the decision window. | job seeker; bargaining agent | Information-Isolated Agent | The chooser operates with fixed information for the decision. | sealed-bid participant; exam-taker |
| Deterministic / Stochastic | Rule-Bound Agent | Given inputs uniquely determine the decision. | strict optimizer; lexicographic chooser | Noise-Affected Agent | Decision outcomes include randomness or error. | random-utility consumer; mixed strategist |
| Local / Global | Situational Actor | Decisions depend only on immediate, local constraints. | impulse buyer; short-run firm | Plan-Bearing Actor | Decisions integrate long-horizon or cross-context constraints. | life-cycle planner; intertemporal investor |
| Linear / Nonlinear | Smooth-Response Agent | Small incentive changes induce proportional responses. | interior demand agent | Thresholded Agent | Small changes trigger discrete behavioral shifts. | participation decision-maker; credit cutoff borrower |
| Classical / Quantum | Preference-Defined Agent | Preferences are well-defined prior to choice. | neoclassical consumer | Preference-Constructed Agent | Preferences are formed or resolved during choice. | context-dependent chooser |
Taken together, the entries show that microeconomics does not operate on a single, universal decision-maker. Different models quietly switch carriers—individuals, representative aggregates, settled preference structures, noisy agents—often without acknowledgment. This matrix makes those assumptions explicit, preventing errors where properties of one carrier type are illegitimately transferred to another. By fixing the substance that carries choice, the analysis that follows remains structurally coherent rather than rhetorically convenient.
State / Phase
This table isolates choice-states as momentary configurations of decision-making. Each row classifies how a single decision condition behaves under a specific binary constraint—scale, continuity, equilibrium status, openness, uncertainty, scope, response shape, and behavioral regime. The binaries are ontological and fixed; what varies here is how a choice instantiates them. The result is a precise map of how individual decisions can exist, differ, and transition without importing assumptions from markets or macro systems.
SAT – Domain – Categories – Unified Ontological Binary Matrix – State / Phase – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Individual Decision State | The instantaneous configuration of a single agent’s feasible set, preferences, and beliefs at the moment of choice. | consumer bundle choice; worker hours decision; firm input selection | Aggregate Choice Configuration | The contemporaneous distribution of individual decision states across a population. | market demand curve; labor supply schedule |
| Discrete / Continuous | Categorical Choice State | A choice condition with a finite, mutually exclusive action set. | buy/not buy; enter/exit; brand A/B/C | Scalar Choice State | A choice condition where the action varies along a continuum. | quantity demanded; savings rate; effort level |
| Equilibrium / Non-equilibrium | Optimality-Satisfied State | Given constraints and beliefs, the chosen action has no profitable unilateral deviation. | utility-maximizing bundle; cost-minimizing input mix | Adjustment State | The agent is revising actions or beliefs because current choices are suboptimal under realized conditions. | post-price-shock reoptimization; belief updating |
| Open / Closed | Information-Admitting State | The choice condition allows new information or options to arrive during deliberation. | live bargaining; rolling job offers | Information-Sealed State | All relevant information and constraints are fixed for the decision interval. | sealed-bid choice; static consumer problem |
| Deterministic / Stochastic | Deterministic Mapping State | Inputs map to a single action under the agent’s decision rule. | argmax choice; dominant strategy | Probabilistic Choice State | Action is selected according to a probability rule due to noise, mixed strategies, or random utility. | logit choice; mixed strategies |
| Local / Global | Myopic Choice State | The decision is made without enforcing consistency across other decisions or time. | spot purchase; short-run consumption | Plan-Consistent Choice State | The decision enforces coherence across intertemporal or multi-constraint plans. | life-cycle saving policy; DP policy function |
| Linear / Nonlinear | Marginal-Response State | Small input changes induce proportional changes in the chosen action within the relevant region. | interior demand adjustment | Threshold / Corner State | Small input changes flip the chosen action due to kinks, cutoffs, or corners. | participation decision; zero/positive purchase |
| Classical / Quantum | Price-Taking Choice State | The agent treats prices and rules as given and ignores own impact on them. | competitive consumer or firm | Anticipatory Choice State | The agent conditions action on expected reactions of others or the mechanism. | auction bidding; Cournot quantity |
Taken together, these classifications show that choice is not a vague act but a well-typed state with a determinate structure at any moment. Different choice-states obey different constraints, respond differently to change, and fail for different reasons. This table makes those differences explicit, ensuring that when we later move to interaction or aggregation, we do not smuggle in properties that belong to choices themselves rather than to markets or systems built from them.
Process / Event
This table classifies changes through time in individual decision-making without naming or reusing the section label itself. Each row isolates a distinct way that decision-related change can unfold—by scale, continuity, stability, openness, uncertainty, scope, proportionality, and evaluative regime. The focus is not on decisions as static objects, but on how adjustments, revisions, and learning sequences actually progress under different structural constraints.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Process / Event – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Individual Deliberation Sequence | Time-ordered changes in evaluations or beliefs occurring within a single agent. | belief revision after price change; learning a preference ranking | Population Pattern Shift | Time-ordered changes in aggregate behavior emerging from many agents simultaneously. | adoption wave; demand reallocation across consumers |
| Discrete / Continuous | Action Switch Sequence | Change unfolds via jumps between distinct actions. | enter/exit; accept/reject over time | Intensity Adjustment Path | Change unfolds via smooth variation of a decision variable. | gradual quantity increase; savings drift |
| Equilibrium / Non-equilibrium | Convergent Update Sequence | Change dampens deviations and settles into a stable configuration. | learning to a fixed rule; habit stabilization | Driven Update Sequence | Change persists due to ongoing disturbances or shifts. | continual re-optimization under volatility |
| Open / Closed | Signal-Assimilation Sequence | Change shaped by continual arrival of external inputs. | updating after news; reacting to offers | Internally-Resolved Sequence | Change unfolds with fixed inputs and constraints. | solving a fixed maximization repeatedly |
| Deterministic / Stochastic | Rule-Following Update | Identical starts yield identical paths. | deterministic learning rule | Noise-Perturbed Update | Randomness alters the path despite identical starts. | experimentation; random-utility updating |
| Local / Global | Short-Horizon Revision | Change responds only to immediate feedback. | paycheck-to-paycheck adjustments | Plan-Consistent Revision | Change enforces coherence across time or constraints. | convergence to an intertemporal plan |
| Linear / Nonlinear | Proportional Revision | Small input changes yield proportionate effects. | marginal response to small price move | Threshold Crossing | Small inputs trigger abrupt shifts. | participation cutoff; default onset |
| Classical / Quantum | Evaluation-Stable Evolution | Criteria remain definite throughout the change. | standard neoclassical updating | Evaluation-Resolving Evolution | Criteria crystallize during the change itself. | framing-driven preference formation |
Read together, the entries show that changes in decision behavior are not a single kind of motion. Some revisions settle, others persist; some respond smoothly, others flip abruptly; some are driven entirely internally, others by continual external signals. By typing these forms explicitly, the table prevents collapsing all behavioral change into a generic “adjustment” story and fixes, in advance, what kinds of evolution a model is actually allowed to claim.
Structure / Configuration
This table characterizes the form of the decision space in microeconomic analysis. It focuses on how options, constraints, and tradeoffs are arranged, independent of how decisions are made or how they change over time. Each binary isolates a distinct structural property of the choice environment, making explicit the geometry, segmentation, stability, and scope of the configuration within which choice occurs.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Structure / Configuration – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Individual Preference Configuration | The internal arrangement of options, constraints, and rankings for a single decision-maker, where local structure determines feasible and preferred choices. | budget set with indifference curves; personal opportunity set | Aggregate Preference Configuration | A population-level arrangement formed by aggregating individual preference and constraint structures into a collective pattern. | market demand surface; income–preference distribution |
| Discrete / Continuous | Option Lattice | A decision arrangement composed of distinct, separable alternatives with explicit boundaries between choices. | product menu; job-offer list | Choice Continuum | A decision arrangement represented as a smooth space without discrete segmentation between options. | quantity–price space; hours–wage surface |
| Equilibrium / Non-equilibrium | Stable Preference Structure | An internally consistent arrangement of tradeoffs and constraints that resists reorganization under small disturbances. | settled tastes with fixed budget alignment | Reconfiguring Preference Structure | An arrangement undergoing internal reordering due to changing constraints, information, or valuations. | preference reshaping after income or price shock |
| Open / Closed | Externally Conditioned Layout | A decision structure whose form depends on incoming information or evolving constraints during evaluation. | expanding option set from new offers | Internally Fixed Layout | A decision structure whose form is fully determined by internal relations over the decision interval. | fixed exam-style choice set |
| Deterministic / Stochastic | Rule-Specified Layout | A preference arrangement defined by fixed evaluation rules that produce a predictable ordering. | lexicographic preferences; strict utility ranking | Probabilistic Layout | A preference arrangement shaped by noise, indeterminacy, or probabilistic comparison. | random-utility preference field |
| Local / Global | Context-Bounded Configuration | A structure defined over a limited subset of options or constraints relevant to a specific situation. | in-store purchase framing | Plan-Spanning Configuration | A structure integrating tradeoffs and constraints across time or multiple decision contexts. | lifetime consumption–saving map |
| Linear / Nonlinear | Proportional Tradeoff Geometry | A structure in which marginal substitutions preserve proportional response across the decision space. | smooth indifference curves | Kinked Tradeoff Geometry | A structure containing thresholds, corners, or discontinuities that distort proportional response. | minimum-consumption constraints; participation cutoffs |
| Classical / Quantum | Predefined Ordering Structure | A preference structure with fully specified rankings prior to evaluation. | standard rational preference ordering | Context-Resolved Ordering Structure | A preference structure whose ordering is partially determined during evaluation itself. | framing-dependent preference construction |
Taken together, the entries show that choice depends as much on how possibilities are structured as on preferences themselves. Different configurations admit different kinds of tradeoffs, thresholds, and consistency conditions, constraining what rational behavior can even mean. By fixing these structures explicitly, the table prevents structural assumptions from being smuggled into behavioral claims and establishes a clear foundation for analyzing interaction and aggregation without category error.
System / Assembly
This table specifies how coherence is achieved in a choice system. Each row identifies a distinct mechanism by which options, constraints, evaluations, and rules bind together into a whole that can be treated as a single decision problem. The focus is not on agents or behavior, but on the condition that makes a choice problem well-defined at all under different structural binaries.
SAT – Domain – Categories – Unified Ontological Binary Matrix – System / Assembly – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Feasible Set Closure | Coherence is achieved by resolving the intersection of options and constraints within a single bounded decision problem; the whole exists only insofar as feasibility is well-defined. | individual budget set; firm cost–output feasibility region | Aggregation Rule Closure | Coherence is achieved by a rule that combines many feasible sets into a single composite outcome space. | representative-agent construction; social welfare aggregation |
| Discrete / Continuous | Option Partition | Coherence arises from membership in a finite partition of mutually exclusive alternatives governed by selection rules. | menu choice; voting over candidates | Metric Domain | Coherence arises from continuity over a metric space where proximity and magnitude define admissibility. | quantity choice interval; effort continuum |
| Equilibrium / Non-equilibrium | Constraint Satisfaction Point | Coherence exists at configurations where all internal constraints and evaluations are jointly satisfied. | utility-maximizing bundle; cost-minimizing input mix | Constraint Conflict Field | Coherence fails because constraints and evaluations cannot be simultaneously satisfied, producing an unresolved system. | infeasible budget–preference pairing; contradictory objectives |
| Open / Closed | Externally Conditioned Problem Space | Coherence depends on inputs that originate outside the problem boundary, altering admissible configurations. | choice under learning signals; institution-dependent options | Self-Contained Problem Space | Coherence is fully determined by internally specified options, constraints, and rules. | sealed optimization problem; fixed parameter choice |
| Deterministic / Stochastic | Unique Resolution Mapping | Coherence is enforced by a mapping from inputs to a single admissible outcome. | strict preference ordering; lexicographic rule | Multiplicity Envelope | Coherence permits multiple admissible outcomes absent further specification, requiring randomization or selection. | random-utility representation; mixed admissibility set |
| Local / Global | Restricted Feasibility Window | Coherence is defined only over a limited subset of constraints or horizons. | short-run consumption feasibility; local choice frame | Cross-Constraint Closure | Coherence requires simultaneous satisfaction across linked domains or time periods. | intertemporal budget closure; life-cycle feasibility |
| Linear / Nonlinear | Additive Constraint Intersection | Coherence is produced by linear combination of constraints preserving proportional tradeoffs. | separable utility with linear budget | Binding Limit Topology | Coherence is shaped by kinks, corners, or thresholds that alter admissible configurations. | credit limits; minimum consumption constraints |
| Classical / Quantum | Pre-Specified Ordering Space | Coherence relies on an ordering that is fully defined prior to evaluation. | classical preference ordering | Evaluation-Dependent Ordering Space | Coherence depends on orderings that are partially constituted during evaluation itself. | context-dependent preference construction |
Read together, the entries show that a choice system is not a generic object but a coherence achievement that can succeed or fail in multiple ways. Feasibility closure, aggregation rules, metric continuity, constraint satisfaction, and ordering resolution each impose different limits on what outcomes are admissible. By fixing these system-forming mechanisms explicitly, the table prevents treating “choice” as a primitive and instead grounds it in the structural conditions that make decision problems intelligible.
Regime / Mode-of-Behavior
This table characterizes recurring behavioral regularities in choice—the ways decision behavior settles into repeatable forms over time. The focus is not on isolated decisions or static preferences, but on how patterns of choice stabilize, persist, or recur under different structural conditions. Each binary isolates a distinct mechanism by which repetition is maintained, whether through local routines, population-level regularities, smooth drift, abrupt switching, internal balance, or external entrainment.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Regime / Mode-of-Behavior – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Personal Routine | A recurring behavioral regularity stabilized by idiosyncratic conditions and local feedback within a single decision context. | same lunch purchase; habitual brand selection | Population Regularity | A recurring behavioral regularity that emerges at scale and persists despite individual variation. | stable demand elasticity; seasonal consumption cycles |
| Discrete / Continuous | State Alternation | Recurrence expressed as repeated transitions between a finite set of distinct actions. | participation on/off; buy vs abstain cycles | Behavioral Drift | Recurrence expressed as smooth modulation around a baseline without sharp transitions. | gradual quantity adjustment; slow savings shifts |
| Equilibrium / Non-equilibrium | Stable Attractor | A behavioral configuration that reproduces itself without internal tendency to change. | fixed labor supply; steady consumption share | Driven Orbit | A behavioral configuration that recurs only because persistent forces prevent settling. | continual re-optimization; unstable spending loops |
| Open / Closed | Externally Entrained Pattern | A recurring behavior synchronized to ongoing external signals or pressures. | promotion-driven purchasing; price-anchored shopping | Self-Maintained Routine | A recurring behavior sustained primarily by internal rules or habits. | rule-of-thumb budgeting; automatic saving |
| Deterministic / Stochastic | Reproducible Sequence | A recurrence in which identical conditions yield the same behavioral outcomes. | deterministic utility maximization | Exploratory Variability | A recurrence in which outcomes vary across repetitions despite similar conditions. | trial-and-error purchasing; random-utility choice |
| Local / Global | Situational Habit | A recurring behavior confined to a narrow context or environment. | impulse buying at checkout; situational indulgence | Cross-Context Disposition | A recurring behavior expressed consistently across multiple environments. | persistent frugality; long-term saving tendency |
| Linear / Nonlinear | Proportional Sensitivity | A recurrence in which behavioral change scales smoothly with incentives. | marginal price responsiveness | Threshold Activation | A recurrence structured around abrupt behavioral shifts once critical levels are crossed. | participation cutoffs; default triggering |
| Classical / Quantum | Preference Preservation | A recurring behavior governed by stable evaluative criteria across repetitions. | classical rational choice regularities | Preference Resolution | A recurring behavior in which evaluative criteria are settled through repeated engagement. | framing-dependent valuation patterns |
Taken together, the entries show that choice behavior does not recur in a single uniform way. Some regularities are idiosyncratic, others systemic; some reproduce smoothly, others hinge on thresholds; some are self-maintained, others synchronized to external signals. By distinguishing these regime forms explicitly, the table prevents collapsing all repeated behavior into generic “habits” or “preferences” and provides a precise vocabulary for describing how and why choice patterns endure.
Role / Function / Position
This table identifies functional positions inside a choice environment—the loci where influence is exerted over how options are evaluated, constrained, or selected. A role here is not an agent or a behavior, but a position within the decision structure that shapes outcomes by admitting, weighting, stabilizing, or perturbing choice. Each binary highlights a different way influence can be localized or system-shaping, categorical or graded, stabilizing or pressuring, internal or externally referenced.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Role / Function / Position – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Margin | The locus where a single tradeoff is evaluated locally, affecting one choice boundary at a time. | one more unit vs not; hour worked at the margin | Schedule | A system-wide mapping that organizes many margins simultaneously into a coherent pattern. | tax schedule; piecewise tariff |
| Discrete / Continuous | Gate | A categorical admission point that permits or denies options in stepwise fashion. | eligibility cutoff; accept/reject rule | Gradient | A graded influence that varies smoothly across intensities without categorical jumps. | price slope; utility gradient |
| Equilibrium / Non-equilibrium | Rest Point | A stabilizing locus where tradeoffs balance and no internal pressure forces change. | budget balance point; time allocation balance | Strain | A destabilizing locus where unresolved pressure persistently pushes choices away from rest. | debt burden; binding penalty |
| Open / Closed | Reference | An externally indexed locus that imports conditions from outside the decision frame. | market price; posted interest rate | Fixture | An internally fixed locus whose influence is determined wholly within the frame. | fixed preference ordering; internal rule |
| Deterministic / Stochastic | Rule | A mapping that yields a single admissible outcome for given inputs. | lexicographic priority; strict maximization | Sampler | A mapping that admits multiple admissible outcomes without further specification. | random tie-break; probabilistic choice |
| Local / Global | Frame | A context-limited locus whose influence applies only within a narrow setting. | in-store discount; situational cue | Horizon | A cross-context locus that links evaluations across settings or time. | lifetime income view; long-run goal |
| Linear / Nonlinear | Slope | A proportional influence where effects scale smoothly with intensity. | linear price response | Kink | A discontinuity where influence changes abruptly once crossed. | credit limit; participation cutoff |
| Classical / Quantum | Evaluator | A pre-specified ordering that ranks options independently of the act of choosing. | classical utility function | Resolver | An ordering that is settled during the act of choosing itself. | context-constructed valuation |
Taken together, the entries show that choice outcomes depend critically on which functional positions are active and how their influence is configured. Budgets, prices, rules, thresholds, and evaluators act as roles that channel decision-making in fundamentally different ways. By making these positions explicit, the table prevents conflating influence with preference or action and provides a precise vocabulary for describing how choice environments govern behavior before interaction or aggregation ever occurs.
Representation / Model-of-Reality
This table catalogs the distinct representational artifacts used to encode choice. Each row names a different kind of construct—maps, matrices, surfaces, frames, trees, schemas—that stands in for decision phenomena by emphasizing certain relations and suppressing others. The binaries specify how the artifact resolves detail, handles continuity, centers balance or pressure, admits context, encodes uncertainty, spans scope, preserves proportionality, and grounds ordering assumptions.
SAT – Domain – Categories – Unified Ontological Binary Matrix – Representation / Model-of-Reality – Choice (Microeconomic Foundations)
| Binary Class | First State Name | First State Definition | First State Examples | Second State Name | Second State Definition | Second State Examples |
|---|---|---|---|---|---|---|
| Micro / Macro | Indifference Map | A constructed surface that encodes individual tradeoffs by resolving fine-grained preference relations. | indifference-curve diagram | Demand Profile | A constructed curve that encodes population-level choice regularities while suppressing individual detail. | market demand curve |
| Discrete / Continuous | Choice Matrix | A tabular encoding where alternatives are enumerated as distinct, categorical options. | payoff matrix; menu table | Utility Surface | A continuous mathematical surface encoding valuation over a smooth domain. | utility function plot |
| Equilibrium / Non-equilibrium | Optimality Diagram | A graphical encoding centered on stationary choice configurations. | tangency diagram; Lagrangian solution | Pressure Landscape | A surface encoding deviations, gradients, or tensions away from stationary configurations. | excess-demand surface |
| Open / Closed | Signal-Augmented Frame | A representational frame that explicitly incorporates external inputs into the choice depiction. | expectation-augmented utility | Isolated Problem Frame | A representational frame that deliberately brackets external inputs. | sealed optimization problem |
| Deterministic / Stochastic | Decision Tree | A branching structure encoding a single outcome per input path. | deterministic decision tree | Probability Simplex | A geometric encoding of choice as a distribution over outcomes. | logit probability simplex |
| Local / Global | Neighborhood Approximation | A local mathematical encoding valid only near a reference point. | local linearization; point elasticity | Planning Schema | A unified encoding enforcing coherence across contexts or time. | life-cycle utility schema |
| Linear / Nonlinear | Linear Form | An algebraic encoding based on additive, proportional relations. | linear demand equation | Nonlinear Form | An algebraic encoding that preserves curvature, thresholds, or amplification. | CES utility function |
| Classical / Quantum | Fixed Ranking | A representation assuming evaluative order is fully specified prior to modeling. | classical preference ordering | Contextual Ordering | A representation where ordering is resolved within the act of evaluation. | framing-dependent valuation map |
Taken together, the entries show that modeling choice is an interpretive act: selecting an artifact fixes what is visible, what is ignored, and what counts as explanation. Indifference maps foreground tradeoffs; matrices privilege categorical comparison; landscapes expose tensions; trees force paths; schemas enforce coherence across time. By naming these artifacts explicitly, the table prevents category drift and makes the limits of each modeling move transparent before any analysis proceeds.