Rationality

Version

v1 · 2026-09-08 · History

Prime #

1544

Aliases

Reason-responsiveness, Rational agency

Related primes

Bounded Rationality, Normativity, Decision, Evidence

Core Idea

Rationality is the structural quality of forming beliefs, choosing actions or governing procedures in a way that is answerable to reasons. A rational commitment is not simply one that succeeds or feels compelling. It connects available evidence, relevant aims, logical and practical constraints, and a norm for evaluation so that the commitment can be explained and revised. Philosophical accounts disagree over the final norm, but they converge on reason-responsiveness as the field's organizing problem.^[n1]

The Prime has seven load-bearing roles: an agent or decision process; representations of the situation; a set of accessible reasons or evidence; aims or truth-directed standards; feasible commitments; coherence and consequence tests; and a revision relation triggered by new information. Removing the normative standard turns rationality into mere behavioral prediction. Removing the information set judges agents by facts they could not access. Removing revision turns reasons into post-hoc decoration.

Rationality has epistemic and practical forms. Epistemic rationality concerns what to believe and how strongly, given evidence and standards oriented toward truth or knowledge. Practical rationality concerns what to intend or do, given ends, alternatives and expected consequences. The forms interact because action depends on belief and inquiry depends on practical allocation of attention, yet neither reduces without remainder to the other.

The structure is normatively plural. Deductive validity, probabilistic coherence, evidential support, expected utility, satisficing, procedural fairness and publicly defensible reason-giving can each govern a well-typed rationality judgment. Disagreement among standards does not erase the Prime; it makes standard declaration constitutive. Bounded rationality explains how limited agents use tractable strategies, but limitation is a qualification of rationality rather than its complete definition.^[1]

Rationality is also corrigible. Evidence can be misleading, objectives can be incomplete and coherent models can be wrong. A rational process is distinguished less by never erring than by calibrating confidence, seeking informative tests and changing when the balance of reasons changes. This creates the autonomous residual: disciplined connection and revision among reasons, commitments and norms across substrates.

Structural Signature

• Reason-bearing carrier: a person, group, institution, proof process or formal agent capable of holding or implementing commitments.
• Representation: an explicit or reconstructable model of circumstances, alternatives and consequences.
• Reasons and evidence: considerations that count for or against commitments under the selected norm.
• Normative standard: truth, coherence, expected value, duty, feasibility, public justification or another stated criterion.
• Information set: the evidence, computational capacity and options reasonably available at the time of judgment.
• Commitment: a belief, confidence level, intention, act, policy, inference or procedure that can be evaluated.
• Consistency and consequence: contradictions, dominance, feasibility and downstream implications are examined rather than hidden.
• Calibration: confidence and decisiveness are proportionate to evidential and model uncertainty.
• Revision: specified counterevidence or failed prediction can alter the commitment.
• Perspective declaration: whose aims and reasons govern the assessment is made explicit.
• Externalities and standing: practical assessments include affected parties and constraints that the agent cannot rationally erase by preference.
• Auditability: a reason chain can be reconstructed sufficiently to distinguish justification from rationalization.

What It Is Not

• It is not intelligence. Capacity for complex computation can serve irrational ends or sustain unsupported beliefs.
• It is not success. A well-supported decision can lose through bad luck, while an unreasonable gamble can succeed.
• It is not self-interest. Rational action can be altruistic, rule-governed or duty-bound when the operative reasons warrant it.
• It is not emotionlessness. Emotions can carry information and value; the question is how they enter evidence and reasons.
• It is not perfect optimization. Bounded agents can act rationally through satisficing and adaptive heuristics when optimization costs exceed its benefit.
• It is not consistency alone. A coherent set of false beliefs can lack evidential warrant, and a consistent plan can pursue an incoherent objective.
• It is not post-hoc explanation. Reasons invented after a commitment without causal or normative force are rationalization.
• It is not majority agreement. Consensus can be evidence under conditions, but shared bias does not become rational by counting supporters.
• It is not moral goodness. Instrumentally coherent pursuit of a wrongful end can be practically efficient yet morally impermissible.
• It is not omniscience. Judgment is indexed to accessible information and foreseeable consequences rather than hindsight.
• It is not one culture's style of expression. Quiet, narrative, mathematical and communal reason-giving can realize the structure differently.
• It is not a binary personality trait. Rationality is assessed by domain, task, information, time and degree.

Broad Use

Epistemic Belief Revision. The carrier contains an agent, evidence, competing propositions and confidence. A rationality assessment asks whether beliefs answer proportionally to evidence, coherence and calibrated uncertainty. The domain residual is truth-directed warrant, not mere confidence or social agreement. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Instrumental Decision Making. The carrier contains an actor, feasible acts, consequences, preferences and uncertainty. A rationality assessment asks whether the selected act is supported by consistent means-end evaluation under the actor's information. The domain residual is goal-sensitive choice, not a guarantee that the goal is morally worthy. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Scientific Inquiry. The carrier contains models, observations, rival explanations, error controls and communal criticism. A rationality assessment asks whether claims change when reproducible evidence and superior explanations warrant revision. The domain residual is publicly criticizable inference, not infallibility or one fixed method. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Organizational Governance. The carrier contains collective goals, stakeholders, forecasts, procedures, incentives and review. A rationality assessment asks whether decisions expose reasons, evidence, tradeoffs and revision triggers to affected evaluators. The domain residual is institutional reason-responsiveness, not the fiction of a unitary mind. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Engineering Design. The carrier contains requirements, alternatives, constraints, failure evidence and lifecycle outcomes. A rationality assessment asks whether design choices trace to explicit models, tests and proportionate margins. The domain residual is bounded optimization with safety duties, not numerical maximization alone. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Legal Reasoning. The carrier contains facts, rules, precedents, purposes, burdens and a reason-giving forum. A rationality assessment asks whether a conclusion follows through publicly articulated interpretation and evidence standards. The domain residual is doctrinal justification under authority, not identicality with scientific proof. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Everyday Planning. The carrier contains a person, desired ends, partial information, actions, costs and feedback. A rationality assessment asks whether plans are feasible, proportionate to evidence and revised after informative failure. The domain residual is practical responsiveness, not endless calculation. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

Machine Decision Systems. The carrier contains a formal objective, data, uncertainty model, policy, constraints and oversight. A rationality assessment asks whether outputs track the declared objective and evidence while uncertainty and misalignment remain auditable. The domain residual is formal coherence, not autonomous possession of human reasons. The reusable structure is literal: a reason-responsive agent or process holds representations, evaluates possible commitments against evidence and aims, chooses or revises, and remains answerable to counterevidence. What changes is the source of reasons and the consequence of error. A well-typed application states whose perspective and information set matter, which norm is used, and whether the judgment concerns a belief, an action, a procedure, or an institution.

These domains share a conserved decision signature without sharing one substantive objective. The signature asks: what commitment is being evaluated; which reasons were accessible; what rule determines relevance; which alternatives were feasible; how uncertainty was represented; and what evidence would change the result. This disciplined typing prevents a model that predicts behavior from being mistaken for a norm of good reasoning. It also prevents one domain's preferred metric—utility, posterior probability, legal validity or design margin—from colonizing every other use.^[n2]

Rationality assessments should therefore be two-layered. The internal layer asks whether the commitment follows coherently from the agent's beliefs, aims and constraints. The external layer asks whether those beliefs are evidence-sensitive, the aims are admissible for the evaluation, omitted stakeholders matter and the representation tracks reality. Internal coherence without external correction licenses sophisticated error. External success without a reconstructable internal relation may be luck. The Prime coordinates both while allowing a particular theory to emphasize one.

Collective rationality requires additional structure. Groups have distributed information, unequal standing, strategic incentives and aggregation rules. A policy cannot be called rational merely because a leader has reasons; the relevant process may require dissent, evidence transmission, conflict-of-interest control and public justification. Institutions instantiate the Prime through procedures that make reasons available, compare them and revise commitments. Their carrier is not a mystical group mind but a governed network of roles and records.

Formal rationality also needs boundaries. Expected-utility axioms, Bayesian coherence and optimization models deliver precise consequences once preferences, priors, utilities and feasible sets are typed. Those inputs are not self-validating. A model can prove an optimum relative to a misspecified objective, omit nonquantified harms or express false precision. Rationality uses formal methods as powerful local certificates while retaining responsibility for representation, evidence and scope.

Finally, rationality is temporal. Inquiry has costs, deadlines and option value. Gathering one more fact can be rational when it may reverse a high-stakes decision and irrational when delay itself destroys value. The stop rule belongs inside the analysis. A process that demands impossible certainty is no more rational than one that acts on the first convenient story. Proportionate inquiry, calibrated commitment and explicit revision triggers provide the transferable middle structure.

Clarity

A clear rationality claim names the object of evaluation. Beliefs are assessed for evidence and coherence; actions for means-end fit and admissible constraints; procedures for how they gather reasons and correct error. Moving silently among these objects makes familiar disputes look deeper than they are.

The claim also declares the perspective and time. Ex ante rationality uses information available before the outcome. Ex post evaluation can reveal model failure but should not rewrite what was knowable. Individual, organizational and social perspectives can rank the same act differently because aims, standing and externalities differ.

Norms must be stated rather than smuggled in. 'Rational' may mean deductively valid, probabilistically coherent, utility maximizing, evidence proportioned, strategically stable or publicly justifiable. Each is a genuine but partial criterion. The Prime supplies a grammar for relating them: carrier, representation, reasons, standard, commitment, consequence and revision.

Confidence language should reflect uncertainty. Rationality can support a probability, a provisional policy or a robust set of options rather than one categorical conclusion. A transparent interval with a revision plan can be more rational than a precise point estimate produced by an untested model.

Manages Complexity

Rationality compresses an open field of facts into a decision-relevant representation. It filters evidence by relevance, groups consequences by aim and constraint, and narrows alternatives without pretending that excluded detail never matters. The compression is accountable because its selection rule and residual uncertainty remain visible.

It separates object-level reasons from meta-level allocation. An analyst reasons about which bridge design is safest while also deciding how much analysis, testing and consultation the decision warrants. Bounded resources make the meta-level unavoidable. Rationality coordinates them by comparing the expected value of further inquiry with delay and computation costs.

It converts conflict into structured disagreement. Parties may disagree about facts, probabilities, values, feasible options or standing. Labeling one another irrational hides the locus. A reason map reveals which premise or norm must change for convergence and which disagreements are legitimately plural.

It manages model risk by preserving a residual category. Unmodeled outcomes, adversarial adaptation and distribution shift cannot always be assigned credible probabilities. Robust choice, scenario analysis and reversible commitments acknowledge that ignorance rather than entering arbitrary numbers to complete an optimization.

The main hazard is rationalistic overreach: mistaking what is legible to a chosen model for all that is real. The correction is a representation audit, independent criticism and outcome feedback. Rationality is not maximal calculation but disciplined answerability of calculation and judgment to the world.

Abstract Reasoning

1. Type the commitment as belief, confidence, intention, act, policy, inference or procedure; different norms attach to each.
2. Fix the temporal information set and distinguish inaccessible facts from ignored available evidence.
3. List feasible alternatives, including delay, information gathering and reversible experiments when they are genuine options.
4. State the evaluative standard and identify which aims or values it treats as inputs rather than conclusions.
5. Trace each material reason to evidence, authority, model or stakeholder standing and record uncertainty and dependence.
6. Test internal coherence, dominance, feasibility and consequence without assuming those tests exhaust external warrant.
7. Search for omitted variables, affected parties, counterexamples and model-breaking cases through independent criticism.
8. Compare robustness across plausible beliefs and values rather than optimizing one fragile point model only.
9. Choose a proportionate stopping rule for inquiry based on stakes, delay cost and value of additional information.
10. Commit at calibrated strength, retaining options when evidence does not warrant irreversible precision.
11. Specify observations or arguments that would trigger revision and assign responsibility for monitoring them.
12. Audit outcomes without hindsight bias, updating the model while separately judging the original ex ante process.

Knowledge Transfer

The transfer skeleton is stable: an agent or process represents a situation, receives reasons, evaluates commitments under a norm, acts or believes at calibrated strength, observes consequences and revises. Transfer succeeds when each target domain supplies literal occupants for those roles. It fails when 'rational' is used only as praise, when one domain's metric replaces the target's norm, or when a successful outcome is treated as proof of a sound process.

From science to management, evidential responsiveness transfers literally, but replication becomes operational monitoring and peer criticism becomes structured dissent. From decision theory to engineering, feasible acts and consequences transfer, but safety constraints and lifecycle duties cannot be compressed into a private utility without argument. From individuals to institutions, reasons transfer through documents, meetings and procedures rather than a single consciousness.

The strongest transfer test is counterfactual. Ask what new evidence would change the commitment and how the process would encounter it. If no answer exists, the target may imitate reason language while lacking revision structure. Then ask what alternative standard would yield a different decision. This reveals whether the judgment is robust or depends on an undeclared normative choice.

Rationality also transfers as an error taxonomy: representation error, evidential neglect, inferential inconsistency, objective misspecification, option omission, externality exclusion, overconfidence, premature stopping and revision failure. These categories support diagnosis without assuming one universal algorithm. Domain practices can supply their own tests while conserving the role structure.

Transfer remains bounded by expertise and legitimacy. A procedure may be technically coherent yet lack authority to choose whose welfare counts. A person may have valid values yet use a false causal model. Rationality organizes the interface; it does not manufacture evidence, moral standing or democratic consent by definition.

Examples

1. In epistemic belief revision, begin with an agent, evidence, competing propositions and confidence. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether beliefs answer proportionally to evidence, coherence and calibrated uncertainty; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains truth-directed warrant, not mere confidence or social agreement.
2. In instrumental decision making, begin with an actor, feasible acts, consequences, preferences and uncertainty. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether the selected act is supported by consistent means-end evaluation under the actor's information; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains goal-sensitive choice, not a guarantee that the goal is morally worthy.
3. In scientific inquiry, begin with models, observations, rival explanations, error controls and communal criticism. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether claims change when reproducible evidence and superior explanations warrant revision; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains publicly criticizable inference, not infallibility or one fixed method.
4. In organizational governance, begin with collective goals, stakeholders, forecasts, procedures, incentives and review. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether decisions expose reasons, evidence, tradeoffs and revision triggers to affected evaluators; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains institutional reason-responsiveness, not the fiction of a unitary mind.
5. In engineering design, begin with requirements, alternatives, constraints, failure evidence and lifecycle outcomes. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether design choices trace to explicit models, tests and proportionate margins; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains bounded optimization with safety duties, not numerical maximization alone.
6. In legal reasoning, begin with facts, rules, precedents, purposes, burdens and a reason-giving forum. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether a conclusion follows through publicly articulated interpretation and evidence standards; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains doctrinal justification under authority, not identicality with scientific proof.
7. In everyday planning, begin with a person, desired ends, partial information, actions, costs and feedback. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether plans are feasible, proportionate to evidence and revised after informative failure; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains practical responsiveness, not endless calculation.
8. In machine decision systems, begin with a formal objective, data, uncertainty model, policy, constraints and oversight. Identify the candidate commitment, the accessible reasons and the normative standard. Test whether outputs track the declared objective and evidence while uncertainty and misalignment remain auditable; then expose uncertainty, omitted options and the observation that would rationally require revision. This maps to the Prime as agent or process → representations → reasons → evaluative norm → commitment → feedback and revision. The boundary remains formal coherence, not autonomous possession of human reasons.
9. A household choosing insurance compares premiums, loss exposure, liquidity and uncertainty. The least expensive policy is not automatically rational if it leaves a ruinous uncovered tail, and the most comprehensive policy is not automatically rational if its cost displaces essential needs. The mapping is agent → financial representation → evidence and risk preference → feasible policies → calibrated commitment → later revision as circumstances change.
10. A research team receives a result that contradicts its favored model. Rationality does not require immediate abandonment or defensive dismissal. It requires checking measurement validity, updating confidence proportionally, seeking discriminating replication and stating what evidence would change the model. The mapping conserves belief, evidence, norm, uncertainty and revision.
11. A public agency faces a low-probability high-consequence hazard. Expected value is one consideration, but distributional burden, legal duty, irreversibility and public reason also constrain the decision. Scenario analysis and staged reversible action can be rational when probability estimates are fragile. The Prime explains the structure without dictating one policy.

Structural Tensions

• Epistemic versus instrumental: evidence can warrant a belief that frustrates an agent's preferred action.
• Optimization versus boundedness: more computation can improve a model while delaying action or consuming the value sought.
• Internal coherence versus external truth: a consistent system can be built on false premises.
• Individual versus collective: one actor's coherent gain can impose costs that a social assessment must include.
• Universal norms versus contextual reasons: formal invariants travel, but relevant values and evidence are situated.
• Precision versus robustness: a sharp optimum can be less defensible than a resilient range under uncertainty.
• Commitment versus corrigibility: action requires closure while learning requires openness to revision.
• Transparency versus cognitive load: complete reason trails can overwhelm the people meant to evaluate them.
• Heuristic efficiency versus bias: shortcuts can be ecologically rational yet systematically fail under changed conditions.
• Expertise versus legitimacy: technical competence does not alone authorize value choices for others.

Structural–Framed Character

Rationality sits at the framed end of the structural–framed spectrum. It assesses whether beliefs, actions, or procedures answer appropriately to accessible reasons, evidence, aims, constraints, and revision requirements, so the operative standard—deductive validity, evidential support, expected utility, fairness, or public justification—is constitutive.

Its vocabulary changes across epistemic belief revision, practical choice, scientific inquiry, legal reasoning, and organizational governance. The concept is explicitly evaluative, distinguishing warranted commitments from poorly reasoned ones without equating rationality with success. Philosophical traditions and institutions stabilize its standards and forums of accountability. Its central cases arise in human reason-giving and coordinated decision practice. Applying rationality requires selecting the norm and information set through which conduct is interpreted, rather than simply recording observable behavior. All five diagnostics therefore point to framing.

Substrate Independence

The substrate-independence claim is strong but bounded. Persons, scientific communities, courts, engineering teams and formal agents all instantiate the same role graph: representation, reasons, standard, commitment, consequence and revision. The graph supports the same diagnostics—coherence, evidence sensitivity, calibration, option completeness and corrigibility—even though cognition, procedure and code realize them differently.

The Prime does not require that every substrate literally experiences reasons. A machine policy can be assessed for formal rationality because its objective, evidence model and update rule occupy functional roles, while claims about consciousness remain separate. An institution can be assessed through procedures and records without pretending it has a single mind. Functional transfer is legitimate because the evaluation concerns relations among representations and commitments.

Substrate independence would fail if rationality meant one biological capacity, one Western rhetorical style or one optimization algorithm. The entry explicitly rejects those reductions. It preserves cultural and normative variation by requiring the standard and standing to be declared. Variation occurs inside the frame rather than erasing it.

The limiting boundary is normativity. A thermostat can minimize temperature error, but calling it rational adds little unless there are competing representations, reasons or revision standards at the relevant grain. Simple feedback is not automatically rational agency. The Prime becomes informative when a process can be evaluated across alternative commitments under reasons and uncertainty.

Relationships to Other Abstractions

Current abstraction Rationality Prime

Parents (1) — more general patterns this builds on

• Rationality is a kind of Normativity Prime

  The accepted reference-grade review places Rationality under Normativity because the child instantiates or depends on the parent's broader structure while retaining its own constitutive identity.

Children (8) — more specific cases that build on this

• Argument to moderation Domain-specific is a kind of Rationality

  The proposed strict upward parent is prime:rationality.

• Critical thinking Domain-specific is a kind of Rationality

  The proposed strict upward parent is prime:rationality.

• Lottery paradox Domain-specific is a kind of Rationality

  The proposed strict upward parent is prime:rationality.

▸ Show 5 more

Hierarchy path (1) — routes to 1 parentless root

• Rationality → Normativity → Constraint

Neighborhood in Abstraction Space

Rationality sits among the more crowded primes in the catalog (21^st percentile for distinctiveness): several abstractions describe nearly the same structure, so a description that fits it will tend to fit its neighbors too — transporting it usually means disambiguating within this family rather than landing on it exactly.

Family — Preference, Utility & Choice (18 primes)

Nearest neighbors

• Causal reasoning — 0.75
• Strategic thinking — 0.73
• Suspension of judgment — 0.73
• Due diligence — 0.73
• Truth value — 0.73

Computed from structural-signature embeddings · 2026-09-10

Not to Be Confused With

• Bounded rationality: a family of accounts of rational choice under cognitive and informational limits; it qualifies the broader rationality structure.
• Intelligence: capacity to learn or solve problems, which can be used in ways that are poorly reasoned or normatively misdirected.
• Reasoning: the process of drawing or assessing conclusions; rationality evaluates how that process and its commitments answer to norms.
• Optimization: selection of a best value in a formal model; rationality also evaluates the model, objective, information cost and omitted constraints.
• Rationalization: production of apparently acceptable reasons after a commitment when those reasons did not govern or warrant it.
• Logic: validity relations among propositions; rationality includes logic but also evidence, uncertainty, aims and revision.
• Self-interest: promotion of an agent's welfare; rationality can organize altruistic, moral or collective commitments.
• Success: favorable outcome; outcome luck and process quality must be evaluated separately.
• Consensus: agreement among people; rationality depends on how agreement was formed and responds to evidence.
• Objectivity: practices that reduce perspective-dependent distortion; rationality is broader and can include acknowledged values and first-person reasons.

The prospective workspace queue contains one strict upward edge to prime:normativity. No live DAG mutation is authorized.

Solution Archetypes

No catalogued solution archetypes reference this prime yet.

Notes

[n1] Source cited in the frozen article, 'Definition of rational'. ↩

[n2] Source cited in the frozen article, 'The American Heritage Dictionary entry: irrational'. ↩

References

[1] Kate Nolfi, 'Which Mental States Are Rationally Evaluable, And Why?', Philosophical Issues, 2015, doi:10.1111/phis.12051. registry ↩