Well-foundedness is the property that every non-empty subset of a relation has a minimal element and no infinite descending chain exists, the structural guarantee that recursive reapplication of a step must terminate. That guarantee is defined relative to Recurrence — the repeated reappearance of a process or value across iterations or instances — because well-foundedness governs precisely how such repetition behaves. Without the recurrence pattern there is no descending chain to bound and well-foundedness has no content to assert.

Well-Foundedness presupposes Recurrence: descending chains and induction take meaning only against repeated reapplication of a step.


The well-foundedness argument that guarantees the predicate is reached (the resource-branch backstop). After the mathematics frame is stripped away, the retained structural roles are those of Termination Condition: An explicit, checkable predicate that decides whether an iterative or recursive process stops or continues. Well-Foundedness (Well-Ordering) adds the local frame and commitments expressed in its identity: Prevents infinite descent. The parent pattern remains recognizable without that vocabulary, while the child is the framed realization of it. That preservation test establishes decomposition rather than taxonomic subsumption.


Wild cards presuppose the black swan pattern because they share its defining combination -- rarity and outsized impact relative to routine outcomes -- and meaningfully exist only against the model in which most planning assumptions ignore tail events. The wild-card refinement is being nameable in prospect: unlike true black swans (unnameable until they occur), wild cards live on watchlists and risk registers as specific identifiable possibilities. Without the black swan framing of routine-model failure under tail dominance, wild card discipline has no point of leverage.

Wild cards presuppose the black swan pattern because they share its high-impact-from-low-probability signature while specializing to nameable-in-prospect events.


Wild cards is a specialization of foresight: it is one named methodology within the foresight stack for engaging plural possible futures, particularized to the case of low-probability high-impact events that are specifiable in advance. It inherits foresight's commitment to structured anticipation of multiple futures under uncertainty — turning the future into an object of disciplined inquiry — and operationalizes it through watchlists, registers, and scenario tests for nameable shock events that routine planning would otherwise miss.

Wild cards is a kind of foresight tool in which low-probability high-impact events are nameable and tracked in scenario planning.


Noisy appraisals determine selection, and conditioning on the winning estimate shifts its error toward the winning tail even when each appraisal was unbiased before the contest. The child adds several competitors or alternatives estimating one common or correlated value, an extremum selection rule, and a correction conditional on having beaten the field.

Winner's Curse is the common-value contest species that selects the maximum or minimum among several noisy estimates.


Winner-take-all is 'the specific case where the reward function is convex in rank near the top'; 'most competition is not winner-take-all (rewards often scale roughly with rank).' A strict specialization of competition by payoff-geometry. Competition supplies the genus: Rivalrous pursuit of a scarce prize where one party's gain is another's loss. Winner Take All Market preserves that general structure while adding its differentia: A payoff structure convex in rank concentrates most reward at the top, so small skill gaps produce vast reward gaps. The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association.


Increasing_returns is 'one of the most common SOURCES of winner-take-all convexity' (network effects, fixed-cost amortization) — but not identical (a fixed convex prize schedule produces it with constant returns). Increasing Returns supplies the prerequisite condition: Marginal benefit of each additional unit rises rather than falls as the cumulative state grows, compounding advantage. Winner Take All Market operates against that background: A payoff structure convex in rank concentrates most reward at the top, so small skill gaps produce vast reward gaps. If the parent condition is removed, the child relation becomes undefined or loses the mechanism asserted by this edge; the parent can obtain independently, so the relation is presupposition rather than subsumption. The typical qualifier limits the claim to the characteristic route, not a constitutive requirement of every instance; exceptions must retain the child's identity through another mechanism.


Wisdom of the crowds is the structurally-particularized form aggregation takes in the information-pooling case: many items (private signals) are collapsed into a unified form (the median or mean estimate) that retains the central tendency while suppressing individual error. It inherits aggregation's commitment to deliberate information loss with retained chosen features, particularized to the case where independence and diversity of inputs cancel individual error in expectation. Galton's ox-weight median is the canonical instance.

Wisdom of the crowds is the specific shape aggregation takes when many independent noisy signals are combined into a more accurate collective estimate.


Population Coding supplies the genus: Information about a quantity is carried by the joint pattern across many individually noisy elements and read out by a decoder, yielding precision and robustness no single element provides. Wisdom of the Crowds preserves that general structure while adding its differentia: Many independent noisy signals combine into an estimate better than any individual (information aggregation). The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association. The typical qualifier limits the claim to the characteristic route, not a constitutive requirement of every instance; exceptions must retain the child's identity through another mechanism.

Wisdom of the Crowds is typically a specialization of Population Coding, retaining the parent's defining structure while adding the child's specific commitments.


Constraint Release is the broader unmasking event in which removing a binding input reveals behavior previously held down. Withdrawal Rebound adds prior adaptive opposition, fast removal relative to compensation decay, and a transient excursion past baseline.

Withdrawal Rebound is Constraint Release specialized to a constraint that induced a slower opposing compensation before it was removed.


Pharmacological, endocrine, behavioral, and many policy examples adapt through setpoint-defending compensation. Engineered integrator wind-up can reproduce the same two-timescale release transient without a full biological homeostatic architecture, so the dependency is typical.

Withdrawal rebound typically depends on a homeostatic opponent-compensation loop left temporarily unopposed after input removal.


There is no rebound without prior accumulated opposing compensation. Stressor-Induced Adaptation supplies the build-up under sustained input; Withdrawal Rebound adds abrupt removal, timescale mismatch, and the opposite-direction overshoot.

Withdrawal rebound is the release phase of the compensation that Stressor-Induced Adaptation builds.


Ordinary design_prototyping builds a REAL but partial interior; wizard_of_oz specifically FAKES the interior with a concealed substitute and aims validation at experience not buildability. A specialized species (concealment and interior-absence) of design_prototyping. Design Prototyping supplies the genus: Early models for testing. Wizard Of Oz Prototyping preserves that general structure while adding its differentia: Validate a planned system cheaply by making its surface convincingly present while a hidden operator supplies the not-yet-built interior. The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association. The typical qualifier limits the claim to the characteristic route, not a constitutive requirement of every instance; exceptions must retain the child's identity through another mechanism.


Yield loss is conservation-closed deficit ACCOUNTING — it presupposes a balance/aggregation that forces named loss channels to sum to the deficit (mass/energy/cohort balance). Built on the partition-and-sum operation.


The decisive move is decomposing one deficit scalar into a partition of named, rankable, removable loss channels — a specialized decompose-and-attack protocol. Decomposition supplies the genus: Breaking a whole into parts that can be analyzed independently and recombined to reconstitute the whole, making complexity tractable through divide-and-conquer. Yield Loss preserves that general structure while adding its differentia: The gap between a transformation's theoretical maximum output and its realized output, decomposed under a balance constraint into named loss channels that sum to the deficit and can be ranked and attacked. The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association. The typical qualifier limits the claim to the characteristic route, not a constitutive requirement of every instance; exceptions must retain the child's identity through another mechanism.


ZKP fills verification's five-role schema (claim/protocol/challenge-response/transcript/verdict) with added zero-knowledgeness — a species of verification protocol, not a component of it. Verification supplies the genus: Check that an object conforms to its specification via a defined procedure yielding evidence and a verdict. Zero Knowledge Proof preserves that general structure while adding its differentia: Convince a verifier a claim is true while revealing nothing beyond its truth. The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association.


Zero-Sum Game classifies a strategic interaction by testing total payoff across alternative strategy profiles. It therefore requires players, their admissible Game-Theoretic Strategies, and the profiles those strategies form. The game is not itself a contingent policy from information to action; Strategy is required machinery for stating the invariant, not a merely typical association.

Every Zero-Sum Game strictly presupposes a strategy-profile space over which total payoff remains invariant.


Readiness Window supplies the genus: A receptive substrate enters a bounded opening-interior-closing interval during which a class of interventions can take hold. Zone of Proximal Development (ZPD) preserves that general structure while adding its differentia: Learn with guidance. The parent can occur without those added commitments, whereas removing the parent structure leaves no basis for classifying the child as this subtype. That asymmetry establishes subsumption rather than mere association. The typical qualifier limits the claim to the characteristic route, not a constitutive requirement of every instance; exceptions must retain the child's identity through another mechanism.

Zone of Proximal Development (ZPD) is typically a specialization of Readiness Window, retaining the parent's defining structure while adding the child's specific commitments.