Introduction
i / 65
The complementarity question
This document maps where the Execution Economics (EE) framework — built on the core identity Y = S · d(P) with sovereignty operationalised through the canonical Decision Sovereignty Index DSI = ∛(A · C · E) · (1 − V) — stands in relation to the principal theoretical traditions it draws on, refines, or extends.
The relationship is rarely replacement. In most cases EE supplies a missing variable (sovereignty, transmission), a missing functional form (the weakest-link min, the logistic congestion function, the geometric-mean DSI), or a missing scope condition that the host theory had implicitly assumed away.
The decisive test applied across 64 traditions is simple: can a given framework account for conditions in which a well-informed, analytically sound and properly authorised decision produces outcomes systematically opposite to those intended — that is, can it generate S < 0? On a more permissive reading the answer is mixed — some traditions (Goodhart, Campbell, Merton, capture theory) do contain mechanisms by which negative outcomes can arise. On the more specific reading that frames EE’s claim, no surveyed tradition independently formalises a signed transmission operator inside a production identity for realised institutional output. The argument is therefore one of formal specificity, not conceptual originality. This is the convergent-impossibility argument.
Verdict key. Each tradition is scored against this strict test on a three-tier scale. No — no signed production identity for realised institutional output. Partial — has an inversion or backfire concept but does not formalise it as a signed transmission operator inside a production identity. Yes — independently formalises signed transmission inside a production identity. Implicit — the institutional engineering is anticipated normatively (e.g., constitutional design of veto structures) without a signed production identity. Under this scale, the convergent-impossibility argument is the empirical observation that no surveyed tradition reaches Yes.
DSI = ∛(A · C · E) · (1 − V)
Authority · Control · Execution-relevant Information, scaled by veto-freedom
Reading guide
The 64 traditions are organised into 23 families grouped under three blocks: Core (F1–F6) covering economic and organisational theory; Extended (F7–F15) covering allied disciplines from game theory to neuroscience; and New EE-Impacted (F16–F23) covering domains where EE has clear application but is not specifically referenced in the EE source corpus — development economics, project management, regulatory science, corporate governance, monetary policy, public health, AI safety, and performativity / unanticipated consequences (Goodhart, Campbell, Merton).
Each tradition is given a full page treatment with four blocks: what the host theory explains, what it cannot explain, what EE adds, and where in the EE corpus the comparison is grounded. Where pages show "Not source-attested", the comparison is offered as an extension of the framework, not a claim made in the source corpus.
Source documents cited per page: Decision Sovereignty (Fritz, Fritz-Kalish & Bodrova, 2026 monograph); Execution Age (manuscript); Extended Position (positioning document).
Core · Family 1
F1 cover
Core family
F1/ 23
Institutional and New Institutional Economics
4 traditions in this family
F1 · Institutional and New Institutional Economics
01 / 64
Core · F1 · Institutional and New Institutional Economics
Transaction-cost economics
Coase (1937), The Nature of the Firm; Williamson (1985), The Economic Institutions of Capitalism
What the theory explains
Why firms exist; how transaction costs determine make-or-buy boundaries; how asset specificity shapes governance.
What it cannot explain
Treats decision authority as uncontested once firm boundaries are drawn. Cannot explain why optimal Coasean boundaries still fail to execute.
What EE adds
S = f(A, C, E, V)
Supplies signed sovereignty S decomposed into A (Authority), C (Control), E (Execution-relevant Information) and V (Veto exposure). High transaction cost attenuates ∛(A · C · E) · (1 − V) but does not invert it.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3 Theoretical forebears
Execution Economics (2026 monograph) I.2.1; 1.4
F1 · Institutional and New Institutional Economics
02 / 64
Core · F1 · Institutional and New Institutional Economics
Property rights and institutional history
North (1990), Institutions, Institutional Change and Economic Performance; Acemoglu & Robinson (2012), Why Nations Fail; Acemoglu, Johnson & Robinson (2001)
What the theory explains
Why some societies sustain growth; inclusive vs extractive institutions; property-rights regimes and long-run outcomes.
What it cannot explain
Conflates decision quality with execution capacity. "Inclusive" vs "extractive" is a design taxonomy, not an execution measure. The USSR was extractive yet high-execution.
What EE adds
sign(S_net)
Separates d(P) from S. Same DSI magnitude can carry opposite signs: USSR had high ∛(A · C · E) but mission-extractive S, producing S < 0; post-colonial states show inclusive design with low E and high V.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3 Theoretical forebears
Execution Age (manuscript) Ch. 3 The Missing Variable
Execution Economics (2026 monograph) I.2; 4.4.1
F1 · Institutional and New Institutional Economics
03 / 64
Core · F1 · Institutional and New Institutional Economics
Commons governance
Ostrom (1990), Governing the Commons; Hardin (1968), "Tragedy of the Commons"
What the theory explains
How shared resources are governed without privatisation or state control; design principles for self-organising communities.
What it cannot explain
Design principles are necessary preconditions for sovereignty but silent on congestion in shared decision channels.
What EE adds
χ(ρ) congestion friction
Extends to a tragedy of the decision commons: shared institutional channels overload, generating congestion friction χ(ρ) that compresses C and E inside the cube root of the DSI.
EE source documents
Execution Economics (2026 monograph) 5.4.2; 5.4.3
F1 · Institutional and New Institutional Economics
04 / 64
Core · F1 · Institutional and New Institutional Economics
Veto-player theory
Tsebelis (2002), Veto Players
What the theory explains
How veto-player count and ideological distance shape policy stability and the probability of policy change.
What it cannot explain
Treats veto as an exogenous structural fact. Cannot specify the signed effect of veto accumulation on output direction.
What EE adds
(1 − V) multiplier
V enters as the (1 − V) multiplier on the cube root of (A · C · E), endogenising veto as a proportional drag on the geometric mean of execution capacity rather than a simple subtraction.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3; Ch. 6.1
Execution Economics (2026 monograph) 2.6
Core · Family 2
F2 cover
Core family
F2/ 23
Bounded rationality and behavioural economics
4 traditions in this family
F2 · Bounded rationality and behavioural economics
05 / 64
Core · F2 · Bounded rationality and behavioural economics
Bounded rationality
Simon (1955, 1976), Administrative Behavior; March & Simon (1958), Organizations
What the theory explains
Decision-makers satisfice rather than maximise; organisational processes differ from frictionless choice.
What it cannot explain
Identifies the cognitive mechanism without production-theoretic consequences. Does not specify when satisficing inverts institutional output.
What EE adds
d(P) = P^α
Recasts as the decision-production function d(P) = P^α capturing degradation under load. The α exponent is governed by cognitive capacity and feeds into d(P) multiplied against ∛(A · C · E) · (1 − V).
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3
Execution Economics (2026 monograph) 1.3.2; 1.4
F2 · Bounded rationality and behavioural economics
06 / 64
Core · F2 · Bounded rationality and behavioural economics
Heuristics, biases, prospect theory
Kahneman & Tversky (1979), "Prospect Theory"; Kahneman (2011), Thinking, Fast and Slow
What the theory explains
Systematic deviations: loss aversion, framing, anchoring; System 1 vs System 2 cognition.
What it cannot explain
Diagnoses individual-level deficiencies without connecting to institutional output. Biases affect d(P) but the framework is silent on S.
What EE adds
α shift under load
Reads System 1/2 as a shift in α under cognitive load. System 1 dominance under institutional stress reduces d(P) and indirectly degrades S via governance curvature κ that attenuates C and E.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 3 The human factor; Ch. 4.3
Execution Age (manuscript) Ch. 3
F2 · Bounded rationality and behavioural economics
07 / 64
Core · F2 · Bounded rationality and behavioural economics
Decision fatigue and the Yerkes–Dodson Law
Yerkes & Dodson (1908), "The Relation of Strength of Stimulus to Rapidity of Habit-Formation" (mouse discrimination learning under shock; the inverted-U "law" is a later generalisation); Vohs et al. (2008), "Making Choices Impairs Subsequent Self-Control"
What the theory explains
Cognitive resources depleted by use; arousal-performance inverted-U; performance declines as stress rises beyond an optimum.
What it cannot explain
Individual-level phenomenon without an institutional aggregation model. Cannot predict when accumulated fatigue produces sign reversal at system level.
What EE adds
S(L) = e^(−κL²)
Aggregates into governance curvature S(L) = e^(−κL²) at institutional scale, where L is decision intensity. The curvature compresses ∛(A · C · E) · (1 − V) under sustained load.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 3.2 Yerkes-Dodson; Appendix Notations
F2 · Bounded rationality and behavioural economics
08 / 64
Core · F2 · Bounded rationality and behavioural economics
Garbage-can model
Cohen, March & Olsen (1972); March & Olsen (2010), Rediscovering Institutions
What the theory explains
High-volume decisions decouple from analysis and reflect coincidence, political negotiation and accident.
What it cannot explain
Descriptive. Cannot distinguish random decoupling from systematic signed inversion of institutional intent.
What EE adds
α → 0 as ρ → ρ*
Formalises as α → 0 as decision volume rises relative to capacity, connecting to the congestion regime ρ > ρ*. Garbage-can dynamics are the overload limit of the EE production function and pull E toward zero inside the cube root.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3
Execution Economics (2026 monograph) 5.1; 5.2
Core · Family 3
F3 cover
Core family
F3/ 23
Organisational economics, contract theory, mechanism design
5 traditions in this family
F3 · Organisational economics, contract theory, mechanism design
09 / 64
Core · F3 · Organisational economics, contract theory, mechanism design
Information economics and contract theory
Akerlof (1970), "Market for Lemons"; Holmström (1979); Holmström & Milgrom (1991); Stiglitz (2000)
What the theory explains
Asymmetric information shaping markets and contracts; signalling, screening; multitask principal-agent design.
What it cannot explain
Treats information as the primary friction and assumes authority is intact post-contract. Does not address partial, contested or vetoed authority.
What EE adds
S as missing variable
Supplies the missing S: even with perfectly aligned incentives (Holmström optimum), if (1 − V) → 0 then DSI → 0 and Y collapses regardless of d(P). Incentive alignment is not transmission fidelity.
EE source documents
Execution Economics (2026 monograph) I.2.2
Decision Sovereignty (2026 monograph) Ch. 5.2 Limits of existing frameworks
F3 · Organisational economics, contract theory, mechanism design
10 / 64
Core · F3 · Organisational economics, contract theory, mechanism design
Principal–agent theory
Holmström (1979), "Moral Hazard and Observability"; Hart and successors
What the theory explains
Divergence between principal and agent objectives under asymmetric information; alignment via incentive design.
What it cannot explain
Even when incentives are aligned and decisions are implemented as intended, outcomes can still diverge from those sought. Operates on alignment of decisions rather than on transmission of effects.
What EE adds
Signed transmission
Provides the signed transmission variable that closes the gap. Robodebt-class cases show faithful execution producing inverted outcomes: high d(P) and aligned incentives yet ∛(A · C · E) · (1 − V) carrying a negative net sign through the alignment vector.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.2 Principal–agent; Ch. 5.4 Execution reversal
Execution Economics (2026 monograph) 6.3; 18.4
F3 · Organisational economics, contract theory, mechanism design
11 / 64
Core · F3 · Organisational economics, contract theory, mechanism design
Organisational architecture and formal vs real authority
Milgrom & Roberts (1990); Aghion & Tirole (1997), "Formal and Real Authority"
What the theory explains
Decision-rights allocation, incentive configuration, complementarities; the gap between formal and real authority.
What it cannot explain
Assumes that once allocation is correct, implementation follows. Formal authority A on its own is not decision sovereignty.
What EE adds
A inside ∛(A · C · E)
A is one of three positive components inside the cube root. Aghion & Tirole's formal/real gap is decomposed: formal authority absent C or E still yields low DSI even before V is applied.
EE source documents
Execution Economics (2026 monograph) 1.4; 2.2.3
F3 · Organisational economics, contract theory, mechanism design
12 / 64
Core · F3 · Organisational economics, contract theory, mechanism design
O-ring theory
Kremer (1993), "O-Ring Theory of Economic Development"
What the theory explains
Weakest-link production; quality complementarities; assortative matching; small task-quality differences generate large output differences.
What it cannot explain
Formally identical to EE's weakest-link transmission structure but only for positive output. Cannot represent reversal when the weakest link turns hostile.
What EE adds
Signed O-ring extension
EE absorbs Kremer's weakest-link structure into the cube-root composite (each of A, C, E behaves O-ring-like; if any approaches zero the whole composite collapses) and adds a signed extension under which mission-extractive components invert rather than merely reduce output.
EE source documents
Execution Economics (2026 monograph) 7.4.3
F3 · Organisational economics, contract theory, mechanism design
13 / 64
Core · F3 · Organisational economics, contract theory, mechanism design
Mechanism design and Pigovian pricing
Pigou (1920); Hurwicz (1973); Maskin (1999); Maskin & Tirole (1999); Laffont & Tirole (1993)
What the theory explains
Internalising externalities through prices and mechanisms; regulator incentive design; conditions for implementability.
What it cannot explain
Implementation theory is binary — a mechanism either yields the intended outcome or it does not. The framework specifies the conditions under which outcomes can be achieved but not the fidelity with which they are preserved in execution.
What EE adds
Continuous signed fidelity
Replaces binary implementability with continuous signed fidelity ∛(A · C · E) · (1 − V) ∈ [−1, 1]. Identifies cases where institutional architecture prevents an otherwise-implementable mechanism from operating, locating the failure in V and E rather than in the mechanism itself.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.2 Mechanism design
Execution Economics (2026 monograph) 5.4.3
Core · Family 4
F4 cover
Core family
F4/ 23
Operations research, queueing theory, management practices
6 traditions in this family
F4 · Operations research, queueing theory, management practices
14 / 64
Core · F4 · Operations research, queueing theory, management practices
Queueing theory
Kleinrock (1975), Queueing Systems; Little's law and successors
What the theory explains
Non-linear waiting times as utilisation approaches capacity; service disciplines; convex congestion.
What it cannot explain
Fixed institutional structure with no alignment or sovereignty layer. Models delay but not inversion of throughput direction.
What EE adds
Logistic χ(ρ)
Imports queueing dynamics into the congestion regime via the logistic specification χ(ρ) = 1/(1 + exp(−γ(ρ − ρ_c))). EE adds the signed sovereignty layer absent from queueing theory: even uncongested systems can deliver ∛(A · C · E) · (1 − V) < 0 when alignment is hostile.
EE source documents
Execution Economics (2026 monograph) 5.1.2; 5.1.3; 10.2.3
F4 · Operations research, queueing theory, management practices
15 / 64
Core · F4 · Operations research, queueing theory, management practices
Operations research / linear programming
Dantzig (1947); general optimisation tradition
What the theory explains
Optimisation within constraints: scheduling, routing, pricing, staffing; finding the feasible optimum.
What it cannot explain
Presumes the structural capacity to implement the optimal solution. The constraint set is exogenous; OR does not explain how constraints arise or differ across organisations.
What EE adds
Endogenous constraints
Endogenises the constraint set. The OR feasible region corresponds to the region where ∛(A · C · E) · (1 − V) > 0; outside it, the optimal solution cannot be transmitted regardless of its mathematical correctness.
EE source documents
Execution Economics (2026 monograph) P.2 Scope, Claims, and Non-Claims
F4 · Operations research, queueing theory, management practices
16 / 64
Core · F4 · Operations research, queueing theory, management practices
Management practices empirics
Bloom & Van Reenen (2007); Bloom, Eifert, Mahajan, McKenzie & Roberts (2013)
What the theory explains
Cross-country and cross-firm management-practice variation correlated with productivity.
What it cannot explain
Unsigned quality scores. Cannot diagnose reversal: mission-extractive institutions can score high on management quality under this framework.
What EE adds
sign(S_net) decomposition
Adds the sign(S_net) decomposition. World Management Survey scores measure ∛(A · C · E) magnitude well; EE supplies (1 − V) and the alignment direction that determine whether a high-scoring firm produces Y > 0 or Y < 0.
EE source documents
Execution Economics (2026 monograph) 4.4.2; 10.1
F4 · Operations research, queueing theory, management practices
17 / 64
Core · F4 · Operations research, queueing theory, management practices
Governance indicators
Kaufmann, Kraay & Mastruzzi (2010), Worldwide Governance Indicators
What the theory explains
Cross-national scoring across voice, political stability, government effectiveness, regulatory quality, rule of law and corruption.
What it cannot explain
Unsigned and aggregated. Cannot distinguish mission-aligned from mission-extractive institutional capacity. Robodebt scored high on Australian governance indicators while producing structurally inverted outcomes.
What EE adds
Signed sovereignty product
Provides a signed sovereignty product. Same component data, opposite diagnoses: WGI reads high; ∛(A · C · E) · (1 − V) under EE diagnoses the Robodebt regime as deeply negative because the alignment vector inside V was hostile to the stated policy intent.
EE source documents
Execution Economics (2026 monograph) 4.4.1; 18.4
Decision Sovereignty (2026 monograph) Ch. 5.4 Robodebt
F4 · Operations research, queueing theory, management practices
18 / 64
Core · F4 · Operations research, queueing theory, management practices
Dynamic capabilities theory
Teece, Pisano & Shuen (1997)
What the theory explains
Capacity of firms to integrate, build and reconfigure competences in response to changing conditions.
What it cannot explain
Possessing a capability is not the same as producing the intended result. The framework establishes that a firm can act, but does not specify whether the effect aligns with intended direction.
What EE adds
S as signed product
Capabilities populate A and C inside the cube root but do not determine sign. EE supplies the ∛(A · C · E) · (1 − V) signed product that converts a possessed capability into realised outcome, including the reversal mode dynamic capabilities theory cannot generate.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.2 Dynamic capabilities
F4 · Operations research, queueing theory, management practices
19 / 64
Core · F4 · Operations research, queueing theory, management practices
Evolutionary and absorptive-capacity theory
Nelson & Winter (1982); Cohen & Levinthal (1990), "Absorptive Capacity"
What the theory explains
How organisational routines evolve, are selected, and how firms process and apply external knowledge over time.
What it cannot explain
Captures variation, selection and learning within organisations. Does not distinguish routines that preserve the intended effect of a decision from those that systematically alter or invert it.
What EE adds
Signed alignment over routines
Routines feed into C and E inside the cube root. EE adds the signed alignment that determines whether evolved routines preserve, attenuate or invert a faithfully executed decision.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.2 Evolutionary and organisational theory
Core · Family 5
F5 cover
Core family
F5/ 23
Civilisational history and long-run political development
5 traditions in this family
F5 · Civilisational history and long-run political development
20 / 64
Core · F5 · Civilisational history and long-run political development
Geographic determinism
Diamond (1997), Guns, Germs and Steel
What the theory explains
Ecological endowments shape the deep distribution of civilisations and the speed of pre-modern development.
What it cannot explain
Explains pre-modern distribution but not modern outcomes. Japan and Britain show modest endowment with formidable execution; Russia shows vast endowment with weak execution.
What EE adds
Carrier variable
Geography sets the stage; it does not write the play. EE supplies the institutional carrier ∛(A · C · E) · (1 − V) through which geographic endowments are or are not converted into realised output.
EE source documents
Execution Age (manuscript) Throughout — civilisational analysis
F5 · Civilisational history and long-run political development
21 / 64
Core · F5 · Civilisational history and long-run political development
Cognitive and ideational history
Harari (2014), Sapiens; McCloskey (2010), Bourgeois Dignity
What the theory explains
Shared fictions enable cooperation; ideational origins of modern growth.
What it cannot explain
Treats ideas as causally primary, but advanced empirical astronomy at the Maragha observatory (13th c.), proto-double-entry techniques in the medieval Islamic accounting tradition, and movable type in Song China (Bi Sheng, c. 1040) all preceded the institutional configurations under which their European analogues reshaped the world. The ideas, or strong precursors of them, were available; they did not move the world until they met execution systems.
What EE adds
S as transmission carrier
Supplies the carrier: ∛(A · C · E) · (1 − V) determines whether an idea propagates into institutional output. Same idea, different DSI, different civilisational outcome.
EE source documents
Execution Age (manuscript) Ch. 7 What the Tablets Could Carry
F5 · Civilisational history and long-run political development
22 / 64
Core · F5 · Civilisational history and long-run political development
State-formation theory
Fukuyama (2011), The Origins of Political Order; Besley & Persson (2011), Pillars of Prosperity
What the theory explains
How merit-recruited bureaucracy emerged; the Chinese precedence; the bureaucracy-rule-of-law-accountability triad.
What it cannot explain
Reads achievement as a developmental endpoint rather than as specific sovereignty arrangements. Cannot explain why well-formed states still fail to execute major reforms.
What EE adds
K = K₀ · Q^φ · D^ψ
Reads Fukuyama's structures as specific sovereignty arrangements that propagate for structural reasons. EE formalises propagation as the institutional capacity equation K = K₀ · Q^φ · D^ψ feeding into C and E inside the cube root.
EE source documents
Execution Age (manuscript) Ch. 9 The Cabbages at Salona; Ch. 10
F5 · Civilisational history and long-run political development
23 / 64
Core · F5 · Civilisational history and long-run political development
Innovation clustering and incumbent failure
Christensen (1997), The Innovator's Dilemma; Perez (2002), Technological Revolutions and Financial Capital
What the theory explains
Why incumbents fail to adopt disruptive technologies; technological revolutions arrive in regular surges and require institutional re-institutionalisation.
What it cannot explain
Christensen attributes incumbent failure to unwillingness to cannibalise margins, not to endogenous decision-governance limits. Perez identifies the lag between technological surge and institutional adjustment but does not formalise the transmission constraint.
What EE adds
Convex governance costs
Locates incumbent failure in convex governance costs that compress ∛(A · C · E) · (1 − V) as decision intensity rises. Firms and organisations do not die because a more creative competitor replaces them; they die when they lack the structural sovereignty to support the activity they have committed to. Re-institutionalisation is the period during which V is renegotiated and E rebuilt around the new technology, typically in uncontested territory.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 1 Convex governance costs; Ch. 2 Uncontested territory; Ch. 4.3 Theoretical forebears
F5 · Civilisational history and long-run political development
24 / 64
Core · F5 · Civilisational history and long-run political development
Neolithic materialism
Childe (1936), Man Makes Himself; Henrich (2004)
What the theory explains
Agricultural transition transformed social organisation; cultural transmission scales with population size and connectivity.
What it cannot explain
Childe's strict materialist sequence is complicated by archaeology: at Göbekli Tepe and related sites, evidence suggests ritual and settlement complexity preceded full agriculture, though the farming–settlement causal sequence remains debated. Henrich's framework has the transmission mathematics but no explicit causal arrow.
What EE adds
Reversed causal arrow
Absorbs Henrich's transmission mathematics and reverses the causal arrow: institutional ∛(A · C · E) · (1 − V) is the precondition for agricultural and technological transitions, not their consequence.
EE source documents
Execution Age (manuscript) Ch. 4 The Bones Remember; Ch. 5 The Walls Came First
Core · Family 6
F6 cover
Core family
F6/ 23
Sociology of institutions, collective action and implementation studies
6 traditions in this family
F6 · Sociology of institutions, collective action and implementation studies
25 / 64
Core · F6 · Sociology of institutions, collective action and implementation studies
Bureaucracy and rationalisation
Weber (1922/1978), Economy and Society
What the theory explains
Typology of bureaucratic forms; routinisation of charisma; rationalisation of social action.
What it cannot explain
Typology without formalised transmission or quantified capacity. Weber names the phenomenon; the framework does not formalise it.
What EE adds
Measurable composite
Converts Weber's intuition into a measurable composite. Bureaucratic capacity K = K₀ · Q^φ · D^ψ feeds into C and E inside ∛(A · C · E), giving Weber's bureaucratic ideal-type a production-function expression.
EE source documents
Execution Economics (2026 monograph) 4.1; 4.2
F6 · Sociology of institutions, collective action and implementation studies
26 / 64
Core · F6 · Sociology of institutions, collective action and implementation studies
Religious sociology
Durkheim (1912); Weber (1905), The Protestant Ethic
What the theory explains
Religion as solidarity, meaning and ethical orientation; the relationship between religion and economic activity.
What it cannot explain
Treats religion as sociological function. Cannot explain why some religious institutions achieve extraordinary institutional transmission fidelity across millennia.
What EE adds
Engineered transmission architecture
Reads major traditions as engineered transmission architectures: distributed redundancy in C, modular self-replication in E, high ∛(A · C · E) · (1 − V) maintained without central control.
EE source documents
Execution Age (manuscript) Ch. 14 Religion as Execution System
F6 · Sociology of institutions, collective action and implementation studies
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Core · F6 · Sociology of institutions, collective action and implementation studies
Collective action and free-riding
Olson (1965), The Logic of Collective Action
What the theory explains
Concentrated costs and diffuse benefits create obstacles to reform. Why groups often fail to act in their collective interest.
What it cannot explain
Explains why reform is hard, not how transmission fidelity is engineered when reform succeeds. Does not formalise the S of successful collective action.
What EE adds
Execution complement
Supplements with the structural variable for execution once the collective-action problem is solved. Overcoming free-riding raises A but is necessary, not sufficient, for ∛(A · C · E) · (1 − V) > 0.
EE source documents
Execution Economics (2026 monograph) 21.1.2
F6 · Sociology of institutions, collective action and implementation studies
28 / 64
Core · F6 · Sociology of institutions, collective action and implementation studies
Network sociology
Granovetter (1973), "The Strength of Weak Ties"
What the theory explains
Weak ties carry information across structural holes; network position shapes opportunity and information flow.
What it cannot explain
Information flow with exogenous authority. The same network produces different outcomes under high-S vs low-S institutional contexts.
What EE adds
Network × S = Y
Provides the institutional structure that determines whether network information translates into executed decisions. Network topology populates E (Execution-relevant Information at the point of action), but ∛(A · C · E) · (1 − V) governs whether that information is acted upon.
EE source documents
Execution Economics (2026 monograph) 23.x Network extensions
F6 · Sociology of institutions, collective action and implementation studies
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Core · F6 · Sociology of institutions, collective action and implementation studies
Decentralised knowledge
Hayek (1945), "The Use of Knowledge in Society"
What the theory explains
Dispersed knowledge that cannot be centralised; the price system as an information-aggregating mechanism.
What it cannot explain
Shows why central planning fails; not when decentralised execution succeeds. No formal model of execution-relevant information in decentralised settings.
What EE adds
E formalises Hayek
EE's E component formalises Hayek's question: how much execution-relevant information reaches the point of action? High E inside the cube root is the operationalisation of Hayekian local-knowledge advantage.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 6 DSI components
Execution Economics (2026 monograph) 2.2.1
F6 · Sociology of institutions, collective action and implementation studies
30 / 64
Core · F6 · Sociology of institutions, collective action and implementation studies
Implementation studies and mid-level filtration
Pressman & Wildavsky (1973), Implementation; Hill & Hupe (2002); Bartlett & Ghoshal (1994); Allison (1971/1999), Essence of Decision
What the theory explains
Policy failure as the product of fragmented authority, sequential veto points and coordination breakdowns; middle-management filtration of strategic intent.
What it cannot explain
Identifies the chain of failures and the dilution effect but does not formalise whether the chain is multiplicative, weakest-link or signed.
What EE adds
Γ = min{β, |A_T|, 1−χ}
Formalises as the weakest-link transmission Γ = min{β, |A_T|, 1−χ} composed with ∛(A · C · E) · (1 − V). Each Pressman-Wildavsky clearance is a contributor to V; each Bartlett-Ghoshal middle-management filter compresses E inside the cube root.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 4.3 Theoretical forebears
Execution Economics (2026 monograph) 7.1; 7.4.3
Extended · Family 7
F7 cover
Extended family
F7/ 23
Game theory and strategic interaction
4 traditions in this family
F7 · Game theory and strategic interaction
31 / 64
Extended · F7 · Game theory and strategic interaction
Classical game theory and Nash equilibrium
von Neumann & Morgenstern (1944); Nash (1950)
What the theory explains
Optimal strategies in strategic interaction; equilibrium selection; mixed strategies; best-response dynamics.
What it cannot explain
Assumes strategies transmit frictionlessly to outcomes. No model of the institutional medium between choice and result. Nash equilibria are identified but not executed.
What EE adds
S as transmission operator
∛(A · C · E) · (1 − V) governs whether Nash equilibria propagate into realised outcomes. Game-theoretic analysis is necessary for d(P) but EE governs whether it reaches Y.
EE source documents
Extended Position (positioning document) Family 7 — Game Theory
F7 · Game theory and strategic interaction
32 / 64
Extended · F7 · Game theory and strategic interaction
Evolutionary game theory
Maynard Smith & Price (1973); Weibull (1995); Hofbauer & Sigmund (1998)
What the theory explains
How strategies evolve in populations; evolutionarily stable strategies (ESS); replicator dynamics; selection pressures on institutional forms.
What it cannot explain
Variation and selection are unsigned — cannot distinguish whether a selected strategy serves or systematically inverts the institution's mission. ESS is a stability concept, not a fidelity concept.
What EE adds
sign(S_net) over equilibria
EE adds transmission fidelity to selected strategies. Mission-extractive institutions can reach an evolutionarily stable equilibrium with high ∛(A · C · E) magnitude while operating with sign(S_net) = −1, amplifying harm.
EE source documents
Extended Position (positioning document) Family 7 — Game Theory
F7 · Game theory and strategic interaction
33 / 64
Extended · F7 · Game theory and strategic interaction
Extensive-form games and backward induction
Selten (1965); Rubinstein (1982)
What the theory explains
Sequential decision trees; subgame-perfect equilibrium; strategic commitment; credible threats.
What it cannot explain
Assumes perfect backward induction with no institutional friction between game nodes. The game tree describes optimal plans; execution along the tree is implicit.
What EE adds
S over node-to-node transit
∛(A · C · E) · (1 − V) governs whether decisions at each node transmit faithfully along the game tree. Congestion friction χ(ρ) is the formalisation of node delay; S < 0 produces rollback failures where backward induction recommends an action that institutions invert.
EE source documents
Extended Position (positioning document) Family 7 — Game Theory
F7 · Game theory and strategic interaction
34 / 64
Extended · F7 · Game theory and strategic interaction
Cooperative game theory and coalitions
Shapley (1953); Aumann (1959)
What the theory explains
Coalition formation; surplus distribution; core and Shapley value; stable allocations.
What it cannot explain
Allocates value but does not model whether the coalition can execute the plan that generates the surplus. Coalition stability is not execution capacity.
What EE adds
V as blocking-coalition model
Decision sovereignty is the precondition for value realisation in coalitions. V (Veto exposure) is the formal EE model of blocking coalitions: the (1 − V) multiplier on ∛(A · C · E) systematically discounts Shapley values that cannot be realised.
EE source documents
Extended Position (positioning document) Family 7 — Game Theory
Extended · Family 8
F8 cover
Extended family
F8/ 23
Complex systems and emergence
2 traditions in this family
F8 · Complex systems and emergence
35 / 64
Extended · F8 · Complex systems and emergence
Complex adaptive systems
Holland (1992); Axelrod (1997); Kauffman (1993)
What the theory explains
Emergence, self-organisation, non-linear dynamics, adaptive agents, phase transitions.
What it cannot explain
Emergence is unsigned — cannot distinguish whether emergent complexity serves or inverts system mission. No variable for the direction of emergent outcomes relative to intent.
What EE adds
sign(S_net) over emergence
Distinguishes adaptive emergence (∛(A · C · E) · (1 − V) > 0) from complexity collapse (≈ 0) and adversarial emergence (< 0) where self-organisation systematically inverts institutional intent — a structural condition, not an anomaly.
EE source documents
Extended Position (positioning document) Family 8 — Complex Systems
F8 · Complex systems and emergence
36 / 64
Extended · F8 · Complex systems and emergence
Systems dynamics and feedback loops
Forrester (1961); Meadows (2008); Sterman (2000)
What the theory explains
Causal loop diagrams; stock-flow models; reinforcing and balancing feedback; policy resistance.
What it cannot explain
Models structural feedback but assumes the decision node faithfully implements its decision. No model of institutional transmission degradation at feedback nodes. Policy resistance is described but not attributed to signed transmission failure.
What EE adds
S modifies feedback gain
∛(A · C · E) · (1 − V) modifies the gain of each feedback arc. Negative S converts reinforcing loops into perverse amplification: each iteration of a reinforcing loop worsens outcomes. Policy resistance is formalised as low DSI at key nodes, not as an exogenous structural property.
EE source documents
Extended Position (positioning document) Family 8 — Complex Systems
Extended · Family 9
F9 cover
Extended family
F9/ 23
Political science and public choice
3 traditions in this family
F9 · Political science and public choice
37 / 64
Extended · F9 · Political science and public choice
Public choice theory
Buchanan & Tullock (1962); Downs (1957)
What the theory explains
Political market failures; rent-seeking; median-voter theorem; rational ignorance; public-good provision.
What it cannot explain
Explains why problematic policies are chosen, not why well-chosen policies fail in execution. Silent on transmission fidelity post-political decision.
What EE adds
S downstream of political choice
∛(A · C · E) · (1 − V) is the execution constraint downstream of political choice. V captures veto-player accumulation in democratic systems; even when public-choice problems are resolved at the d(P) stage, DSI determines whether good decisions reach Y.
EE source documents
Extended Position (positioning document) Family 9 — Political Science
F9 · Political science and public choice
38 / 64
Extended · F9 · Political science and public choice
Arrow's impossibility and social choice
Arrow (1951); Sen (1970)
What the theory explains
No social choice function simultaneously satisfies all fairness axioms; cycling preferences; aggregation paradoxes.
What it cannot explain
Shows the impossibility of aggregating preferences but not the transmission conditions for whatever choice is made.
What EE adds
Two-layer separation
Arrow identifies impossibility at the d(P) layer; EE addresses the S layer. A social choice that clears Arrow's constraints still requires ∛(A · C · E) · (1 − V) > 0 to reach Y.
EE source documents
Extended Position (positioning document) Family 9 — Political Science
F9 · Political science and public choice
39 / 64
Extended · F9 · Political science and public choice
State capacity theory
Mann (1984); Besley & Persson (2011), Pillars of Prosperity
What the theory explains
Why some states can implement policy and others cannot; fiscal and legal capacity; infrastructural vs despotic power.
What it cannot explain
Unsigned capacity. High capacity is treated as uniformly good. Cannot diagnose high-capacity mission-extractive states. The USSR had state capacity yet produced systematic S < 0 outcomes.
What EE adds
Magnitude × sign decomposition
Decomposes state capacity into magnitude and sign. High Mann-style infrastructural power × sign(S_net) = −1 produces the mission-extractive high-capacity state — empirically observed but theoretically invisible without the cube-root signed product.
EE source documents
Extended Position (positioning document) Family 9
Execution Age (manuscript) Ch. 3 — explicitly distinguishes S from state capacity
Extended · Family 10
F10 cover
Extended family
F10/ 23
Cybernetics, control theory and engineering systems
3 traditions in this family
F10 · Cybernetics, control theory and engineering systems
40 / 64
Extended · F10 · Cybernetics, control theory and engineering systems
Cybernetics and feedback control
Wiener (1948), Cybernetics; Ashby (1956) — Law of Requisite Variety
What the theory explains
Feedback mechanisms for system stabilisation; requisite variety; homeostasis; information and control in machines and animals.
What it cannot explain
Assumes the controller faithfully implements corrective signals. No model of the institutional medium inverting control. Ashby's Law addresses variety mismatch, not signed transmission failure.
What EE adds
Signed transfer function
Extends Wiener's transfer function: ∛(A · C · E) · (1 − V) is the institutional gain coefficient that may be negative. S < 0 captures control-signal inversion, where institutional amplification produces the opposite of the intended correction. Robodebt is a cybernetic S < 0 system.
EE source documents
Extended Position (positioning document) Family 10 — Control Theory
F10 · Cybernetics, control theory and engineering systems
41 / 64
Extended · F10 · Cybernetics, control theory and engineering systems
Reliability theory and the Swiss-cheese model
Reason (1990), Human Error; Weibull (1951)
What the theory explains
Component failure distributions; system reliability; accident causation via aligned holes in defensive layers.
What it cannot explain
Models failure as random degradation or cascading aligned holes. Cannot model systematic signed inversion: a system producing contrary outcomes by structural design rather than by accident.
What EE adds
Inversion ≠ degradation
Execution reversal is not Swiss-cheese degradation but inversion — structural rather than probabilistic. The Boeing 737 MAX MCAS is not a Swiss-cheese failure but an S < 0 structural condition in the certification and feedback system, with V dominated by misaligned actors.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.4 — Boeing 737 MAX MCAS
Extended Position (positioning document) Family 10
F10 · Cybernetics, control theory and engineering systems
42 / 64
Extended · F10 · Cybernetics, control theory and engineering systems
Information theory
Shannon & Weaver (1949); Kolmogorov (1965)
What the theory explains
Channel capacity, noise, entropy, coding efficiency; bandwidth limits on information transmission.
What it cannot explain
Models degradation of signal fidelity (attenuation, noise) but the channel is passive. Shannon entropy is unsigned; no model of adversarial or signed channel behaviour.
What EE adds
Active adversarial channel
The institutional channel is active and potentially adversarial. S < 0 extends beyond channel noise to signed transformation: the institution does not merely degrade the signal but reverses it. Information theory becomes a special case where ∛(A · C · E) · (1 − V) = 1 − noise rate.
EE source documents
Extended Position (positioning document) Family 10
Extended · Family 11
F11 cover
Extended family
F11/ 23
Law, jurisprudence and constitutional theory
2 traditions in this family
F11 · Law, jurisprudence and constitutional theory
43 / 64
Extended · F11 · Law, jurisprudence and constitutional theory
Law and economics
Posner (1973); Calabresi (1970); Coase (1960), "The Problem of Social Cost"
What the theory explains
Efficiency of legal rules; property rights; liability as internalisation mechanism; contracts as governance.
What it cannot explain
Assumes legal rules transmit faithfully into behavioural compliance. Execution of law is implicit and costless. V (legal challenge and judicial blocking) is not formalised.
What EE adds
Legal transmission fidelity
∛(A · C · E) · (1 − V) is the execution fidelity of legal rules. A legally optimal rule (high d(P)) with V → 1 drives DSI → 0: the law is formally valid but institutionally blocked.
EE source documents
Extended Position (positioning document) Family 11 — Law
F11 · Law, jurisprudence and constitutional theory
44 / 64
Extended · F11 · Law, jurisprudence and constitutional theory
Constitutional theory and separation of powers
Madison (1788), Federalist No. 51; Montesquieu (1748); Dahl (1956); Driesen (2025), "Donald Trump's Unitary Executive: Overcoming the Constitution," Constitutional Studies 11(2)
What the theory explains
Checks, balances and veto structures designed to prevent tyranny; separation of powers; constitutional design.
What it cannot explain
Designed to constrain S < 1 (preventing unchecked execution) but cannot distinguish protective attenuation from mission-extractive blockage. Cannot specify when adding veto players moves from protective to paralytic.
What EE adds
Engineered V
Provides the normative framework Madison lacks. V suppression is protective when sign(S_net) of unchecked authority would be negative; V accumulation is dangerous when it suppresses positive ∛(A · C · E). Constitutional design is the engineering of V to target S ∈ (0, 1].
EE source documents
Extended Position (positioning document) Family 11 — Law
Decision Sovereignty (2026 monograph) Ch. 4.3 — Tsebelis veto-player theory
Extended · Family 12
F12 cover
Extended family
F12/ 23
Military strategy and doctrine
2 traditions in this family
F12 · Military strategy and doctrine
45 / 64
Extended · F12 · Military strategy and doctrine
Clausewitzian strategy and friction of war
Clausewitz (1832), On War; Moltke the Elder (1871); van Creveld (1985), Command in War
What the theory explains
Strategy as continuation of politics; fog of war; friction in military operations; the gap between plan and execution.
What it cannot explain
Friction is identified qualitatively ("the resistance of the real") but not formalised as a signed transmission operator. Cannot distinguish attenuating friction from inverting friction. Cannot predict when better plans produce worse outcomes.
What EE adds
(1 − DSI) = friction
(1 − ∛(A · C · E) · (1 − V)) is the quantitative expression of Clausewitz's friction. S < 0 is the condition Clausewitz observed empirically (Vietnam; Napoleon in Russia) but could not formalise. The OODA loop is d(P); DSI governs whether the loop closes into Y.
EE source documents
Extended Position (positioning document) Family 12 — Military
F12 · Military strategy and doctrine
46 / 64
Extended · F12 · Military strategy and doctrine
Mission command and Auftragstaktik
Prussian General Staff (19th c.); van Creveld (1985); US Army (2012), Mission Command FM 6-0
What the theory explains
Decentralised execution authority; intent-based command rather than rule-based; initiative at the point of action; commander's intent.
What it cannot explain
Institutional rather than theoretical. No formal production function linking command style to outcome. Cannot predict when mission command produces higher or lower S than centralised command.
What EE adds
High A + low V architecture
Mission command is the institutional design that maximises A and E (Execution-relevant Information at the point of action) while minimising V. EE provides the production function justifying Prussian doctrine: high ∛(A · C · E) · (1 − V) through distributed authority rather than centralised veto accumulation.
EE source documents
Extended Position (positioning document) Family 12 — Military
Decision Sovereignty (2026 monograph) Ch. 2.6 Second Track architecture
Extended · Family 13
F13 cover
Extended family
F13/ 23
Philosophy of action and practical rationality
2 traditions in this family
F13 · Philosophy of action and practical rationality
47 / 64
Extended · F13 · Philosophy of action and practical rationality
Philosophy of action and intentional action
Anscombe (1957); Davidson (1980); Bratman (1987)
What the theory explains
How intentions cause actions; practical reasoning; akrasia (weakness of will); causal theory of action.
What it cannot explain
Individual-level: explains why agents fail to act on intentions but not how institutional structures invert the effects of successfully executed actions.
What EE adds
Institutional akrasia and inversion
S < 1 reads as institutional akrasia (the organisation cannot fully act on its intentions); S < 0 as institutional inversion (it acts on its intentions and produces the opposite effect). EE extends action theory from the individual to the institutional level via ∛(A · C · E) · (1 − V), adding a failure mode that has no individual analogue.
EE source documents
Extended Position (positioning document) Family 13 — Philosophy
F13 · Philosophy of action and practical rationality
48 / 64
Extended · F13 · Philosophy of action and practical rationality
Deliberative democracy and communicative rationality
Habermas (1984); Rawls (1993)
What the theory explains
Ideal speech situations; communicative vs strategic action; discourse ethics; public reason as legitimating force.
What it cannot explain
Assumes well-formed discourse produces legitimate and executable outcomes. No model of transmission failure from legitimate deliberation to executed outcome.
What EE adds
Legitimacy × DSI = Y
∛(A · C · E) · (1 − V) governs whether deliberatively legitimate decisions transmit into Y. Habermasian discourse is a theory of d(P); EE provides the S layer. Democratic legitimacy is necessary but not sufficient.
EE source documents
Extended Position (positioning document) Family 13 — Philosophy
Extended · Family 14
F14 cover
Extended family
F14/ 23
Computer science and distributed systems
2 traditions in this family
F14 · Computer science and distributed systems
49 / 64
Extended · F14 · Computer science and distributed systems
Distributed consensus and Byzantine fault tolerance
Lamport, Shostak & Pease (1982); Castro & Liskov (1999); Brewer (2000), CAP Theorem (conjecture); Gilbert & Lynch (2002), "Brewer's Conjecture and the Feasibility of Consistent, Available, Partition-Tolerant Web Services" (formal proof)
What the theory explains
Consensus under network partitions and malicious nodes; fault-tolerant distributed systems; impossibility results for consensus.
What it cannot explain
Models fault tolerance against random or adversarial node failure within a well-defined protocol. Does not model institutions in which the entire transmission medium is structurally mission-hostile.
What EE adds
S < 0 = Byzantine class
S < 0 is Byzantine-class institutional failure where the organisation is the adversarial transmission medium producing systematic inversion rather than random error. Byzantine tolerance targets ∛(A · C · E) · (1 − V) above a threshold; EE addresses the case where the consensus protocol itself inverts the intended decision.
EE source documents
Extended Position (positioning document) Family 14 — Computer Science
F14 · Computer science and distributed systems
50 / 64
Extended · F14 · Computer science and distributed systems
Software architecture and technical debt
Cunningham (1992); Brooks (1975), The Mythical Man-Month
What the theory explains
Technical debt accumulation; architectural entropy; scaling failure as complexity compounds; why adding engineers to a late project makes it later.
What it cannot explain
Domain-specific analogue of governance curvature but without a generalised production-theoretic framework. No signed transmission variable.
What EE adds
Technical debt = governance curvature
Technical debt is a specific case of convex governance costs. Brooks's Law (adding engineers delays the project) is S(L) = e^(−κL²) applied to software: decision intensity rises faster than capacity, compressing C and E inside the cube root.
EE source documents
Extended Position (positioning document) Family 14
Decision Sovereignty (2026 monograph) Ch. 1.4 Convex decision-governance costs
Extended · Family 15
F15 cover
Extended family
F15/ 23
Neuroscience and cognitive science
2 traditions in this family
F15 · Neuroscience and cognitive science
51 / 64
Extended · F15 · Neuroscience and cognitive science
Decision neuroscience and the somatic-marker hypothesis
Damasio (1994); Bechara, Damasio et al. (1994); LeDoux (1996); Sapolsky (2017)
What the theory explains
Emotional substrates of decision-making; somatic markers guiding choice under uncertainty; orbitofrontal cortex as executor of practical rationality.
What it cannot explain
Individual-level neurological mechanism. Cannot aggregate individual somatic-marker failures into institutional transmission effects.
What EE adds
α exponent from neural basis
Neurological constraints absorbed into the α exponent of d(P) = P^α. Orbitofrontal damage drives α → 0. Stress-induced cortisol elevation suppresses prefrontal function and produces institutional α decline under load, indirectly compressing E inside ∛(A · C · E).
EE source documents
Extended Position (positioning document) Family 15 — Neuroscience
Decision Sovereignty (2026 monograph) Ch. 3 The human factor
F15 · Neuroscience and cognitive science
52 / 64
Extended · F15 · Neuroscience and cognitive science
Dual-process theory and Yerkes-Dodson
Yerkes & Dodson (1908) (mouse discrimination learning under shock — the inverted-U "law" is a later, contested generalisation); Kahneman (2011); Evans (2008); Stanovich & West (2000)
What the theory explains
System 1 vs System 2 processing; cognitive load effects on reasoning quality; the inverted-U arousal-performance relationship.
What it cannot explain
Individual cognitive architecture. The institutional consequences of aggregated System 1 dominance under organisational stress are not specified.
What EE adds
Collective amygdala hijack → κ
System 1 dominance under load is the institutional shift in α. Collective amygdala hijack under sustained decision intensity is the neurological mechanism of governance curvature κ. The Yerkes–Dodson generalisation is the individual-level analogue of S(L) = e^(−κL²).
EE source documents
Decision Sovereignty (2026 monograph) Ch. 3.2 The Yerkes-Dodson Law
Extended Position (positioning document) Family 15
New EE-Impacted · Family 16
F16 cover
New EE-Impacted family
F16/ 23
Development economics and policy scaling NEW
2 traditions in this family
F16 · Development economics and policy scaling
53 / 64
NEW · EE-Impacted
Randomised controlled trials in development
Banerjee & Duflo (2011), Poor Economics; Banerjee, Banerji, Berry, Duflo, Kannan, Mukerji, Shotland & Walton (2017), "From Proof of Concept to Scalable Policies," Journal of Economic Perspectives 31(4): 73–102; Duflo, Glennerster & Kremer (2007)
What the theory explains
Causal identification of programme effects through randomisation; cost-effectiveness comparisons across interventions.
What it cannot explain
Trial effects often collapse on scaling. The frameworks identify what works in trial settings but do not specify the structural conditions required for the intervention to translate into population-level outcomes.
What EE adds
Trial vs scale gap
RCT effects are estimates of d(P) under a specific institutional context. Scaling reduces ∛(A · C · E) · (1 − V) at the population level: A diffuses across many implementing agencies, E is sparser at the periphery, and V rises with each new implementing layer. The SMS-tax-compliance vignette (P.1 of EE) — 23 percentage points in trial, under 2 at national scale — is the canonical EE illustration.
EE source documents
Execution Economics (2026 monograph) P.1 — SMS-tax-compliance vignette
F16 · Development economics and policy scaling
54 / 64
NEW · EE-Impacted
Scaling and policy implementation
Pritchett, Woolcock & Andrews (2010, 2013), "Capability Traps"; Banerjee, Banerji, Berry et al. (2017)
What the theory explains
Why programmes that work in pilots fail when scaled; isomorphic mimicry; the 'capability trap' in which form is reproduced without function.
What it cannot explain
Names the phenomenon but does not formalise the structural variable governing the gap between form and function.
What EE adds
Form vs DSI
Isomorphic mimicry is high A on paper with low C and E in practice, plus high V from donor-imposed conditions. EE makes the form/function gap measurable through the DSI components and predicts when capability traps will resolve (∛(A · C · E) rises) versus deepen (V rises faster).
EE source documents
Not source-attested in the EE corpus; offered as a programme extension.
New EE-Impacted · Family 17
F17 cover
New EE-Impacted family
F17/ 23
Project management and megaproject performance NEW
2 traditions in this family
F17 · Project management and megaproject performance
55 / 64
NEW · EE-Impacted
Megaproject performance and reference-class forecasting
Flyvbjerg, Bruzelius & Rothengatter (2003), Megaprojects and Risk; Flyvbjerg (2014); Morris & Hough (1987)
What the theory explains
Systematic cost and timeline overruns in megaprojects; optimism bias and strategic misrepresentation; the survival rate of accurate forecasts under political pressure.
What it cannot explain
Identifies the regularity (overrun) and the proximate cognitive and political causes but does not formalise the structural decision-sovereignty conditions under which an accurate ex-ante forecast survives to govern execution.
What EE adds
Forecast survival = (1 − V)
Reference-class forecasting raises d(P). Whether the forecast is acted upon depends on ∛(A · C · E) · (1 − V) of the project sponsor. The recurrent Flyvbjerg overrun is the empirical signature of low DSI in the project-sponsor coalition: A is contested, V is high, and accurate forecasts are politically dominated.
EE source documents
Execution Economics (2026 monograph) P.1 — Flyvbjerg cited as megaproject benchmark
F17 · Project management and megaproject performance
56 / 64
NEW · EE-Impacted
Theory of Constraints and project chains
Goldratt (1984), The Goal; Goldratt (1997), Critical Chain
What the theory explains
Throughput is determined by the binding constraint; local optimisation is wasted unless it acts on the constraint; project critical chains aggregate buffers at the system rather than activity level.
What it cannot explain
Operates within a fixed institutional architecture. Cannot diagnose when the binding constraint is not in the production system but in the governance system that allocates authority over it.
What EE adds
ToC + signed sovereignty
EE generalises the binding-constraint claim from production to governance. Goldratt's critical chain is operational; EE's weakest-link transmission Γ = min{β, |A_T|, 1 − χ} composed with ∛(A · C · E) · (1 − V) is the governance analogue. A project in a high-DSI environment can absorb operational shocks; a high-throughput project in a low-DSI environment cannot.
EE source documents
Not source-attested in the EE corpus; offered as a programme extension.
New EE-Impacted · Family 18
F18 cover
New EE-Impacted family
F18/ 23
Regulatory science and approval regimes NEW
1 tradition in this family
F18 · Regulatory science and approval regimes
57 / 64
NEW · EE-Impacted
Pharmaceutical and device regulation
Carpenter (2010), Reputation and Power; Olson (1995), "Regulatory Agency Discretion"; literature on FDA, EMA, TGA approval processes
What the theory explains
How regulatory agencies build reputational and statutory authority; the trade-off between Type I (false approval) and Type II (delayed approval) errors; regulator capture and independence.
What it cannot explain
Treats regulator capacity as unsigned. Cannot specify when a regulator's high apparent authority and control are nonetheless coupled with a hostile alignment vector (capture, ideological mission drift, or institutional self-preservation crowding out the statutory mission).
What EE adds
Regulator DSI is signed
A regulator with high A (statutory authority), high C (technical staff, inspection capacity) and adequate E (premarket data) but a misaligned objective function — favouring industry, ideology, or self-preservation over the statutory mission — exhibits high ∛(A · C · E) magnitude with sign(S_net) < 0. The Boeing 737 MAX MCAS certification (DS Ch. 5.4) is a canonical EE example: the FAA had high apparent capacity but the alignment vector with the statutory safety mission was compromised.
EE source documents
Decision Sovereignty (2026 monograph) Ch. 5.4 — Boeing 737 MAX MCAS
New EE-Impacted · Family 19
F19 cover
New EE-Impacted family
F19/ 23
Corporate governance NEW
1 tradition in this family
New EE-Impacted · Family 20
F20 cover
New EE-Impacted family
F20/ 23
Monetary policy and central banking NEW
1 tradition in this family
F20 · Monetary policy and central banking
59 / 64
NEW · EE-Impacted
Central bank independence and monetary policy implementation
Goodhart (1988); Taylor (1993); Cukierman, Webb & Neyapti (1992); Reis (2013)
What the theory explains
Why central bank independence raises credibility of inflation control; how rules-based policy reduces time-inconsistency; transmission of policy rates through the financial system.
What it cannot explain
Treats monetary transmission as a financial-market phenomenon. Does not formalise the institutional sovereignty conditions under which a central bank can act decisively in non-inflation crises (lender of last resort, macroprudential regulation, climate-related financial risk).
What EE adds
Mandate width × DSI
Independence raises A and reduces V for the inflation-targeting mandate but says nothing about A and V for tasks outside the mandate. The Bank of England's post-2008 shift toward open-letter inflation accountability (cited in EA Ch. 3 as exemplary revision agility) is the EE-canonical case of a high-DSI institution successfully extending its mandate without eroding the underlying authority structure.
EE source documents
Execution Age (manuscript) Ch. 3 — Bank of England post-2008 example
New EE-Impacted · Family 21
F21 cover
New EE-Impacted family
F21/ 23
Public health and emergency response NEW
1 tradition in this family
F21 · Public health and emergency response
60 / 64
NEW · EE-Impacted
Pandemic preparedness and outbreak response
WHO (2005), International Health Regulations; Henderson (2009), Smallpox; Lessler et al. (2014); after-action reports COVID-19, Ebola West Africa, SARS
What the theory explains
Surveillance systems; case-fatality estimation; non-pharmaceutical interventions; vaccine deployment logistics; the architecture of multilateral disease response.
What it cannot explain
Treats failure modes as informational (delayed surveillance, poor data) or capacity-based (insufficient PPE, ICU beds). Does not formalise the structural decision-sovereignty failures that prevent timely action even when information and capacity are present.
What EE adds
Outbreak DSI under load
Pandemic response is a high-L, high-stakes decision regime. The empirical record (COVID-19 across multiple jurisdictions) shows S(L) = e^(−κL²) collapse: as decision intensity rose, ∛(A · C · E) · (1 − V) compressed. Authority fragmented across health ministries, treasuries, and constitutional jurisdictions; V rose through judicial challenge and political contestation; E lagged surveillance lead times. EE predicts that pandemic preparedness investment must include DSI investment, not only capacity investment.
EE source documents
Execution Age (manuscript) Ch. 3 — pandemic response cited in closing
Decision Sovereignty (2026 monograph) Ch. 8 — wicked-problem framing
New EE-Impacted · Family 22
F22 cover
New EE-Impacted family
F22/ 23
AI safety and alignment NEW
1 tradition in this family
F22 · AI safety and alignment
61 / 64
NEW · EE-Impacted
AI alignment and safe deployment
Russell (2019), Human Compatible; Bostrom (2014), Superintelligence; Christiano et al. (2017); Amodei et al. (2016), "Concrete Problems in AI Safety"
What the theory explains
How to design AI systems whose objectives align with human values; reward hacking; specification gaming; corrigibility and oversight.
What it cannot explain
Operates at the system-design level. Treats the deploying institution as a homogeneous principal. Does not formalise the institutional decision-sovereignty conditions under which alignment work can be carried through to deployment, audited and revised.
What EE adds
Alignment ≠ DSI
An aligned AI system inside a low-DSI institution still produces S < 0 outcomes: the model recommends correctly, the institution executes faithfully, and the alignment vector inside V — the deploying organisation's actual mission as opposed to its stated mission — inverts the result. Robodebt (DS Ch. 5.4) is the operative case: the algorithm did what it was specified to do; the institution had high apparent A, C, E; the mission was extractive. EE predicts that AI safety progress without parallel investment in deploying-institution DSI will not reduce harm and may increase it through capability amplification.
EE source documents
Execution Economics (2026 monograph) Ch. 22 — AI raises d(P) but not S; the invariance claim
Decision Sovereignty (2026 monograph) Ch. 1.2 — AI deployment failure
New EE-Impacted · Family 23
F23 cover
New EE-Impacted family
F23/ 23
Performativity and unanticipated consequences NEW
3 traditions in this family
F23 · Performativity and unanticipated consequences
62 / 64
NEW · EE-Impacted
Goodhart’s Law
Goodhart (1975); Strathern (1997) reformulation.
What the theory explains
When a measure becomes a target, it ceases to be a good measure. Once an indicator is used as a control variable, the relationship between indicator and underlying construct decays.
What it cannot explain
Identifies a regularity in measurement and incentive design but does not formalise the institutional conditions under which the indicator-target gap inverts realised outcomes.
What EE adds
Goodhart drift = A_T → 0
EE locates Goodhart’s regularity inside A_T: the measure is the alignment vector under which the institution executes. When the measure ceases to track the underlying mission, A_T moves toward zero or below, and competent execution against the measure produces realised outcomes opposite to the stated mission.
EE source documents
Not source-attested in the EE corpus; added to the survey on review.
F23 · Performativity and unanticipated consequences
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NEW · EE-Impacted
Campbell’s Law
Campbell (1976).
What the theory explains
The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.
What it cannot explain
Predicts corruption as an emergent property of metric salience but does not formalise the structural conditions under which the corruption inverts realised outcomes at the institutional level.
What EE adds
Campbell distortion → A_T inversion
Campbell’s Law is the social-policy variant of the Robodebt-class case: high-stakes use of an indicator distorts the alignment vector A_T against the underlying mission, even where d(P) (data, analytical quality, updating, forecast track record) and the magnitude of ∛(A · C · E) · (1 − V) remain high.
EE source documents
Not source-attested in the EE corpus; added to the survey on review.
F23 · Performativity and unanticipated consequences
64 / 64
NEW · EE-Impacted
Unanticipated consequences of purposive social action
Merton (1936).
What the theory explains
Purposive action regularly produces consequences its actors did not anticipate. Merton enumerates ignorance, error, the imperious immediacy of interest, basic values, and self-defeating prophecy as sources of divergence.
What it cannot explain
Sociological canon on the gap between intent and outcome, but at the level of typology rather than production identity. Does not specify a signed transmission operator.
What EE adds
Production identity over Merton typology
EE supplies the production identity Y = d(P) · S that Merton’s typology lacks. The five Merton mechanisms map onto EE components: ignorance and error onto E; imperious immediacy of interest and basic values onto A_T (alignment of the executor’s utility function with the stated mission); self-defeating prophecy onto the feedback structure that updates U inside d(P).
EE source documents
Not source-attested in the EE corpus; added to the survey on review.
Cross-cutting
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The convergent-impossibility argument
Across all 64 traditions surveyed in this document — spanning institutional economics, behavioural science, organisational theory, operations research, civilisational history, sociology, game theory, complex systems, public choice, cybernetics, jurisprudence, military doctrine, philosophy of action, distributed computing, neuroscience, development economics, megaproject management, regulatory science, corporate governance, central banking, public health, AI safety, and performativity / unanticipated consequences — none independently formalises a signed transmission operator inside a production identity for realised institutional output. Traditions that acknowledge negative outcomes (Goodhart, Campbell, Merton, capture theory, veto-player gridlock) do so through auxiliary narratives rather than through a production identity in which the sovereignty term carries a sign that can flip.
This is not a charge of error against the host theories. Each was developed to answer a different question — why firms exist, why some societies grow, how cooperation emerges, how systems remain stable, why metrics decay under pressure. EE’s claim is narrower: across this convergent set of traditions, the variable that decides whether a decision executes in the direction intended is absent as a formally specified component of a production identity. EE names that variable S, decomposes it as DSI = ∛(A · C · E) · (1 − V), signs it through the cosine alignment A_T, and embeds it in the identity Y = S · d(P).
What this implies for application
The complementarity stance has practical consequences. EE does not require host theories to be discarded. It requires them to be supplemented with sovereignty accounting at every point where a decision is alleged to translate into an outcome — that is, at every transmission step. Where S > 0.4, host-theory predictions tend to hold. Where S < 0.25, host predictions fail in ways that look from inside the host theory like noise, anomaly, or implementation failure. Where S < 0 — as in Goodhart-style indicator inversion, Campbell-style metric corruption, or Merton-style purposive-action backfire under high stakes — host theories systematically over-predict the magnitude and sign of the intended effect.
Empirical anchor
The empirical companion volume Existence and Sign demonstrates the S < 0 condition operating in working institutional cases — most fully in the Robodebt scheme (2015–2020), where canonical scoring places government decision sovereignty in the symbolic-reversal regime throughout the operational period. The convergent-impossibility argument as developed here is the theoretical correlate of that empirical demonstration.