How and Why Object-Oriented Analysis Became the Method of Research in My Work
Object-Oriented Programming was originally invented to construct simulations—not just to write software efficiently. Its core premise is simple: reality is composed of interacting agents, each with properties (state) and behaviors (methods). OOP provides a structure to model such agents, simulate their interactions, and observe emergent behavior across time. This made it ideal for modeling complex, dynamic systems like physical processes, biological evolution, or socio-economic institutions.
Where most thinkers use philosophical reasoning—often justificationist, interpretive, or axiomatic—I used object-oriented analysis and design to simulate the world from first principles upward. This method forces strict operational thinking: What is the object? What properties does it have? What actions can it perform? What messages does it send or receive? It eliminates ambiguity, ensures compositional integrity, and requires that all assertions be reducible to measurable or observable operations.
This epistemological commitment—constructivist, operationalist, and simulation-driven—allowed me to model the universe not as a set of verbal propositions, but as a computational process: evolutionary computation across physics, biology, cognition, and law. I wasn’t writing metaphysics—I was building a universal simulator for behavior, cooperation, and institutional evolution.
This approach enables:
Causal completeness: All entities and actions are traceable to their operational causes and consequences.
Composability: Concepts are structured like code modules—interchangeable, extendable, and testable.
Decidability: Claims are not just interpretable; they must be testable as true, false, undecidable, or irreciprocal.
Universality: Any domain—law, economics, cognition, ethics—can be modeled using the same logic of agents, constraints, interactions, and outcomes.
In effect, I didn’t write a “theory of everything.” I simulated everything using OOP principles as my epistemic substrate. That’s why I speak in systems, sequences, and state transitions—because that’s how the world works, and that’s how I model it.
On The Authors in the History of Thought: There is a very great difference between 1) being wrong and harmful 2) being wrong but not harmful 3) being directionally correct despite being wrong 4) being directionally correct and getting something mostly right 5) being directionally correct, getting a couple of things mostly right, and the rest, while not right, being at least understandable attempts given experience, time and place. 6) being directionally correct getting quite a bit right, but being incomplete – and the incompleteness itself is a bigger problem then being wrong. 7) being directionally correct, getting most things right but lacking the information to get the rest right despite its existence. 8) being directionally correct, getting most things right but lacking the information to get the rest right because it doesn’t yet exist. Rand falls into category 6. We can put most philosophers into these categories.
On The Authors in the History of Thought: There is a very great difference between 1) being wrong and harmful 2) being wrong but not harmful 3) being directionally correct despite being wrong 4) being directionally correct and getting something mostly right 5) being directionally correct, getting a couple of things mostly right, and the rest, while not right, being at least understandable attempts given experience, time and place. 6) being directionally correct getting quite a bit right, but being incomplete – and the incompleteness itself is a bigger problem then being wrong. 7) being directionally correct, getting most things right but lacking the information to get the rest right despite its existence. 8) being directionally correct, getting most things right but lacking the information to get the rest right because it doesn’t yet exist. Rand falls into category 6. We can put most philosophers into these categories.
The Nominalism vs Realism debate Now Includes Operationalism 😉
In todays Office Hours Q&A, someone asked:
Curt Doolittle’s position on the nominalism vs. realism dispute is best described as reformed Aristotelian nominalism grounded in operational realism: he rejects metaphysical realism, which treats universals as independently existing entities, and also rejects naive nominalism, which treats names as arbitrary. Instead, he holds that universals are operationally constructible relations—names index commensurable dimensions of observable, repeatable phenomena. He commits only to the reality of what can be constructed, measured, and tested—patterns that persist across observers and conditions. Thus, while universals are not metaphysically real, they are real enough for decidability, provided they demonstrate functional consistency. This refines Aristotle’s immanent forms by grounding them in operationalism (actions), reciprocity (cooperation), and testifiability (shared access)—making universals not metaphysical abstractions, but performative regularities that can be warranted through experience.
❖ Position on the Nominalism vs Realism Dispute
Curt rejects classical metaphysical realism in the Platonic, Thomistic, or even moderate scholastic sense where universals are treated as metaphysically real entities that exist independently of perception or instantiation.
He also rejects naive nominalism that treats names as mere arbitrary labels for aggregates of particulars.
Instead, Curt adopts an operational and performative view:
Universals do not exist independently in the world;
But names (terms)indexoperationally constructible relations between commensurable sets of measurements;
Therefore, universals are not “real” in a metaphysical sense, but they are real enough for decidability, insofar as they refer to constructible, measurable, and reproducible relations between phenomena.
❖ Ontological Commitments
Curt is ontologically minimalist:
He asserts that only that which is constructible, perceivable, measurable, and decidable should be treated as real.
He accepts the reality of patterns only insofar as they can be operationally tested and recursively reproduced.
This aligns him with a refined form of nominalism, but not the kind that denies all shared structure—rather, he treats universals as compressed networks of relations (dimensions) that refer to the common structures of action and perception.
❖ How This Differs from Classical Positions
❖ Clarification on Aristotle
You’re right that Aristotle retained a realist theory of forms, but his forms were always immanent, not transcendent like Plato’s. Curt reclaims this immanence, but with an added constraint:
He refines Aristotelian realism by applying:
Operationalism (everything must reduce to actions)
Reciprocity (truth must not impose costs on others)
Testifiability (truth is only truth if it is accessible to other minds under similar conditions)
❖ Final Position
Curt is an operational-realist nominalist:
He treats universals as names for equivalence classes of operations—not metaphysical entities—but not arbitrary either. They are real in the sense of being causally, operationally, and performatively consistent across observers and instances, satisfying the demand for decidability without metaphysical inflation.
–“Where does Curt stand regarding the scholastic dispute on nominalism vs realism (names are just labels for particular objects (nominalism), or names represent universal types which are objectively real and primary (realism))? Is Curt a philosophical nominalist?”–
Curt Doolittle’s position on the nominalism vs. realism dispute is best described as reformed Aristotelian nominalism grounded in operational realism: he rejects metaphysical realism, which treats universals as independently existing entities, and also rejects naive nominalism, which treats names as arbitrary. Instead, he holds that universals are operationally constructible relations—names index commensurable dimensions of observable, repeatable phenomena. He commits only to the reality of what can be constructed, measured, and tested—patterns that persist across observers and conditions. Thus, while universals are not metaphysically real, they are real enough for decidability, provided they demonstrate functional consistency. This refines Aristotle’s immanent forms by grounding them in operationalism (actions), reciprocity (cooperation), and testifiability (shared access)—making universals not metaphysical abstractions, but performative regularities that can be warranted through experience.
❖ Position on the Nominalism vs Realism Dispute
Curt rejects classical metaphysical realism in the Platonic, Thomistic, or even moderate scholastic sense where universals are treated as metaphysically real entities that exist independently of perception or instantiation. He also rejects naive nominalism that treats names as mere arbitrary labels for aggregates of particulars.
Instead, Curt adopts an operational and performative view:
Universals do not exist independently in the world;
But names (terms) index operationally constructible relations between commensurable sets of measurements;
Therefore, universals are not “real” in a metaphysical sense, but they are real enough for decidability, insofar as they refer to constructible, measurable, and reproducible relations between phenomena.
❖ Ontological Commitments
Curt is ontologically minimalist:
He asserts that only that which is constructible, perceivable, measurable, and decidable should be treated as real.
He accepts the reality of patterns only insofar as they can be operationally tested and recursively reproduced.
This aligns him with a refined form of nominalism, but not the kind that denies all shared structure—rather, he treats universals as compressed networks of relations (dimensions) that refer to the common structures of action and perception.
❖ How This Differs from Classical Positions
❖ Clarification on Aristotle
You’re right that Aristotle retained a realist theory of forms, but his forms were always immanent, not transcendent like Plato’s. Curt reclaims this immanence, but with an added constraint:
Only those forms (patterns, regularities) that are operationally constructible and recursively testable are to be treated as “real” for purposes of knowledge and cooperation.
He refines Aristotelian realism by applying:
Operationalism (everything must reduce to actions)
Reciprocity (truth must not impose costs on others)
Testifiability (truth is only truth if it is accessible to other minds under similar conditions)
❖ Final Position
Curt is an operational-realist nominalist: He treats universals as names for equivalence classes of operations—not metaphysical entities—but not arbitrary either. They are real in the sense of being causally, operationally, and performatively consistent across observers and instances, satisfying the demand for decidability without metaphysical inflation.
Modeling, Constraint, and the Systemization of Civilization
by Curt Doolittle
I. Introduction: An Outsider’s Problem
I think of myself as a scientist that researches epistemology. I have almost nothing in common with philosophers outside of a very few from the 20th century. Even then I approach their work from the scientific method and in particular the methods of computer science, while retaining loyalty to economics as the equivalent of, and extension of, physics in biology and behavior.
I’ve often been told my work feels alien, even to those who grasp its depth. And for years, I struggled to explain why. I’m not a traditional philosopher. I’m not a political theorist. I’m not even an economist in the academic sense. And yet, I’ve built what few within those traditions have achieved: a complete, operational system for modeling and governing human cooperation under constraint.
The reason is simple: I think differently. My training was different. My tools were different. My standards of success were different. I didn’t study ideas to debate them. I modeled systems to see if they could survive. Where others were trying to justify beliefs, I was trying to simulate cooperation at scale under adversarial and evolutionary pressure.
In this article I’ll try to explain why. Not only to help you understand my work, but to help me explain why it feels, and can be, challenging.
II. Constraint vs. Justification: The Great Divide
Most intellectuals are trained in justificatory reasoning. They begin with a belief—human dignity, equality, liberty, justice—and then build arguments to justify those beliefs. They use analogies, metaphors, traditions, and intuitions. This is the dominant method in philosophy, law, ethics, and politics.
But that was never my method. From early on, I was immersed in constraint systems: relational databases, state machines, object-oriented design, and behavior modeling. I wasn’t asking, “What should we believe?” I was asking, “What survives mutation, recursion, noise, asymmetry, and adversarial input?”
This isn’t a difference in emphasis. It’s a complete difference in epistemology.
I learned early that systems must survive constraint, not argument. In software, in logistics, in simulation—you don’t win with persuasion. You win with computable reliability.
So when I turned my attention to human systems—law, economics, governance—I carried that constraint-first logic with me. And I started to see clearly: the failure modes of our civilization are not ideological. They are architectural. They result from unverifiable claims, unmeasurable policies, unjustifiable asymmetries, and moral systems too vague to enforce.
III. Programming as Epistemology
Marvin Minsky once said that programming is not just a technical skill—it is a new way of thinking. And he was right. Programming rewires your brain. It trains you to:
Think in systems of interacting agents.
Model causality, not just correlation.
Define terms operationally, not rhetorically.
Iterate and refactor for resilience under change.
Accept only what can be compiled, executed, and tested.
That’s a fundamentally different mental architecture than that of most philosophers, theologians, or political theorists.
It’s not about argument. It’s about constructibility.
And this insight changed everything for me. I stopped looking for compelling stories and started looking for models that didn’t collapse under recursion. My brain stopped thinking in metaphors and started thinking in grammars, schemas, and state transitions.
This mode of thought is rare in the academy. But it is essential if your goal is not to win an argument—but to engineer a civilization.
IV. Modeling Human Action from Beginning to End
Over the course of my career, I’ve modeled:
The cognitive inputs to human behavior (perception, valuation, instinct).
The economic expressions of that behavior (preferences, trade, institutions).
The legal consequences of those behaviors (disputes, resolutions, enforcement).
This means I didn’t just study one domain. I modeled the entire causal chain:
Cognition →
Incentive →
Action →
Conflict →
Adjudication →
Restitution
And I noticed something crucial: the same logical structure reappeared at every level.
That structure was evolutionary computation.
Trial and error.
Cost and benefit.
Variation and selection.
Reciprocity and punishment.
In other words: the universe behaves as a cooperative computation under constraint, and so must any successful human system.
So I asked the natural next question: Can we model that process at every level of civilization—cognitive, moral, legal, economic, and political? And the answer was yes.
But no one had done it—because no one had unified those grammars under the same method of operational, testable, decidable reasoning.
V. Stories vs. Simulations
Most intellectual traditions are still built around narratives:
Plato: allegories.
Hegel: dialectics.
Rawls: thought experiments.
Marx: historical inevitabilities.
Even most economists rely on idealized simplifications.
But I don’t think in narratives. I think in simulations.
I model actors.
I define constraints.
I calculate outcomes.
I test for failure modes.
This is why my work often feels alien to others. I’m not using their grammar. I’m not offering a story. I’m offering a compiler—a machine for deciding moral, legal, and institutional questions under real-world constraints.
This is why I define truth not as “correspondence” or “coherence,” but as survival under adversarial recursion with no externalities. That is a systems definition of truth. And it forces an entirely new set of constraints on what can be claimed, believed, or enforced.
VI. What Emerged: A Civilizational Operating System
What emerged from this lifelong modeling wasn’t a “theory.” It was a constructive logic of human cooperation. A universal language for modeling truth, reciprocity, and decidability.
I built:
A grammar of operational speech.
A system of reciprocal insurance.
A legal architecture based on testifiability and restitution.
An economic model based on bounded rationality under evolutionary constraint.
A political model based on institutional decidability rather than discretion.
I didn’t invent moral philosophy. I engineered moral computability.
This is what I call Natural Law—not the mystical kind, not the theological kind, but the operational structure of all sustainable cooperation.
And it works because it obeys the same rules the universe does:
Scarcity
Entropy
Evolution
Computation
Reciprocity
Testability
Decidability
No metaphysics. No utopias. Just the minimum viable grammar of cooperation that does not fail at scale.
VII. Why It Had to Be Built
I began to see this clearly in the 1990s. Progressive thought was collapsing into scripted talking points. Conservative thought was collapsing into ineffectual moralizing. And no one—not left, right, or center—was answering hard questions in operational, value-neutral, measurable terms.
It was obvious what was coming: pseudoscience, institutional capture, epistemic collapse, and eventually civil war. And that’s what we’re living through now.
So I made a decision. I would build the language of truth and cooperation that our institutions failed to produce.
Not because I had all the answers. But because no one else was even asking the right questions in the right language.
That decision cost me wealth, relationships, status—and I don’t regret it. Because the world doesn’t need another ideology. It needs a system of decidability that can constrain all ideologies.
That’s what I built. That’s what this is. And now, finally, I’m teaching it.