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Version: v0.1
Status: Exploratory Note
Last updated: 2026-01-04
This exploratory note proposes a minimal logical typology for rule-like statements in science.
It argues that many scientific rules are treated as universal despite being conditional or probabilistic in structure. The resulting ambiguity produces apparent counterexamples, false expectations, and conceptual disputes.
By distinguishing between universal, conditional, and probabilistic rules, the note clarifies the logical status of such claims without introducing unnecessary theoretical complexity.
Scientific discourse is saturated with rules, laws, principles, and general statements.
These are often formulated as if they possessed universal validity. However, closer inspection shows that many of them depend on unstated conditions or express statistical regularities rather than necessity.
As with all model-based claims, the decisive question is therefore not whether a rule is true, but:
What kind of claim is being made —
and under which conditions does it hold?
In practice, rule-like statements are frequently formulated without an explicit declaration of their logical status.
Conditional validity is compressed into universal language, and probabilistic regularities are read as deterministic constraints.
This implicit universalization leads to recurring problems:
The issue is not empirical error, but structural ambiguity.
To remove this ambiguity, a minimal and sufficient classification of rules can be introduced.
A universal rule claims exceptionless validity within a specified domain.
It has the logical form:
∀x ∈ M : P(x)
Such rules admit no exceptions within their domain. A single counterexample invalidates the claim.
Universal rules therefore require extremely high standards of precision and justification and are rare outside formal systems such as mathematics and logic.
A conditional rule asserts validity only under explicitly stated conditions.
Its logical form is:
∀x ∈ M : (B(x) → P(x))
No claim is made outside the specified conditions. Apparent exceptions indicate unmet conditions, not rule failure.
Most scientific “laws” in empirical disciplines fall into this category, despite often being presented in universal language.
A probabilistic rule describes regularities in terms of likelihood rather than necessity.
In simplified form:
Pr(Y | B) = p, with 0 < p < 1
Even when conditions are met, outcomes are not guaranteed. Deviations are expected and only meaningful at the statistical level.
Probabilistic rules dominate domains involving complex, adaptive, or social systems.
The notation used above draws from elementary predicate logic and probability theory.
It is intended to clarify the type of claim being made, not to formalize empirical content.
Several recurrent errors arise from failing to distinguish between rule types:
These errors are structural rather than empirical.
A minimal meta-rule follows:
Rule-like statements should be explicitly identified as
universal, conditional, or probabilistic.
This classification clarifies logical status without restricting substantive inquiry.
Many disputes about whether a rule “holds” are, in fact, disputes about what kind of rule is being claimed.
Making the rule type explicit resolves apparent contradictions without requiring new data.
This document is an exploratory note.
It is intentionally minimal and open-ended. Its purpose is to clarify logical structure, not to settle disciplinary debates.
Wende, A. (2026).
On the Typing of Rules: Why Scientific Rules Must Be Classified as Universal, Conditional, or Probabilistic.
Exploratory Notes, systemic-effect.org. Version 0.1.
https://systemic-effect.org/exploratory-notes/typing-of-rules/v0.1.md
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Exploratory Notes